From d8d03b5a6901387745d7943fed9a0b334773e136 Mon Sep 17 00:00:00 2001
From: jesse-ux <a740821056@gmail.com>
Date: Sun, 27 Sep 2026 01:24:04 +0800
Subject: [PATCH] research: consultation evidence-card inventory and draft

Measure the model-visible consultation payload on three public charts, draft per-domain cards, and record the Narayana/pratyantar projection gap as BUG-1054. No runtime behavior change.
---
 docs/BUG_HISTORY.md                           |   15 +
 ...onsult_evidence_card_draft_2026_09_27.json |  601 ++
 ...lt_evidence_card_inventory_2026_09_27.json | 6321 +++++++++++++++++
 ...nsult_evidence_card_research_2026_09_27.md |  189 +
 ...idence_card_sample_parents_2026_09_27.json |  294 +
 ...sult_evidence_card_timings_2026_09_27.json |   35 +
 ...consult-evidence-card-research-20260927.md |   30 +
 docs/tasks/README.md                          |    2 +-
 scripts/research/consult_evidence_card_lib.py |  811 +++
 scripts/research/consult_evidence_card_run.py |  263 +
 .../research/consult_evidence_card_time.py    |   88 +
 .../research/project_consult_model_context.ts |  107 +
 tests/test_consult_evidence_card_research.py  |  127 +
 13 files changed, 8882 insertions(+), 1 deletion(-)
 create mode 100644 docs/research/consult_evidence_card_draft_2026_09_27.json
 create mode 100644 docs/research/consult_evidence_card_inventory_2026_09_27.json
 create mode 100644 docs/research/consult_evidence_card_research_2026_09_27.md
 create mode 100644 docs/research/consult_evidence_card_sample_parents_2026_09_27.json
 create mode 100644 docs/research/consult_evidence_card_timings_2026_09_27.json
 create mode 100644 docs/tasks/PROGRESS-consult-evidence-card-research-20260927.md
 create mode 100644 scripts/research/consult_evidence_card_lib.py
 create mode 100644 scripts/research/consult_evidence_card_run.py
 create mode 100644 scripts/research/consult_evidence_card_time.py
 create mode 100644 scripts/research/project_consult_model_context.ts
 create mode 100644 tests/test_consult_evidence_card_research.py

diff --git a/docs/BUG_HISTORY.md b/docs/BUG_HISTORY.md
index 936becf8..d018d8f6 100644
--- a/docs/BUG_HISTORY.md
+++ b/docs/BUG_HISTORY.md
@@ -14186,3 +14186,18 @@
 - 相关记录：BUG-612（分段写作再调工具，同一 compose 结构）、BUG-942 / BUG-943 / BUG-944（三通道重做，保留了丢弃主循环正文的结构）、BUG-1051（写回答时钟与结算规则，本单沿用并搬进主循环）、BUG-305、BUG-937（主循环开 thinking，不得用非 `auto` 的 toolChoice）。
 - 复发自：无（新缺陷）。
 - 修复版本：待提交
+
+## BUG-1054 | 咨询投影把当前 Narayana 段和子运日期裁成空
+
+- 状态：investigating
+- 首次发现 / 最近更新：2026-09-27 / 2026-09-27
+- 影响面：`frontend/src/mastra/consultation-workflow.ts` 的 `toModelOutput` / `projectAllowlistedTree`；普通咨询写答案时看到的 timing 卡
+- 现象：引擎已经算出当前 Narayana 段和 Vimshottari 子运（pratyantar）起止日期，投影给模型的 timing 卡里 `current_dasha` 是空对象，子运日期整段不在。
+- 触发条件：有出生分钟的本命咨询走 `toModelOutput`。2026-09-27 数据卡调研用 3 张公开 AA 盘 × 10 种问法，30/30 都是这个形状。
+- 根因：timing 投影只保留 allowlist 里的键。Narayana 当前段写在 `current_dasha.md` / `ad` / `pd` 下，`md` 不在 allowlist 里，于是对象被留成空。子运日期的键是 `pratyantar_dasha_timeline`，也不在 allowlist 里，整段被丢掉。大运和子运（antardasha）的日期键在 allowlist 里，所以那两段还在。
+- 修复：未修。本单是调研，不改投影。
+- 验证：调研脚本对 30 次投影做了结构化比对：上升、月亮星座与宫位、当前大运起止、D12 落点与引擎一致；Narayana 当前星座和子运起止在卡里是空。见 `docs/research/consult_evidence_card_research_2026_09_27.md`。
+- 防复发：实现单补投影时，要锁住「引擎当前 Narayana 星座和子运起止日期原样出现在模型 timing 卡里」，不能只断言 `narayana_dasha` 键存在。
+- 相关记录：BUG-287（同一条 allowlist 曾经把分盘和审计表整段挡住；这次是嵌套键还没放行，不是「没算」复发）
+- 复发自：无
+- 修复版本：无
diff --git a/docs/research/consult_evidence_card_draft_2026_09_27.json b/docs/research/consult_evidence_card_draft_2026_09_27.json
new file mode 100644
index 00000000..b7f4a2e8
--- /dev/null
+++ b/docs/research/consult_evidence_card_draft_2026_09_27.json
@@ -0,0 +1,601 @@
+{
+  "card_version": "evidence-card-draft-20260927",
+  "reference_date": "2026-09-27",
+  "ayanamsa": "raman",
+  "node_mode": "mean",
+  "cards": {
+    "career": {
+      "label": "事业",
+      "vargas": [
+        "D10"
+      ],
+      "houses": [
+        10
+      ],
+      "arudha": [
+        "A10"
+      ],
+      "karakas": [
+        "AmK"
+      ],
+      "planets": [],
+      "yogas": true,
+      "transits": true,
+      "ashtakavarga": false,
+      "shadbala": true
+    },
+    "marriage": {
+      "label": "婚恋",
+      "vargas": [
+        "D9"
+      ],
+      "houses": [
+        7
+      ],
+      "arudha": [
+        "UL",
+        "A7"
+      ],
+      "karakas": [
+        "DK"
+      ],
+      "planets": [
+        "venus",
+        "jupiter"
+      ],
+      "yogas": false,
+      "transits": true,
+      "ashtakavarga": false,
+      "shadbala": false
+    },
+    "wealth": {
+      "label": "财富",
+      "vargas": [
+        "D2",
+        "D11"
+      ],
+      "houses": [
+        2,
+        11,
+        9,
+        5
+      ],
+      "arudha": [],
+      "karakas": [],
+      "planets": [],
+      "yogas": true,
+      "transits": false,
+      "ashtakavarga": true,
+      "shadbala": true
+    },
+    "health": {
+      "label": "健康",
+      "vargas": [
+        "D6",
+        "D8",
+        "D30"
+      ],
+      "houses": [
+        6,
+        8
+      ],
+      "arudha": [],
+      "karakas": [],
+      "planets": [],
+      "yogas": false,
+      "transits": true,
+      "ashtakavarga": false,
+      "shadbala": true
+    },
+    "education": {
+      "label": "学习",
+      "vargas": [
+        "D5",
+        "D24"
+      ],
+      "houses": [
+        5,
+        9
+      ],
+      "arudha": [],
+      "karakas": [],
+      "planets": [
+        "mercury",
+        "jupiter"
+      ],
+      "yogas": false,
+      "transits": false,
+      "ashtakavarga": false,
+      "shadbala": false
+    },
+    "migration": {
+      "label": "迁居",
+      "vargas": [
+        "D4",
+        "D12"
+      ],
+      "houses": [
+        4,
+        12
+      ],
+      "arudha": [],
+      "karakas": [],
+      "planets": [],
+      "yogas": false,
+      "transits": false,
+      "ashtakavarga": false,
+      "shadbala": false
+    },
+    "family": {
+      "label": "家庭（现路由，父母与子女混在一起）",
+      "vargas": [
+        "D7",
+        "D12"
+      ],
+      "houses": [
+        4,
+        5,
+        9
+      ],
+      "arudha": [],
+      "karakas": [],
+      "planets": [],
+      "yogas": false,
+      "transits": false,
+      "ashtakavarga": false,
+      "shadbala": false
+    },
+    "parents": {
+      "label": "父母",
+      "vargas": [
+        "D12"
+      ],
+      "houses": [
+        4,
+        9
+      ],
+      "arudha": [],
+      "karakas": [],
+      "planets": [
+        "sun",
+        "moon"
+      ],
+      "yogas": false,
+      "transits": false,
+      "ashtakavarga": false,
+      "shadbala": false,
+      "basis": [
+        "skills/jyotish-vedic-astrology/references/strict-workflow-router.md shared baseline: D12 for family/ancestral themes",
+        "references/birth-time-rectification-decision-tree.md section 4: 父母/家族 -> D12"
+      ]
+    },
+    "children": {
+      "label": "子女",
+      "vargas": [
+        "D7"
+      ],
+      "houses": [
+        5
+      ],
+      "arudha": [],
+      "karakas": [
+        "PK"
+      ],
+      "planets": [
+        "jupiter"
+      ],
+      "yogas": false,
+      "transits": false,
+      "ashtakavarga": false,
+      "shadbala": false,
+      "basis": [
+        "skills/jyotish-vedic-astrology/references/strict-workflow-router.md shared baseline: D7 for children",
+        "references/birth-time-rectification-decision-tree.md section 4: 子女/生育 -> D7"
+      ]
+    },
+    "general": {
+      "label": "综合",
+      "vargas": [
+        "D9",
+        "D10",
+        "D2"
+      ],
+      "houses": [
+        1,
+        10,
+        7,
+        2
+      ],
+      "arudha": [
+        "A10"
+      ],
+      "karakas": [],
+      "planets": [],
+      "yogas": true,
+      "transits": true,
+      "ashtakavarga": true,
+      "shadbala": true
+    }
+  },
+  "source_matrix": {
+    "domains": [
+      {
+        "domain": "annual",
+        "registry_required_layers": [
+          "D1",
+          "Annual chart boundary",
+          "Dasha",
+          "Transit",
+          "Tajika candidate"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [
+          "Narayana Dasha",
+          "Vimshottari sub-periods",
+          "Chara Dasha"
+        ],
+        "python_focus_techniques": [
+          "Annual chart boundary",
+          "Dasha",
+          "Transit",
+          "Tajika candidate",
+          "claim boundary"
+        ],
+        "card_vargas": [],
+        "parents_children_split": false
+      },
+      {
+        "domain": "career",
+        "registry_required_layers": [
+          "D1",
+          "D10",
+          "10th house/lord",
+          "A10",
+          "AmK",
+          "Vimshottari",
+          "Narayana",
+          "Transit"
+        ],
+        "methodology_strict_route": "career-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Arudha / UL / A10",
+          "Narayana Dasha",
+          "Chara Dasha"
+        ],
+        "python_focus_techniques": [
+          "D10",
+          "Dasha",
+          "Shadbala",
+          "Transit",
+          "Narayana Dasha"
+        ],
+        "card_vargas": [
+          "D10"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "children",
+        "registry_required_layers": [],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [],
+        "card_vargas": [
+          "D7"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "education",
+        "registry_required_layers": [
+          "D1",
+          "D24",
+          "5th/9th houses",
+          "Mercury/Jupiter",
+          "Dasha"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D5",
+          "D24",
+          "5th house",
+          "9th house",
+          "Dasha"
+        ],
+        "card_vargas": [
+          "D5",
+          "D24"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "family",
+        "registry_required_layers": [
+          "D1",
+          "D7",
+          "D12",
+          "4th/5th/9th houses",
+          "Dasha"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D7",
+          "D12",
+          "4th house",
+          "5th house",
+          "9th house",
+          "Dasha"
+        ],
+        "card_vargas": [
+          "D7",
+          "D12"
+        ],
+        "parents_children_split": true
+      },
+      {
+        "domain": "general",
+        "registry_required_layers": [
+          "D1",
+          "D9",
+          "D10",
+          "D2",
+          "Dasha",
+          "Narayana",
+          "Transit",
+          "Functional Benefic/Malefic"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D1",
+          "D9",
+          "Dasha",
+          "Yoga",
+          "Shadbala",
+          "Ashtakavarga"
+        ],
+        "card_vargas": [
+          "D9",
+          "D10",
+          "D2"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "health",
+        "registry_required_layers": [
+          "D1",
+          "D6",
+          "D8",
+          "6th/8th houses",
+          "Dasha",
+          "non-medical boundary"
+        ],
+        "methodology_strict_route": "health-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Shadbala components"
+        ],
+        "python_focus_techniques": [
+          "D6",
+          "D8",
+          "D30",
+          "Dasha",
+          "Narayana Dasha",
+          "Shadbala",
+          "Transit",
+          "Functional Benefic/Malefic"
+        ],
+        "card_vargas": [
+          "D6",
+          "D8",
+          "D30"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "marriage",
+        "registry_required_layers": [
+          "D1",
+          "D9",
+          "7th house/lord",
+          "Venus/Jupiter",
+          "DK",
+          "UL",
+          "A7",
+          "Vimshottari",
+          "Narayana",
+          "Transit"
+        ],
+        "methodology_strict_route": "relationship-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Arudha / UL / A10"
+        ],
+        "python_focus_techniques": [
+          "D9",
+          "UL Upapada",
+          "Dasha",
+          "Nakshatra",
+          "Vivah Saham"
+        ],
+        "card_vargas": [
+          "D9"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "migration",
+        "registry_required_layers": [
+          "D1",
+          "D4",
+          "D12",
+          "4th/12th houses",
+          "Dasha",
+          "Narayana"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D4",
+          "D12",
+          "12th house",
+          "Dasha",
+          "Narayana Dasha"
+        ],
+        "card_vargas": [
+          "D4",
+          "D12"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "parents",
+        "registry_required_layers": [],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [],
+        "card_vargas": [
+          "D12"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "timing",
+        "registry_required_layers": [
+          "Vimshottari",
+          "Narayana",
+          "Transit",
+          "Varga",
+          "negative holdout gate"
+        ],
+        "methodology_strict_route": "event-timing-strict",
+        "ts_must_use_layers": [
+          "Narayana Dasha",
+          "Vimshottari sub-periods",
+          "Transits / Sade Sati",
+          "Chara Dasha"
+        ],
+        "python_focus_techniques": [
+          "Dasha",
+          "Transit",
+          "Double Transit",
+          "Gochara"
+        ],
+        "card_vargas": [],
+        "parents_children_split": false
+      },
+      {
+        "domain": "wealth",
+        "registry_required_layers": [
+          "D1",
+          "D2",
+          "D11",
+          "2nd/11th/9th/5th houses",
+          "Wealth Yogas",
+          "Ashtakavarga",
+          "Dasha"
+        ],
+        "methodology_strict_route": "finance-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Ashtakavarga"
+        ],
+        "python_focus_techniques": [
+          "D2",
+          "D11",
+          "Dasha",
+          "Shadbala",
+          "Ashtakavarga"
+        ],
+        "card_vargas": [
+          "D2",
+          "D11"
+        ],
+        "parents_children_split": false
+      }
+    ],
+    "skill_citations": {
+      "d12_family": "references/strict-workflow-router.md: D12 for family/ancestral themes",
+      "d7_children": "references/strict-workflow-router.md: D7 for children",
+      "decision_tree_parents": "references/birth-time-rectification-decision-tree.md: 父母/家族 -> D12",
+      "decision_tree_children": "references/birth-time-rectification-decision-tree.md: 子女/生育 -> D7"
+    }
+  },
+  "telemetry": {
+    "stores": "numbers, enums, and field names only",
+    "does_not_store": [
+      "question text",
+      "answer text",
+      "birth date",
+      "birth time",
+      "birth place",
+      "name",
+      "email",
+      "user id",
+      "session id",
+      "matched substring"
+    ],
+    "fields": [
+      {
+        "name": "domain",
+        "type": "enum",
+        "values": [
+          "career",
+          "marriage",
+          "wealth",
+          "health",
+          "education",
+          "migration",
+          "family",
+          "general",
+          "parents",
+          "children"
+        ]
+      },
+      {
+        "name": "card_version",
+        "type": "enum",
+        "values": [
+          "evidence-card-draft-20260927"
+        ]
+      },
+      {
+        "name": "card_chars",
+        "type": "int"
+      },
+      {
+        "name": "card_token_estimate",
+        "type": "int"
+      },
+      {
+        "name": "cited_field_ids",
+        "type": "enum[]",
+        "note": "ids from the card schema, not free text"
+      },
+      {
+        "name": "feedback",
+        "type": "enum",
+        "values": [
+          "up",
+          "down",
+          "none"
+        ]
+      }
+    ],
+    "citation_method": {
+      "rule": "A field is cited when its scalar value appears in the answer and the value is an ISO date, a degree token, or a compound planet-in-sign phrase of at least 8 characters. Bare planet or sign names are not counted.",
+      "false_positive": "A date or degree that also appears in the question, or a repeated stock phrase, can be counted without the model using that field.",
+      "false_negative": "A paraphrase that names the period without copying the date is not counted.",
+      "stored": "Only the field id. The matched text is discarded."
+    },
+    "aggregates": [
+      "count of answers by domain and card_version",
+      "fields whose cited rate stays under 5 percent after 30 answers in that domain",
+      "down rate by domain and card_version"
+    ]
+  }
+}
\ No newline at end of file
diff --git a/docs/research/consult_evidence_card_inventory_2026_09_27.json b/docs/research/consult_evidence_card_inventory_2026_09_27.json
new file mode 100644
index 00000000..9f5633b3
--- /dev/null
+++ b/docs/research/consult_evidence_card_inventory_2026_09_27.json
@@ -0,0 +1,6321 @@
+{
+  "baseline": "76924e3362c0a47d9d8de896c448c66055826f70",
+  "reference_date": "2026-09-27",
+  "ayanamsa": "raman",
+  "node_mode": "mean",
+  "pythonhashseed": "0",
+  "external_vedastro": "not_called",
+  "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer.",
+  "charts": [
+    {
+      "id": "steve_jobs",
+      "label": "Steve Jobs",
+      "source": "references/real_case_calibration/minute_rectification_development_v1.json",
+      "case_id": "steve_jobs_1955_development",
+      "rodden_rating": "AA"
+    },
+    {
+      "id": "barack_obama",
+      "label": "Barack Obama",
+      "source": "references/real_case_calibration/minute_rectification_holdout_v4.json",
+      "case_id": "barack_obama_1961_aa_v4_holdout",
+      "rodden_rating": "AA"
+    },
+    {
+      "id": "elizabeth_taylor",
+      "label": "Elizabeth Taylor",
+      "source": "references/real_case_calibration/minute_rectification_holdout_v4.json",
+      "case_id": "elizabeth_taylor_1932_aa_v4_holdout",
+      "rodden_rating": "AA"
+    }
+  ],
+  "source_matrix": {
+    "domains": [
+      {
+        "domain": "annual",
+        "registry_required_layers": [
+          "D1",
+          "Annual chart boundary",
+          "Dasha",
+          "Transit",
+          "Tajika candidate"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [
+          "Narayana Dasha",
+          "Vimshottari sub-periods",
+          "Chara Dasha"
+        ],
+        "python_focus_techniques": [
+          "Annual chart boundary",
+          "Dasha",
+          "Transit",
+          "Tajika candidate",
+          "claim boundary"
+        ],
+        "card_vargas": [],
+        "parents_children_split": false
+      },
+      {
+        "domain": "career",
+        "registry_required_layers": [
+          "D1",
+          "D10",
+          "10th house/lord",
+          "A10",
+          "AmK",
+          "Vimshottari",
+          "Narayana",
+          "Transit"
+        ],
+        "methodology_strict_route": "career-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Arudha / UL / A10",
+          "Narayana Dasha",
+          "Chara Dasha"
+        ],
+        "python_focus_techniques": [
+          "D10",
+          "Dasha",
+          "Shadbala",
+          "Transit",
+          "Narayana Dasha"
+        ],
+        "card_vargas": [
+          "D10"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "children",
+        "registry_required_layers": [],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [],
+        "card_vargas": [
+          "D7"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "education",
+        "registry_required_layers": [
+          "D1",
+          "D24",
+          "5th/9th houses",
+          "Mercury/Jupiter",
+          "Dasha"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D5",
+          "D24",
+          "5th house",
+          "9th house",
+          "Dasha"
+        ],
+        "card_vargas": [
+          "D5",
+          "D24"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "family",
+        "registry_required_layers": [
+          "D1",
+          "D7",
+          "D12",
+          "4th/5th/9th houses",
+          "Dasha"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D7",
+          "D12",
+          "4th house",
+          "5th house",
+          "9th house",
+          "Dasha"
+        ],
+        "card_vargas": [
+          "D7",
+          "D12"
+        ],
+        "parents_children_split": true
+      },
+      {
+        "domain": "general",
+        "registry_required_layers": [
+          "D1",
+          "D9",
+          "D10",
+          "D2",
+          "Dasha",
+          "Narayana",
+          "Transit",
+          "Functional Benefic/Malefic"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D1",
+          "D9",
+          "Dasha",
+          "Yoga",
+          "Shadbala",
+          "Ashtakavarga"
+        ],
+        "card_vargas": [
+          "D9",
+          "D10",
+          "D2"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "health",
+        "registry_required_layers": [
+          "D1",
+          "D6",
+          "D8",
+          "6th/8th houses",
+          "Dasha",
+          "non-medical boundary"
+        ],
+        "methodology_strict_route": "health-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Shadbala components"
+        ],
+        "python_focus_techniques": [
+          "D6",
+          "D8",
+          "D30",
+          "Dasha",
+          "Narayana Dasha",
+          "Shadbala",
+          "Transit",
+          "Functional Benefic/Malefic"
+        ],
+        "card_vargas": [
+          "D6",
+          "D8",
+          "D30"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "marriage",
+        "registry_required_layers": [
+          "D1",
+          "D9",
+          "7th house/lord",
+          "Venus/Jupiter",
+          "DK",
+          "UL",
+          "A7",
+          "Vimshottari",
+          "Narayana",
+          "Transit"
+        ],
+        "methodology_strict_route": "relationship-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Arudha / UL / A10"
+        ],
+        "python_focus_techniques": [
+          "D9",
+          "UL Upapada",
+          "Dasha",
+          "Nakshatra",
+          "Vivah Saham"
+        ],
+        "card_vargas": [
+          "D9"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "migration",
+        "registry_required_layers": [
+          "D1",
+          "D4",
+          "D12",
+          "4th/12th houses",
+          "Dasha",
+          "Narayana"
+        ],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [
+          "D4",
+          "D12",
+          "12th house",
+          "Dasha",
+          "Narayana Dasha"
+        ],
+        "card_vargas": [
+          "D4",
+          "D12"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "parents",
+        "registry_required_layers": [],
+        "methodology_strict_route": null,
+        "ts_must_use_layers": [],
+        "python_focus_techniques": [],
+        "card_vargas": [
+          "D12"
+        ],
+        "parents_children_split": false
+      },
+      {
+        "domain": "timing",
+        "registry_required_layers": [
+          "Vimshottari",
+          "Narayana",
+          "Transit",
+          "Varga",
+          "negative holdout gate"
+        ],
+        "methodology_strict_route": "event-timing-strict",
+        "ts_must_use_layers": [
+          "Narayana Dasha",
+          "Vimshottari sub-periods",
+          "Transits / Sade Sati",
+          "Chara Dasha"
+        ],
+        "python_focus_techniques": [
+          "Dasha",
+          "Transit",
+          "Double Transit",
+          "Gochara"
+        ],
+        "card_vargas": [],
+        "parents_children_split": false
+      },
+      {
+        "domain": "wealth",
+        "registry_required_layers": [
+          "D1",
+          "D2",
+          "D11",
+          "2nd/11th/9th/5th houses",
+          "Wealth Yogas",
+          "Ashtakavarga",
+          "Dasha"
+        ],
+        "methodology_strict_route": "finance-timing-strict",
+        "ts_must_use_layers": [
+          "Formal Vargas D1–D60",
+          "Ashtakavarga"
+        ],
+        "python_focus_techniques": [
+          "D2",
+          "D11",
+          "Dasha",
+          "Shadbala",
+          "Ashtakavarga"
+        ],
+        "card_vargas": [
+          "D2",
+          "D11"
+        ],
+        "parents_children_split": false
+      }
+    ],
+    "skill_citations": {
+      "d12_family": "references/strict-workflow-router.md: D12 for family/ancestral themes",
+      "d7_children": "references/strict-workflow-router.md: D7 for children",
+      "decision_tree_parents": "references/birth-time-rectification-decision-tree.md: 父母/家族 -> D12",
+      "decision_tree_children": "references/birth-time-rectification-decision-tree.md: 子女/生育 -> D7"
+    }
+  },
+  "runs": [
+    {
+      "id": "steve_jobs__career",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "career",
+      "domain": "career",
+      "wall_seconds": 5.539,
+      "workflow_chars": 411737,
+      "route": "career",
+      "focus_techniques": [
+        "D10",
+        "Dasha",
+        "Shadbala",
+        "Transit",
+        "Narayana Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__career",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 7313,
+        "model_chars": 142680
+      },
+      "categories": {
+        "categories": {
+          "core": 47808,
+          "status": 16082,
+          "not_applicable": 1972,
+          "research": 43926,
+          "western": 32892
+        },
+        "total_chars": 142680,
+        "category_sum": 142680,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 142680,
+          "token_estimate": 40766,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 67640,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3971,
+        "token_estimate": 1135,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D10"
+          ],
+          "expected_vargas": [
+            "D10"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas",
+        "transits",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": {
+        "card_id": "career",
+        "label": "事业",
+        "question": "未来一年，事业和收入该关注什么？",
+        "route": "career",
+        "base": {
+          "ascendant": {
+            "degree": 0.51,
+            "degree_in_sign": 0.51,
+            "lon": 150.5069,
+            "sign": "Virgo",
+            "sign_idx": 5
+          },
+          "houses": {
+            "1": {
+              "sign": "Virgo",
+              "sign_idx": 5
+            },
+            "2": {
+              "sign": "Libra",
+              "sign_idx": 6
+            },
+            "3": {
+              "sign": "Scorpio",
+              "sign_idx": 7
+            },
+            "4": {
+              "sign": "Sagittarius",
+              "sign_idx": 8
+            },
+            "5": {
+              "sign": "Capricorn",
+              "sign_idx": 9
+            },
+            "6": {
+              "sign": "Aquarius",
+              "sign_idx": 10
+            },
+            "7": {
+              "sign": "Pisces",
+              "sign_idx": 11
+            },
+            "8": {
+              "sign": "Aries",
+              "sign_idx": 0
+            },
+            "9": {
+              "sign": "Taurus",
+              "sign_idx": 1
+            },
+            "10": {
+              "sign": "Gemini",
+              "sign_idx": 2
+            },
+            "11": {
+              "sign": "Cancer",
+              "sign_idx": 3
+            },
+            "12": {
+              "sign": "Leo",
+              "sign_idx": 4
+            }
+          },
+          "planet_placements": {
+            "Jupiter": {
+              "sign": "Gemini",
+              "house": 10
+            },
+            "Ketu": {
+              "sign": "Gemini",
+              "house": 10
+            },
+            "Mars": {
+              "sign": "Aries",
+              "house": 8
+            },
+            "Mercury": {
+              "sign": "Capricorn",
+              "house": 5
+            },
+            "Moon": {
+              "sign": "Pisces",
+              "house": 7
+            },
+            "Rahu": {
+              "sign": "Sagittarius",
+              "house": 4
+            },
+            "Saturn": {
+              "sign": "Libra",
+              "house": 2
+            },
+            "Sun": {
+              "sign": "Aquarius",
+              "house": 6
+            },
+            "Venus": {
+              "sign": "Sagittarius",
+              "house": 4
+            }
+          },
+          "functional_benefic_malefic": {
+            "status": "used",
+            "ascendant": "Virgo",
+            "functional_benefics": [
+              "Mercury",
+              "Saturn",
+              "Venus"
+            ],
+            "functional_malefics": [
+              "Mars",
+              "Moon",
+              "Sun"
+            ],
+            "functional_neutrals": [
+              "Jupiter"
+            ],
+            "yogakarakas": [
+              "Mercury"
+            ],
+            "owned_houses": {
+              "Jupiter": [
+                4,
+                7
+              ],
+              "Mars": [
+                3,
+                8
+              ],
+              "Mercury": [
+                1,
+                10
+              ],
+              "Moon": [
+                11
+              ],
+              "Saturn": [
+                5,
+                6
+              ],
+              "Sun": [
+                12
+              ],
+              "Venus": [
+                2,
+                9
+              ]
+            },
+            "effect_on_confidence": "高严谨模式下必须叠加功能性宫主吉凶与自然吉凶；若功能属性与自然属性冲突，应降低置信度或显式标记冲突。",
+            "source": "strict_functional_benefic_malefic_v1"
+          },
+          "vimshottari": {
+            "status": "ready",
+            "source": "chart.dasha.periods + dasha_analyzer.build_antardasha",
+            "method": "vimshottari_antardasha_proportional",
+            "current": {
+              "mahadasha": {
+                "lord": "Rahu",
+                "start": "2023-02-25",
+                "end": "2041-02-24"
+              },
+              "antardasha": {
+                "lord": "Jupiter",
+                "start": "2025-11-07",
+                "end": "2028-04-01"
+              }
+            },
+            "next": {
+              "lord": "Saturn",
+              "start": "2028-04-01",
+              "end": "2031-02-06"
+            },
+            "boundaries": [
+              {
+                "lord": "Rahu",
+                "start": "2023-02-25",
+                "end": "2025-11-07"
+              },
+              {
+                "lord": "Jupiter",
+                "start": "2025-11-07",
+                "end": "2028-04-01"
+              },
+              {
+                "lord": "Saturn",
+                "start": "2028-04-01",
+                "end": "2031-02-06"
+              },
+              {
+                "lord": "Mercury",
+                "start": "2031-02-06",
+                "end": "2033-08-25"
+              },
+              {
+                "lord": "Ketu",
+                "start": "2033-08-25",
+                "end": "2034-09-13"
+              },
+              {
+                "lord": "Venus",
+                "start": "2034-09-13",
+                "end": "2037-09-12"
+              },
+              {
+                "lord": "Sun",
+                "start": "2037-09-12",
+                "end": "2038-08-07"
+              },
+              {
+                "lord": "Moon",
+                "start": "2038-08-07",
+                "end": "2040-02-06"
+              },
+              {
+                "lord": "Mars",
+                "start": "2040-02-06",
+                "end": "2041-02-24"
+              }
+            ],
+            "boundary_count": 9,
+            "summary": "当前 Rahu 大运下的小运为 Jupiter，边界 2025-11-07 至 2028-04-01。更细的 Pratyantardasha 与行运触发不在本层计算范围内。"
+          },
+          "narayana_dasha": {
+            "current_dasha": {}
+          }
+        },
+        "domain": {
+          "vargas": {
+            "D10": {
+              "lagna": "Taurus",
+              "planets": {
+                "Sun": "Gemini",
+                "Moon": "Aries",
+                "Mars": "Gemini",
+                "Mercury": "Aries",
+                "Jupiter": "Pisces",
+                "Venus": "Virgo",
+                "Saturn": "Cancer",
+                "Rahu": "Pisces",
+                "Ketu": "Virgo"
+              },
+              "name": "Dasamsa",
+              "meaning": "事业"
+            }
+          },
+          "houses": {
+            "10": {
+              "sign": "Gemini",
+              "sign_idx": 2
+            }
+          },
+          "planets": {},
+          "arudha": {},
+          "karakas": {},
+          "yogas": {
+            "status": "executed",
+            "count": 6,
+            "yogas": [
+              {
+                "name": "Sunaphaa Yoga",
+                "claim_boundary": "governed_support_only_candidate_ready"
+              },
+              {
+                "name": "Anaphaa Yoga",
+                "claim_boundary": "governed_support_only_candidate_ready"
+              },
+              {
+                "name": "Duradhara Yoga",
+                "claim_boundary": "governed_support_only_candidate_ready"
+              },
+              {
+                "name": "Vosi Yoga",
+                "claim_boundary": "governed_support_only_candidate_ready"
+              },
+              {
+                "name": "Ubhayachara Yoga",
+                "claim_boundary": "governed_support_only_candidate_ready"
+              },
+              {
+                "name": "Naukaa Yoga",
+                "claim_boundary": "governed_support_only_candidate_ready"
+              }
+            ]
+          },
+          "transits": {
+            "status": "executed",
+            "sade_sati": {
+              "active": true,
+              "phase": "peak",
+              "phase_name": "高峰期（Peak Phase）",
+              "moon_sign": "Pisces",
+              "saturn_sign": "Pisces",
+              "intensity": "高潮"
+            },
+            "triggers": [
+              {
+                "date": "2026-10-26",
+                "planet": "Saturn",
+                "target": "Moon",
+                "kind": "transit_contact",
+                "orb": 0.93
+              }
+            ],
+            "trigger_count": 1,
+            "search_period": {
+              "start": "2026-09-27",
+              "end": "2026-12-26"
+            },
+            "boundary": "observation windows, not guaranteed events; empty triggers means none in the searched window, not that transits were skipped"
+          },
+          "ashtakavarga": null,
+          "shadbala": {
+            "Jupiter": {},
+            "Mars": {},
+            "Mercury": {},
+            "Moon": {},
+            "Saturn": {},
+            "Sun": {},
+            "Venus": {}
+          }
+        },
+        "gaps": [],
+        "basis": []
+      }
+    },
+    {
+      "id": "steve_jobs__marriage",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "marriage",
+      "domain": "marriage",
+      "wall_seconds": 2.612,
+      "workflow_chars": 407665,
+      "route": "marriage",
+      "focus_techniques": [
+        "D9",
+        "UL Upapada",
+        "Dasha",
+        "Nakshatra",
+        "Vivah Saham"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__marriage",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 9708,
+        "model_chars": 143603
+      },
+      "categories": {
+        "categories": {
+          "core": 46936,
+          "status": 17877,
+          "not_applicable": 1972,
+          "research": 43926,
+          "western": 32892
+        },
+        "total_chars": 143603,
+        "category_sum": 143603,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 143603,
+          "token_estimate": 41029,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66903,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3832,
+        "token_estimate": 1095,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D9"
+          ],
+          "expected_vargas": [
+            "D9"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas",
+        "transits"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "steve_jobs__wealth",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "wealth",
+      "domain": "wealth",
+      "wall_seconds": 2.581,
+      "workflow_chars": 410941,
+      "route": "wealth",
+      "focus_techniques": [
+        "D2",
+        "D11",
+        "Dasha",
+        "Shadbala",
+        "Ashtakavarga"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__wealth",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 6841,
+        "model_chars": 139506
+      },
+      "categories": {
+        "categories": {
+          "core": 44598,
+          "status": 15502,
+          "not_applicable": 2588,
+          "research": 43926,
+          "western": 32892
+        },
+        "total_chars": 139506,
+        "category_sum": 139506,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 139506,
+          "token_estimate": 39859,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66289,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3766,
+        "token_estimate": 1076,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D11",
+            "D2"
+          ],
+          "expected_vargas": [
+            "D2",
+            "D11"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "ashtakavarga",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "steve_jobs__health",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "health",
+      "domain": "health",
+      "wall_seconds": 2.604,
+      "workflow_chars": 431486,
+      "route": "health",
+      "focus_techniques": [
+        "D6",
+        "D8",
+        "D30",
+        "Dasha",
+        "Narayana Dasha",
+        "Shadbala",
+        "Transit",
+        "Functional Benefic/Malefic"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__health",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 2,
+        "methodology_chars": 3772,
+        "model_chars": 138895
+      },
+      "categories": {
+        "categories": {
+          "core": 45256,
+          "status": 14233,
+          "not_applicable": 2588,
+          "research": 43926,
+          "western": 32892
+        },
+        "total_chars": 138895,
+        "category_sum": 138895,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 138895,
+          "token_estimate": 39684,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 67518,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3974,
+        "token_estimate": 1135,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D30",
+            "D6",
+            "D8"
+          ],
+          "expected_vargas": [
+            "D6",
+            "D8",
+            "D30"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "transits",
+        "shadbala"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "steve_jobs__education",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "education",
+      "domain": "education",
+      "wall_seconds": 2.616,
+      "workflow_chars": 429370,
+      "route": "education",
+      "focus_techniques": [
+        "D5",
+        "D24",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__education",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2024,
+        "model_chars": 135306
+      },
+      "categories": {
+        "categories": {
+          "core": 43392,
+          "status": 12485,
+          "not_applicable": 2588,
+          "research": 43949,
+          "western": 32892
+        },
+        "total_chars": 135306,
+        "category_sum": 135306,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 135306,
+          "token_estimate": 38659,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66596,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3637,
+        "token_estimate": 1039,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D24",
+            "D5"
+          ],
+          "expected_vargas": [
+            "D5",
+            "D24"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "steve_jobs__migration",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "migration",
+      "domain": "migration",
+      "wall_seconds": 2.58,
+      "workflow_chars": 429455,
+      "route": "migration",
+      "focus_techniques": [
+        "D4",
+        "D12",
+        "12th house",
+        "Dasha",
+        "Narayana Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__migration",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2024,
+        "model_chars": 135386
+      },
+      "categories": {
+        "categories": {
+          "core": 43392,
+          "status": 12565,
+          "not_applicable": 2588,
+          "research": 43949,
+          "western": 32892
+        },
+        "total_chars": 135386,
+        "category_sum": 135386,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 135386,
+          "token_estimate": 38682,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66636,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3168,
+        "token_estimate": 905,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12",
+            "D4"
+          ],
+          "expected_vargas": [
+            "D4",
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "steve_jobs__family",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "family",
+      "domain": "family",
+      "wall_seconds": 2.588,
+      "workflow_chars": 413339,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__family",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 133308
+      },
+      "categories": {
+        "categories": {
+          "core": 42757,
+          "status": 11122,
+          "not_applicable": 2588,
+          "research": 43949,
+          "western": 32892
+        },
+        "total_chars": 133308,
+        "category_sum": 133308,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 133308,
+          "token_estimate": 38088,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65600,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3228,
+        "token_estimate": 922,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12",
+            "D7"
+          ],
+          "expected_vargas": [
+            "D7",
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "steve_jobs__general",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "general",
+      "domain": "general",
+      "wall_seconds": 2.599,
+      "workflow_chars": 429753,
+      "route": "general",
+      "focus_techniques": [
+        "D1",
+        "D9",
+        "Dasha",
+        "Yoga",
+        "Shadbala",
+        "Ashtakavarga"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__general",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2022,
+        "model_chars": 135284
+      },
+      "categories": {
+        "categories": {
+          "core": 43372,
+          "status": 12483,
+          "not_applicable": 2588,
+          "research": 43949,
+          "western": 32892
+        },
+        "total_chars": 135284,
+        "category_sum": 135284,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 135284,
+          "token_estimate": 38653,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66587,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 5737,
+        "token_estimate": 1639,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D10",
+            "D2",
+            "D9"
+          ],
+          "expected_vargas": [
+            "D9",
+            "D10",
+            "D2"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "transits",
+        "ashtakavarga",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "steve_jobs__parents",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "parents",
+      "domain": "family",
+      "wall_seconds": 2.611,
+      "workflow_chars": 413258,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__parents",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 133290
+      },
+      "categories": {
+        "categories": {
+          "core": 42739,
+          "status": 11122,
+          "not_applicable": 2588,
+          "research": 43949,
+          "western": 32892
+        },
+        "total_chars": 133290,
+        "category_sum": 133290,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 133290,
+          "token_estimate": 38083,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65591,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3576,
+        "token_estimate": 1022,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12"
+          ],
+          "expected_vargas": [
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": {
+        "card_id": "parents",
+        "label": "父母",
+        "question": "我和父母关系如何",
+        "route": "family",
+        "base": {
+          "ascendant": {
+            "degree": 0.51,
+            "degree_in_sign": 0.51,
+            "lon": 150.5069,
+            "sign": "Virgo",
+            "sign_idx": 5
+          },
+          "houses": {
+            "1": {
+              "sign": "Virgo",
+              "sign_idx": 5
+            },
+            "2": {
+              "sign": "Libra",
+              "sign_idx": 6
+            },
+            "3": {
+              "sign": "Scorpio",
+              "sign_idx": 7
+            },
+            "4": {
+              "sign": "Sagittarius",
+              "sign_idx": 8
+            },
+            "5": {
+              "sign": "Capricorn",
+              "sign_idx": 9
+            },
+            "6": {
+              "sign": "Aquarius",
+              "sign_idx": 10
+            },
+            "7": {
+              "sign": "Pisces",
+              "sign_idx": 11
+            },
+            "8": {
+              "sign": "Aries",
+              "sign_idx": 0
+            },
+            "9": {
+              "sign": "Taurus",
+              "sign_idx": 1
+            },
+            "10": {
+              "sign": "Gemini",
+              "sign_idx": 2
+            },
+            "11": {
+              "sign": "Cancer",
+              "sign_idx": 3
+            },
+            "12": {
+              "sign": "Leo",
+              "sign_idx": 4
+            }
+          },
+          "planet_placements": {
+            "Jupiter": {
+              "sign": "Gemini",
+              "house": 10
+            },
+            "Ketu": {
+              "sign": "Gemini",
+              "house": 10
+            },
+            "Mars": {
+              "sign": "Aries",
+              "house": 8
+            },
+            "Mercury": {
+              "sign": "Capricorn",
+              "house": 5
+            },
+            "Moon": {
+              "sign": "Pisces",
+              "house": 7
+            },
+            "Rahu": {
+              "sign": "Sagittarius",
+              "house": 4
+            },
+            "Saturn": {
+              "sign": "Libra",
+              "house": 2
+            },
+            "Sun": {
+              "sign": "Aquarius",
+              "house": 6
+            },
+            "Venus": {
+              "sign": "Sagittarius",
+              "house": 4
+            }
+          },
+          "functional_benefic_malefic": {
+            "status": "used",
+            "ascendant": "Virgo",
+            "functional_benefics": [
+              "Mercury",
+              "Saturn",
+              "Venus"
+            ],
+            "functional_malefics": [
+              "Mars",
+              "Moon",
+              "Sun"
+            ],
+            "functional_neutrals": [
+              "Jupiter"
+            ],
+            "yogakarakas": [
+              "Mercury"
+            ],
+            "owned_houses": {
+              "Jupiter": [
+                4,
+                7
+              ],
+              "Mars": [
+                3,
+                8
+              ],
+              "Mercury": [
+                1,
+                10
+              ],
+              "Moon": [
+                11
+              ],
+              "Saturn": [
+                5,
+                6
+              ],
+              "Sun": [
+                12
+              ],
+              "Venus": [
+                2,
+                9
+              ]
+            },
+            "effect_on_confidence": "高严谨模式下必须叠加功能性宫主吉凶与自然吉凶；若功能属性与自然属性冲突，应降低置信度或显式标记冲突。",
+            "source": "strict_functional_benefic_malefic_v1"
+          },
+          "vimshottari": {
+            "status": "ready",
+            "source": "chart.dasha.periods + dasha_analyzer.build_antardasha",
+            "method": "vimshottari_antardasha_proportional",
+            "current": {
+              "mahadasha": {
+                "lord": "Rahu",
+                "start": "2023-02-25",
+                "end": "2041-02-24"
+              },
+              "antardasha": {
+                "lord": "Jupiter",
+                "start": "2025-11-07",
+                "end": "2028-04-01"
+              }
+            },
+            "next": {
+              "lord": "Saturn",
+              "start": "2028-04-01",
+              "end": "2031-02-06"
+            },
+            "boundaries": [
+              {
+                "lord": "Rahu",
+                "start": "2023-02-25",
+                "end": "2025-11-07"
+              },
+              {
+                "lord": "Jupiter",
+                "start": "2025-11-07",
+                "end": "2028-04-01"
+              },
+              {
+                "lord": "Saturn",
+                "start": "2028-04-01",
+                "end": "2031-02-06"
+              },
+              {
+                "lord": "Mercury",
+                "start": "2031-02-06",
+                "end": "2033-08-25"
+              },
+              {
+                "lord": "Ketu",
+                "start": "2033-08-25",
+                "end": "2034-09-13"
+              },
+              {
+                "lord": "Venus",
+                "start": "2034-09-13",
+                "end": "2037-09-12"
+              },
+              {
+                "lord": "Sun",
+                "start": "2037-09-12",
+                "end": "2038-08-07"
+              },
+              {
+                "lord": "Moon",
+                "start": "2038-08-07",
+                "end": "2040-02-06"
+              },
+              {
+                "lord": "Mars",
+                "start": "2040-02-06",
+                "end": "2041-02-24"
+              }
+            ],
+            "boundary_count": 9,
+            "summary": "当前 Rahu 大运下的小运为 Jupiter，边界 2025-11-07 至 2028-04-01。更细的 Pratyantardasha 与行运触发不在本层计算范围内。"
+          },
+          "narayana_dasha": {
+            "current_dasha": {}
+          }
+        },
+        "domain": {
+          "vargas": {
+            "D12": {
+              "lagna": "Virgo",
+              "planets": {
+                "Sun": "Cancer",
+                "Moon": "Virgo",
+                "Mars": "Gemini",
+                "Mercury": "Libra",
+                "Jupiter": "Taurus",
+                "Venus": "Scorpio",
+                "Saturn": "Virgo",
+                "Rahu": "Aries",
+                "Ketu": "Libra"
+              },
+              "name": "Dwadasamsa",
+              "meaning": "父母"
+            }
+          },
+          "houses": {
+            "4": {
+              "sign": "Sagittarius",
+              "sign_idx": 8
+            },
+            "9": {
+              "sign": "Taurus",
+              "sign_idx": 1
+            }
+          },
+          "planets": {
+            "Sun": {
+              "degree": 13.9638,
+              "degree_in_sign": 13.9638,
+              "degree_raw": 313.96378728533347,
+              "house": 6,
+              "lon": 313.96378728533347,
+              "nakshatra": "Shatabhisha",
+              "retrograde": false,
+              "sign": "Aquarius",
+              "sign_idx": 10,
+              "status": "极敌(Great Enemy)"
+            },
+            "Moon": {
+              "degree": 15.9628,
+              "degree_in_sign": 15.9628,
+              "degree_raw": 345.9628222838024,
+              "house": 7,
+              "lon": 345.9628222838024,
+              "nakshatra": "Uttara Bhadrapada",
+              "retrograde": false,
+              "sign": "Pisces",
+              "sign_idx": 11,
+              "status": "入友(Friendly Sign)"
+            }
+          },
+          "arudha": {},
+          "karakas": {},
+          "yogas": null,
+          "transits": null,
+          "ashtakavarga": null,
+          "shadbala": null
+        },
+        "gaps": [],
+        "basis": [
+          "skills/jyotish-vedic-astrology/references/strict-workflow-router.md shared baseline: D12 for family/ancestral themes",
+          "references/birth-time-rectification-decision-tree.md section 4: 父母/家族 -> D12"
+        ]
+      }
+    },
+    {
+      "id": "steve_jobs__children",
+      "chart_id": "steve_jobs",
+      "chart_label": "Steve Jobs",
+      "question_id": "children",
+      "domain": "family",
+      "wall_seconds": 2.591,
+      "workflow_chars": 413267,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "steve_jobs__children",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 133292
+      },
+      "categories": {
+        "categories": {
+          "core": 42741,
+          "status": 11122,
+          "not_applicable": 2588,
+          "research": 43949,
+          "western": 32892
+        },
+        "total_chars": 133292,
+        "category_sum": 133292,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 133292,
+          "token_estimate": 38083,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65592,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3310,
+        "token_estimate": 946,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D7"
+          ],
+          "expected_vargas": [
+            "D7"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Pisces",
+            "actual": "Pisces"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 7,
+            "actual": 7
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Rahu",
+            "actual": "Rahu"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2023-02-25",
+            "actual": "2023-02-25"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2041-02-24",
+            "actual": "2041-02-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-11-07",
+            "actual": "2025-11-07"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2028-04-01",
+            "actual": "2028-04-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-07-20",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-11-21",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Leo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__career",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "career",
+      "domain": "career",
+      "wall_seconds": 2.813,
+      "workflow_chars": 412761,
+      "route": "career",
+      "focus_techniques": [
+        "D10",
+        "Dasha",
+        "Shadbala",
+        "Transit",
+        "Narayana Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__career",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 7313,
+        "model_chars": 142682
+      },
+      "categories": {
+        "categories": {
+          "core": 47688,
+          "status": 16044,
+          "not_applicable": 1972,
+          "research": 44050,
+          "western": 32928
+        },
+        "total_chars": 142682,
+        "category_sum": 142682,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 142682,
+          "token_estimate": 40766,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 67641,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3984,
+        "token_estimate": 1138,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D10"
+          ],
+          "expected_vargas": [
+            "D10"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Scorpio",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas",
+        "transits",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__marriage",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "marriage",
+      "domain": "marriage",
+      "wall_seconds": 2.603,
+      "workflow_chars": 406988,
+      "route": "marriage",
+      "focus_techniques": [
+        "D9",
+        "UL Upapada",
+        "Dasha",
+        "Nakshatra",
+        "Vivah Saham"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__marriage",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 9708,
+        "model_chars": 142541
+      },
+      "categories": {
+        "categories": {
+          "core": 45742,
+          "status": 17849,
+          "not_applicable": 1972,
+          "research": 44050,
+          "western": 32928
+        },
+        "total_chars": 142541,
+        "category_sum": 142541,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 142541,
+          "token_estimate": 40726,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66372,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3724,
+        "token_estimate": 1064,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D9"
+          ],
+          "expected_vargas": [
+            "D9"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Scorpio",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas",
+        "transits"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__wealth",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "wealth",
+      "domain": "wealth",
+      "wall_seconds": 2.623,
+      "workflow_chars": 411563,
+      "route": "wealth",
+      "focus_techniques": [
+        "D2",
+        "D11",
+        "Dasha",
+        "Shadbala",
+        "Ashtakavarga"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__wealth",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 6841,
+        "model_chars": 139490
+      },
+      "categories": {
+        "categories": {
+          "core": 44460,
+          "status": 15464,
+          "not_applicable": 2588,
+          "research": 44050,
+          "western": 32928
+        },
+        "total_chars": 139490,
+        "category_sum": 139490,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 139490,
+          "token_estimate": 39854,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66281,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3853,
+        "token_estimate": 1101,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D11",
+            "D2"
+          ],
+          "expected_vargas": [
+            "D2",
+            "D11"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Scorpio",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "ashtakavarga",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__health",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "health",
+      "domain": "health",
+      "wall_seconds": 2.636,
+      "workflow_chars": 432490,
+      "route": "health",
+      "focus_techniques": [
+        "D6",
+        "D8",
+        "D30",
+        "Dasha",
+        "Narayana Dasha",
+        "Shadbala",
+        "Transit",
+        "Functional Benefic/Malefic"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__health",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 2,
+        "methodology_chars": 3772,
+        "model_chars": 139179
+      },
+      "categories": {
+        "categories": {
+          "core": 45436,
+          "status": 14177,
+          "not_applicable": 2588,
+          "research": 44050,
+          "western": 32928
+        },
+        "total_chars": 139179,
+        "category_sum": 139179,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 139179,
+          "token_estimate": 39765,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 67660,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3852,
+        "token_estimate": 1101,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D30",
+            "D6",
+            "D8"
+          ],
+          "expected_vargas": [
+            "D6",
+            "D8",
+            "D30"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Scorpio",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "transits",
+        "shadbala"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__education",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "education",
+      "domain": "education",
+      "wall_seconds": 2.598,
+      "workflow_chars": 430364,
+      "route": "education",
+      "focus_techniques": [
+        "D5",
+        "D24",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__education",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2024,
+        "model_chars": 135570
+      },
+      "categories": {
+        "categories": {
+          "core": 43552,
+          "status": 12429,
+          "not_applicable": 2588,
+          "research": 44073,
+          "western": 32928
+        },
+        "total_chars": 135570,
+        "category_sum": 135570,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 135570,
+          "token_estimate": 38734,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66728,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3631,
+        "token_estimate": 1037,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D24",
+            "D5"
+          ],
+          "expected_vargas": [
+            "D5",
+            "D24"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Scorpio",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__migration",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "migration",
+      "domain": "migration",
+      "wall_seconds": 2.568,
+      "workflow_chars": 430449,
+      "route": "migration",
+      "focus_techniques": [
+        "D4",
+        "D12",
+        "12th house",
+        "Dasha",
+        "Narayana Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__migration",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2024,
+        "model_chars": 135650
+      },
+      "categories": {
+        "categories": {
+          "core": 43552,
+          "status": 12509,
+          "not_applicable": 2588,
+          "research": 44073,
+          "western": 32928
+        },
+        "total_chars": 135650,
+        "category_sum": 135650,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 135650,
+          "token_estimate": 38757,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66768,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3181,
+        "token_estimate": 909,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12",
+            "D4"
+          ],
+          "expected_vargas": [
+            "D4",
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__family",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "family",
+      "domain": "family",
+      "wall_seconds": 2.609,
+      "workflow_chars": 413849,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__family",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 133222
+      },
+      "categories": {
+        "categories": {
+          "core": 42543,
+          "status": 11090,
+          "not_applicable": 2588,
+          "research": 44073,
+          "western": 32928
+        },
+        "total_chars": 133222,
+        "category_sum": 133222,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 133222,
+          "token_estimate": 38063,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65557,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3214,
+        "token_estimate": 918,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12",
+            "D7"
+          ],
+          "expected_vargas": [
+            "D7",
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__general",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "general",
+      "domain": "general",
+      "wall_seconds": 2.572,
+      "workflow_chars": 430747,
+      "route": "general",
+      "focus_techniques": [
+        "D1",
+        "D9",
+        "Dasha",
+        "Yoga",
+        "Shadbala",
+        "Ashtakavarga"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__general",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2022,
+        "model_chars": 135548
+      },
+      "categories": {
+        "categories": {
+          "core": 43532,
+          "status": 12427,
+          "not_applicable": 2588,
+          "research": 44073,
+          "western": 32928
+        },
+        "total_chars": 135548,
+        "category_sum": 135548,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 135548,
+          "token_estimate": 38728,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66719,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 5863,
+        "token_estimate": 1675,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D10",
+            "D2",
+            "D9"
+          ],
+          "expected_vargas": [
+            "D9",
+            "D10",
+            "D2"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Scorpio",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "transits",
+        "ashtakavarga",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__parents",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "parents",
+      "domain": "family",
+      "wall_seconds": 2.58,
+      "workflow_chars": 413768,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__parents",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 133204
+      },
+      "categories": {
+        "categories": {
+          "core": 42525,
+          "status": 11090,
+          "not_applicable": 2588,
+          "research": 44073,
+          "western": 32928
+        },
+        "total_chars": 133204,
+        "category_sum": 133204,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 133204,
+          "token_estimate": 38058,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65548,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3554,
+        "token_estimate": 1015,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12"
+          ],
+          "expected_vargas": [
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Virgo",
+            "actual": "Virgo"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "barack_obama__children",
+      "chart_id": "barack_obama",
+      "chart_label": "Barack Obama",
+      "question_id": "children",
+      "domain": "family",
+      "wall_seconds": 2.586,
+      "workflow_chars": 413777,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "barack_obama__children",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 133206
+      },
+      "categories": {
+        "categories": {
+          "core": 42527,
+          "status": 11090,
+          "not_applicable": 2588,
+          "research": 44073,
+          "western": 32928
+        },
+        "total_chars": 133206,
+        "category_sum": 133206,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 133206,
+          "token_estimate": 38059,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65549,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3305,
+        "token_estimate": 944,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D7"
+          ],
+          "expected_vargas": [
+            "D7"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Capricorn",
+            "actual": "Capricorn"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Taurus",
+            "actual": "Taurus"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 5,
+            "actual": 5
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Saturn",
+            "actual": "Saturn"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2011-06-24",
+            "actual": "2011-06-24"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2030-06-24",
+            "actual": "2030-06-24"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2025-02-03",
+            "actual": "2025-02-03"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2027-12-11",
+            "actual": "2027-12-11"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-05-08",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-10-03",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Virgo",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Scorpio",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Virgo",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__career",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "career",
+      "domain": "career",
+      "wall_seconds": 3.421,
+      "workflow_chars": 409250,
+      "route": "career",
+      "focus_techniques": [
+        "D10",
+        "Dasha",
+        "Shadbala",
+        "Transit",
+        "Narayana Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__career",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 7313,
+        "model_chars": 142088
+      },
+      "categories": {
+        "categories": {
+          "core": 47550,
+          "status": 16060,
+          "not_applicable": 1972,
+          "research": 43662,
+          "western": 32844
+        },
+        "total_chars": 142088,
+        "category_sum": 142088,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 142088,
+          "token_estimate": 40597,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 67344,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3872,
+        "token_estimate": 1106,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D10"
+          ],
+          "expected_vargas": [
+            "D10"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas",
+        "transits",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__marriage",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "marriage",
+      "domain": "marriage",
+      "wall_seconds": 2.625,
+      "workflow_chars": 403759,
+      "route": "marriage",
+      "focus_techniques": [
+        "D9",
+        "UL Upapada",
+        "Dasha",
+        "Nakshatra",
+        "Vivah Saham"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__marriage",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 9708,
+        "model_chars": 142141
+      },
+      "categories": {
+        "categories": {
+          "core": 45808,
+          "status": 17855,
+          "not_applicable": 1972,
+          "research": 43662,
+          "western": 32844
+        },
+        "total_chars": 142141,
+        "category_sum": 142141,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 142141,
+          "token_estimate": 40612,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66172,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3702,
+        "token_estimate": 1058,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D9"
+          ],
+          "expected_vargas": [
+            "D9"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas",
+        "transits"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__wealth",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "wealth",
+      "domain": "wealth",
+      "wall_seconds": 2.613,
+      "workflow_chars": 408166,
+      "route": "wealth",
+      "focus_techniques": [
+        "D2",
+        "D11",
+        "Dasha",
+        "Shadbala",
+        "Ashtakavarga"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__wealth",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 3,
+        "methodology_chars": 6841,
+        "model_chars": 138988
+      },
+      "categories": {
+        "categories": {
+          "core": 44414,
+          "status": 15480,
+          "not_applicable": 2588,
+          "research": 43662,
+          "western": 32844
+        },
+        "total_chars": 138988,
+        "category_sum": 138988,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 138988,
+          "token_estimate": 39711,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66030,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3778,
+        "token_estimate": 1079,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D11",
+            "D2"
+          ],
+          "expected_vargas": [
+            "D2",
+            "D11"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "ashtakavarga",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__health",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "health",
+      "domain": "health",
+      "wall_seconds": 4.147,
+      "workflow_chars": 428729,
+      "route": "health",
+      "focus_techniques": [
+        "D6",
+        "D8",
+        "D30",
+        "Dasha",
+        "Narayana Dasha",
+        "Shadbala",
+        "Transit",
+        "Functional Benefic/Malefic"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__health",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 2,
+        "methodology_chars": 3772,
+        "model_chars": 138361
+      },
+      "categories": {
+        "categories": {
+          "core": 45056,
+          "status": 14211,
+          "not_applicable": 2588,
+          "research": 43662,
+          "western": 32844
+        },
+        "total_chars": 138361,
+        "category_sum": 138361,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 138361,
+          "token_estimate": 39532,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 67251,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3856,
+        "token_estimate": 1102,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D30",
+            "D6",
+            "D8"
+          ],
+          "expected_vargas": [
+            "D6",
+            "D8",
+            "D30"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "transits",
+        "shadbala"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__education",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "education",
+      "domain": "education",
+      "wall_seconds": 2.64,
+      "workflow_chars": 426624,
+      "route": "education",
+      "focus_techniques": [
+        "D5",
+        "D24",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__education",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2024,
+        "model_chars": 134798
+      },
+      "categories": {
+        "categories": {
+          "core": 43218,
+          "status": 12463,
+          "not_applicable": 2588,
+          "research": 43685,
+          "western": 32844
+        },
+        "total_chars": 134798,
+        "category_sum": 134798,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 134798,
+          "token_estimate": 38514,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66342,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3611,
+        "token_estimate": 1032,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D24",
+            "D5"
+          ],
+          "expected_vargas": [
+            "D5",
+            "D24"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__migration",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "migration",
+      "domain": "migration",
+      "wall_seconds": 2.601,
+      "workflow_chars": 426709,
+      "route": "migration",
+      "focus_techniques": [
+        "D4",
+        "D12",
+        "12th house",
+        "Dasha",
+        "Narayana Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__migration",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2024,
+        "model_chars": 134878
+      },
+      "categories": {
+        "categories": {
+          "core": 43218,
+          "status": 12543,
+          "not_applicable": 2588,
+          "research": 43685,
+          "western": 32844
+        },
+        "total_chars": 134878,
+        "category_sum": 134878,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 134878,
+          "token_estimate": 38537,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66382,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3159,
+        "token_estimate": 903,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12",
+            "D4"
+          ],
+          "expected_vargas": [
+            "D4",
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Cancer",
+            "actual": "Cancer"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Cancer",
+            "actual": "Cancer"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__family",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "family",
+      "domain": "family",
+      "wall_seconds": 2.638,
+      "workflow_chars": 410647,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__family",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 132800
+      },
+      "categories": {
+        "categories": {
+          "core": 42583,
+          "status": 11100,
+          "not_applicable": 2588,
+          "research": 43685,
+          "western": 32844
+        },
+        "total_chars": 132800,
+        "category_sum": 132800,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 132800,
+          "token_estimate": 37943,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65346,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3197,
+        "token_estimate": 913,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12",
+            "D7"
+          ],
+          "expected_vargas": [
+            "D7",
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Cancer",
+            "actual": "Cancer"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Cancer",
+            "actual": "Cancer"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__general",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "general",
+      "domain": "general",
+      "wall_seconds": 2.607,
+      "workflow_chars": 427007,
+      "route": "general",
+      "focus_techniques": [
+        "D1",
+        "D9",
+        "Dasha",
+        "Yoga",
+        "Shadbala",
+        "Ashtakavarga"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__general",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2022,
+        "model_chars": 134776
+      },
+      "categories": {
+        "categories": {
+          "core": 43198,
+          "status": 12461,
+          "not_applicable": 2588,
+          "research": 43685,
+          "western": 32844
+        },
+        "total_chars": 134776,
+        "category_sum": 134776,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 134776,
+          "token_estimate": 38507,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 66333,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 5650,
+        "token_estimate": 1614,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D10",
+            "D2",
+            "D9"
+          ],
+          "expected_vargas": [
+            "D9",
+            "D10",
+            "D2"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "transits",
+        "ashtakavarga",
+        "shadbala",
+        "yogas"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__parents",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "parents",
+      "domain": "family",
+      "wall_seconds": 2.609,
+      "workflow_chars": 410566,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__parents",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 132782
+      },
+      "categories": {
+        "categories": {
+          "core": 42565,
+          "status": 11100,
+          "not_applicable": 2588,
+          "research": 43685,
+          "western": 32844
+        },
+        "total_chars": 132782,
+        "category_sum": 132782,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 132782,
+          "token_estimate": 37938,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65337,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3548,
+        "token_estimate": 1014,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D12"
+          ],
+          "expected_vargas": [
+            "D12"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "match",
+            "expected": "Cancer",
+            "actual": "Cancer"
+          },
+          "d12_moon": {
+            "status": "match",
+            "expected": "Cancer",
+            "actual": "Cancer"
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only"
+      ],
+      "sample_card": null
+    },
+    {
+      "id": "elizabeth_taylor__children",
+      "chart_id": "elizabeth_taylor",
+      "chart_label": "Elizabeth Taylor",
+      "question_id": "children",
+      "domain": "family",
+      "wall_seconds": 2.599,
+      "workflow_chars": 410575,
+      "route": "family",
+      "focus_techniques": [
+        "D7",
+        "D12",
+        "4th house",
+        "5th house",
+        "9th house",
+        "Dasha"
+      ],
+      "success": true,
+      "projection": {
+        "id": "elizabeth_taylor__children",
+        "schema_ok": true,
+        "schema_error": null,
+        "methodology_sections": 1,
+        "methodology_chars": 2021,
+        "model_chars": 132784
+      },
+      "categories": {
+        "categories": {
+          "core": 42567,
+          "status": 11100,
+          "not_applicable": 2588,
+          "research": 43685,
+          "western": 32844
+        },
+        "total_chars": 132784,
+        "category_sum": 132784,
+        "sum_error_ratio": 0.0,
+        "tokens": {
+          "chars": 132784,
+          "token_estimate": 37938,
+          "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+        }
+      },
+      "duplicates": {
+        "consultation_copies": 2,
+        "spread_keys_matching_consultations_0": [
+          "domain",
+          "packet_version",
+          "question",
+          "route",
+          "status",
+          "evidence_contract",
+          "claim_cards",
+          "presentation",
+          "rectification"
+        ],
+        "consultations_chars": 65338,
+        "named_subtree_copies": {
+          "technique_audit_table": 4,
+          "varga_spectrum": 4,
+          "western_spectrum": 4,
+          "methodology": 1
+        }
+      },
+      "card_size": {
+        "chars": 3276,
+        "token_estimate": 936,
+        "token_method": "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected characters as about 40000 tokens (3.6 chars/token). This estimate uses 3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+      },
+      "card_gaps": [],
+      "part_b": {
+        "dual_dasha": true,
+        "domain_divisional": true,
+        "functional_benefic_malefic": true,
+        "raw_data": true,
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": [],
+        "present": {
+          "functional_benefic_malefic": true,
+          "vimshottari": true,
+          "narayana": true,
+          "ascendant_raw": true,
+          "domain_vargas": [
+            "D7"
+          ],
+          "expected_vargas": [
+            "D7"
+          ]
+        }
+      },
+      "verbatim": {
+        "ok": false,
+        "checks": {
+          "ascendant_sign": {
+            "status": "match",
+            "expected": "Scorpio",
+            "actual": "Scorpio"
+          },
+          "moon_sign": {
+            "status": "match",
+            "expected": "Libra",
+            "actual": "Libra"
+          },
+          "moon_house": {
+            "status": "match",
+            "expected": 12,
+            "actual": 12
+          },
+          "vimshottari_lord": {
+            "status": "match",
+            "expected": "Mars",
+            "actual": "Mars"
+          },
+          "vimshottari_start": {
+            "status": "match",
+            "expected": "2022-01-07",
+            "actual": "2022-01-07"
+          },
+          "vimshottari_end": {
+            "status": "match",
+            "expected": "2029-01-07",
+            "actual": "2029-01-07"
+          },
+          "antardasha_start": {
+            "status": "match",
+            "expected": "2026-07-05",
+            "actual": "2026-07-05"
+          },
+          "antardasha_end": {
+            "status": "match",
+            "expected": "2026-12-01",
+            "actual": "2026-12-01"
+          },
+          "pratyantar_start": {
+            "status": "mismatch",
+            "expected": "2026-09-05",
+            "actual": null
+          },
+          "pratyantar_end": {
+            "status": "mismatch",
+            "expected": "2026-09-27",
+            "actual": null
+          },
+          "narayana_sign": {
+            "status": "mismatch",
+            "expected": "Capricorn",
+            "actual": null
+          },
+          "d12_lagna": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          },
+          "d12_moon": {
+            "status": "not_on_card",
+            "expected": "Cancer",
+            "actual": null
+          }
+        },
+        "mismatched": [
+          "pratyantar_start",
+          "pratyantar_end",
+          "narayana_sign"
+        ]
+      },
+      "card_dependencies": [
+        "compute_chart",
+        "functional_benefic_malefic",
+        "dasha_sub_periods",
+        "narayana_dasha",
+        "varga_requested_only",
+        "arudha_padas",
+        "chara_karakas"
+      ],
+      "sample_card": null
+    }
+  ],
+  "layer_timings_seconds": {
+    "steve_jobs": {
+      "error": "NameError",
+      "message": "name 'swe' is not defined"
+    },
+    "barack_obama": {
+      "error": "NameError",
+      "message": "name 'swe' is not defined"
+    },
+    "elizabeth_taylor": {
+      "error": "NameError",
+      "message": "name 'swe' is not defined"
+    }
+  }
+}
\ No newline at end of file
diff --git a/docs/research/consult_evidence_card_research_2026_09_27.md b/docs/research/consult_evidence_card_research_2026_09_27.md
new file mode 100644
index 00000000..948ec27a
--- /dev/null
+++ b/docs/research/consult_evidence_card_research_2026_09_27.md
@@ -0,0 +1,189 @@
+# 普通对话数据卡调研（2026-09-27）
+
+写答案的模型现在每轮要读约 3.8–4.1 万 token，其中能写进一张领域数据卡的大约 900–1700 token，约 2.3%–4.3%。建议立实现单，但先拍板下面 7 项。本单没有改线上行为，也没有下占星结论。
+
+基准是 `origin/staging` `76924e33`。三张公开 AA 盘：Steve Jobs、Barack Obama、Elizabeth Taylor。参考日钉在 `2026-09-27`，岁差 `raman`，交点 `mean`。外部 VedAstro 没有调用。
+
+## 要拍板的 7 项
+
+1. **按草案把写答案的上下文收成数据卡。** 推荐：收。父母问法现在给模型 133290 字符（约 38083 token），草案卡 3548–3576 字符（约 1014–1022 token）。
+2. **「家庭」拆成「父母」和「子女」。** 推荐：拆。两种问法现在都进 `family`，焦点技法都是 D7、D12、4/5/9 宫。仓库里 Skill 和校时决策树已经把子女写成 D7、父母/家族写成 D12。
+3. **状态说明、研究分盘、西洋层留在后台。** 推荐：留在后台。审计回执继续用，不进写答案的上下文。
+4. **Part B 与「只给相关数据」的冲突。** 高严谨解读要求 MEVG 和真实案例校准。这两项现在是「没做」的状态说明。推荐：回答模型不读长状态，回执保留一行「未做，置信度封顶」。这一项必须由产品定，本单不取舍。
+5. **先补投影缺口再上卡。** 推荐：先补。引擎算出了当前 Narayana 星座和子运起止，投影给模型时被裁空（BUG-1054，investigating，未修）。卡只复制投影，所以这两项现在进不了卡。
+6. **先不要为了提速少算。** 推荐：计算先照旧。本机不调 VedAstro 时，一轮约 2.6 秒，其中校正门约 2.5 秒；40 张研究分盘合计不到 0.01 秒。线上曾经约 31 秒/领域，那次含外部取证，本单没有重测。
+7. **埋点只存领域、卡版本、大小、被引用字段名、赞或踩。** 推荐：按这个做。不存问题、回答、出生资料。
+
+## R1 模型现在看到什么
+
+结论：投影后约 13.3–14.4 万字符，按诊断同一比例估成约 3.8–4.1 万 token。五类加总与总字符数一致（误差 0）。同一份包在 `consultations` 里再放一遍，约占一半。
+
+复跑：
+
+```text
+$env:PYTHONHASHSEED = "0"
+python scripts/research/consult_evidence_card_run.py
+```
+
+token 估算是字符数 / 3.5。2026-09-27 诊断把约 144000 字符看成约 40000 token。这不是供应商分词器。
+
+父母问法、Jobs 盘，模型可见文本 133290 字符：
+
+| 类别 | 字符 | 占总量 |
+| --- | ---: | ---: |
+| 核心数据 | 42739 | 32.1% |
+| 研究用 | 43949 | 33.0% |
+| 西洋 | 32892 | 24.7% |
+| 状态说明 | 11122 | 8.3% |
+| 本轮不适用 | 2588 | 1.9% |
+| 合计 | 133290 | 100% |
+
+十种问法的模型可见文本在 132782–143603 字符之间。事业、婚恋带方法学长文，所以更大。30 次的类别合计都与各自总量一致。
+
+重复：`consultations[0]` 与摊开的同一批键逐字相同。Jobs 父母问法里这段 65591 字符，占 49.2%。`varga_spectrum`、`western_spectrum`、`technique_audit_table` 各出现 4 次：本命卡或时间卡一份，证据合同再一份，然后整包再复制进 `consultations`。方法学只出现 1 次。
+
+43 行技法审计表（同一套分类规则）：核心 15、西洋 12、状态 8、不适用 5、研究 3。规则写在 `scripts/research/consult_evidence_card_lib.py` 的技法名表里。
+
+原始工作流 JSON 是 394333–423130 字符（30 个缓存文件的字符数，均值 409085）。诊断里的约 478K 含外部取证原文；本单按任务要求没有调 VedAstro，所以原始包更小。库存 JSON 里的 `workflow_chars` 是文件字节数，不是字符数。
+
+建议立实现单：是，但实现的是筛选，不是先改计算。
+
+## R2 领域和技法对不上
+
+结论：同一领域在注册表、方法学、前端必用层、Python 焦点技法四处不一致。父母和子女没有独立领域，两种问法都走 `family`。
+
+复跑：草案 JSON 由下面的库函数生成，已写入 `docs/research/consult_evidence_card_draft_2026_09_27.json`。
+
+```text
+python -c "import json,sys; from pathlib import Path; sys.path[:0]=['scripts','scripts/research']; from consult_evidence_card_lib import CARD_SPECS, TELEMETRY_SPEC, source_matrix; json.dump({'cards':CARD_SPECS,'source_matrix':source_matrix(Path('.')),'telemetry':TELEMETRY_SPEC}, open('docs/research/consult_evidence_card_draft_2026_09_27.json','w',encoding='utf-8'), ensure_ascii=False, indent=2)"
+```
+
+| 领域 | 注册表要的层 | 方法学路线 | 前端必用层 | Python 焦点 | 草案分盘 |
+| --- | --- | --- | --- | --- | --- |
+| 事业 | D1 D10 10宫 A10 AmK 大运 Narayana 过境 | career-timing-strict | 正式分盘、A10、Narayana、Chara | D10 大运 Shadbala 过境 Narayana | D10 |
+| 婚恋 | D1 D9 7宫 金木 DK UL A7 大运 Narayana 过境 | relationship-timing-strict | 正式分盘、Arudha | D9 UL 大运 星宿 婚姻份 | D9 |
+| 财富 | D1 D2 D11 2/11/9/5 财富格局 Ashtakavarga 大运 | finance-timing-strict | 正式分盘、Ashtakavarga | D2 D11 大运 Shadbala Ashtakavarga | D2 D11 |
+| 健康 | D1 D6 D8 6/8宫 大运 非医疗边界 | health-timing-strict | 正式分盘、Shadbala | D6 D8 D30 大运 Narayana Shadbala 过境 功能吉凶 | D6 D8 D30 |
+| 学习 | D1 D24 5/9宫 水木 大运 | 无 | 无 | D5 D24 5宫 9宫 大运 | D5 D24 |
+| 迁居 | D1 D4 D12 4/12宫 大运 Narayana | 无 | 无 | D4 D12 12宫 大运 Narayana | D4 D12 |
+| 家庭 | D1 D7 D12 4/5/9宫 大运 | 无 | 无 | D7 D12 4宫 5宫 9宫 大运 | D7 D12 |
+| 综合 | D1 D9 D10 D2 大运 Narayana 过境 功能吉凶 | 无 | 无 | D1 D9 大运 格局 Shadbala Ashtakavarga | D9 D10 D2 |
+| 父母 | 无此领域 | 无 | 无 | 无；问法仍进 family | D12、4宫、9宫 |
+| 子女 | 无此领域 | 无 | 无 | 无；问法仍进 family | D7、5宫 |
+
+每张卡的基础段都带：上升、十二宫星座、行星落宫、功能吉凶（含宫主归属）、当前 Vimshottari 大运与子运起止、Narayana 对象。领域段只带上表分盘和该领域的宫、行星、过境或力量层。值从投影里原样复制，不改写。
+
+父母、子女的依据：
+
+- Skill `references/strict-workflow-router.md` 共用基线：子女用 D7，父母/家族主题用 D12。
+- `references/birth-time-rectification-decision-tree.md` 第 4 节：子女/生育 → D7；父母/家族 → D12。
+
+Part B 覆盖：双轨大运、领域分盘、功能吉凶、上升与大运日期，在投影还留着的字段上是齐的。MEVG 和真实案例校准按草案留在后台，见拍板第 4 项。Narayana 当前星座和子运日期被投影裁掉，见拍板第 5 项。
+
+建议立实现单：是。先让产品和懂印占的人确认这张表，尤其是健康域 Python 有 D30、注册表没有，学习域 Python 有 D5、注册表没有。
+
+## R3 数据卡有多小，事实有没有被改
+
+结论：十张草案卡是现状的 2.3%–4.3%。验收点名的事实与引擎逐字一致。卡没有改值。投影丢掉的两项记成缺陷，没有用引擎原文填回去。
+
+复跑：同一条 R1 命令。比对在 `scripts/research/consult_evidence_card_lib.py` 的 `verbatim_check`。
+
+三盘均值：
+
+| 问法 | 现状字符 | 现状 token 估计 | 卡字符 | 卡 token 估计 | 卡 / 现状 |
+| --- | ---: | ---: | ---: | ---: | ---: |
+| 事业 | 142483 | 40710 | 3942 | 1126 | 2.77% |
+| 婚恋 | 142762 | 40789 | 3753 | 1072 | 2.63% |
+| 财富 | 139328 | 39808 | 3799 | 1085 | 2.73% |
+| 健康 | 138812 | 39660 | 3894 | 1113 | 2.81% |
+| 学习 | 135225 | 38636 | 3626 | 1036 | 2.68% |
+| 迁居 | 135305 | 38659 | 3169 | 906 | 2.34% |
+| 家庭 | 133110 | 38031 | 3213 | 918 | 2.41% |
+| 综合 | 135203 | 38629 | 5750 | 1643 | 4.25% |
+| 父母 | 133092 | 38026 | 3559 | 1017 | 2.67% |
+| 子女 | 133094 | 38027 | 3297 | 942 | 2.48% |
+
+逐字核对，30 次里凡是卡上有的都一致：上升星座、月亮星座、月亮宫位、当前大运起止、子运起止。带 D12 的 9 次（父母、家庭、迁居 × 3 盘）D12 上升和月亮落点也一致。不带 D12 的卡不拿 D12 做失败。
+
+不一致、且没有改卡：30/30 的子运起止和 Narayana 当前星座。引擎有值，投影是空，卡跟着空。BUG-1054。
+
+建议立实现单：是。实现时卡仍然只复制投影，先把 BUG-1054 的两段放进投影。
+
+## R4 少算省不了这轮等待
+
+结论：本机不调 VedAstro 时，少算研究分盘和西洋层省不到 0.05 秒。等待几乎全在校正门。外部取证没有计时，也不计入。
+
+复跑：
+
+```text
+$env:PYTHONHASHSEED = "0"
+python scripts/research/consult_evidence_card_time.py
+```
+
+数字在 `docs/research/consult_evidence_card_timings_2026_09_27.json`。包一层计时的一轮（事业问法）：
+
+| 模块 | Jobs | Obama | Taylor |
+| --- | ---: | ---: | ---: |
+| 整轮 | 4.81 秒 | 2.58 秒 | 2.59 秒 |
+| 校正门 | 3.97 秒 | 2.47 秒 | 2.48 秒 |
+| 本命计算 | 0.002 秒 | 0.002 秒 | 0.002 秒 |
+| 本地附加层（含分盘） | 0.035 秒 | 0.031 秒 | 0.020 秒 |
+| 其中正式分盘 | 0.002 秒 | 0.001 秒 | 0.001 秒 |
+| 40 张研究分盘合计 | 0.000 秒 | 0.000 秒 | 0.0002 秒 |
+| 主题报告 | 0.072 秒 | 0.008 秒 | 0.009 秒 |
+
+30 次库存跑的墙钟是 2.568–5.539 秒，去掉第一次冷启动后均值 2.692 秒。
+
+卡依赖的计算是本命盘、功能吉凶、大运子运、Narayana，加上该领域 1–3 张分盘。这些层加起来远小于校正门。研究分盘 40 次调用都发生了，时间可以忽略。所以「只算卡里要的」相对「全算」的节省，在本机是毫秒级。
+
+校正门不是数据卡的内容。要不要缩短它，是另一张单，不是这张卡的筛选。
+
+线上约 31 秒/领域来自 BUG-1051 的观察，路径里含外部取证。本单按任务没有重跑 VedAstro，不把 31 秒写成本机结果。
+
+建议立实现单：筛选可以立。少算先不立，除非产品要单独处理校正门或外部取证等待。
+
+## R5 反馈只记字段名
+
+结论：每轮可以记 6 个字段，用来以后删卡上没人用的项。不存用户句子。
+
+| 字段 | 内容 |
+| --- | --- |
+| domain | 十个问法枚举 |
+| card_version | `evidence-card-draft-20260927` |
+| card_chars | 整数 |
+| card_token_estimate | 整数 |
+| cited_field_ids | 卡方案里的字段名 |
+| feedback | up / down / none |
+
+怎样算「引用了」：字段值是 ISO 日期、度数，或至少 8 个字符的「行星在星座」短语，并且原样出现在回答里，才算引用。裸的行星名、星座名不算。误报：问题和回答里碰巧有同一个日期。漏报：模型改写了时期、没抄日期。落库只留字段名，匹配到的原文丢掉。
+
+后台汇总：按领域和卡版本数回答数；某领域满 30 条后，引用率仍低于 5% 的字段；按领域和卡版本的点踩率。没有用户句、没有出生资料、没有会话 id。
+
+建议立实现单：方案可以并进数据卡实现单，不必单独先做。
+
+## 复跑与测试
+
+```text
+$env:PYTHONHASHSEED = "0"
+python scripts/research/consult_evidence_card_run.py
+python scripts/research/consult_evidence_card_time.py
+python -m pytest tests/test_consult_evidence_card_research.py
+```
+
+Windows 上 `skills/jyotish-vedic-astrology/references` 若不是目录，投影读不到方法学。本机把仓库根的 `references`、`scripts`、`assets` 接成 junction，并把 `SKILL.md` 复制进技能目录后再投影。这些链接没有提交。
+
+## 附录：父母卡样例
+
+公开盘 Steve Jobs，问法「我和父母关系如何」，参考日 2026-09-27。完整卡片在 `docs/research/consult_evidence_card_sample_parents_2026_09_27.json`。下面是核对过的事实，不是解读。
+
+| 项 | 卡里的值 | 与引擎 |
+| --- | --- | --- |
+| 上升 | Virgo 0.51° | 一致 |
+| 月亮 | Pisces，7 宫 | 一致 |
+| 大运 | Rahu，2023-02-25 至 2041-02-24 | 一致 |
+| 子运 | Jupiter，2025-11-07 至 2028-04-01 | 一致 |
+| D12 | 上升 Virgo，月亮 Virgo | 一致 |
+| 功能吉星 | Mercury、Saturn、Venus | 来自投影，未改 |
+| 4 宫 / 9 宫 | Sagittarius / Taurus | 来自投影，未改 |
+| Narayana 当前段 | 投影后是空对象 | 引擎有值，BUG-1054 |
+| 子运 PD | 不在投影里 | 引擎有值，BUG-1054 |
diff --git a/docs/research/consult_evidence_card_sample_parents_2026_09_27.json b/docs/research/consult_evidence_card_sample_parents_2026_09_27.json
new file mode 100644
index 00000000..c306a99c
--- /dev/null
+++ b/docs/research/consult_evidence_card_sample_parents_2026_09_27.json
@@ -0,0 +1,294 @@
+{
+  "card_id": "parents",
+  "label": "父母",
+  "question": "我和父母关系如何",
+  "route": "family",
+  "base": {
+    "ascendant": {
+      "degree": 0.51,
+      "degree_in_sign": 0.51,
+      "lon": 150.5069,
+      "sign": "Virgo",
+      "sign_idx": 5
+    },
+    "houses": {
+      "1": {
+        "sign": "Virgo",
+        "sign_idx": 5
+      },
+      "2": {
+        "sign": "Libra",
+        "sign_idx": 6
+      },
+      "3": {
+        "sign": "Scorpio",
+        "sign_idx": 7
+      },
+      "4": {
+        "sign": "Sagittarius",
+        "sign_idx": 8
+      },
+      "5": {
+        "sign": "Capricorn",
+        "sign_idx": 9
+      },
+      "6": {
+        "sign": "Aquarius",
+        "sign_idx": 10
+      },
+      "7": {
+        "sign": "Pisces",
+        "sign_idx": 11
+      },
+      "8": {
+        "sign": "Aries",
+        "sign_idx": 0
+      },
+      "9": {
+        "sign": "Taurus",
+        "sign_idx": 1
+      },
+      "10": {
+        "sign": "Gemini",
+        "sign_idx": 2
+      },
+      "11": {
+        "sign": "Cancer",
+        "sign_idx": 3
+      },
+      "12": {
+        "sign": "Leo",
+        "sign_idx": 4
+      }
+    },
+    "planet_placements": {
+      "Jupiter": {
+        "sign": "Gemini",
+        "house": 10
+      },
+      "Ketu": {
+        "sign": "Gemini",
+        "house": 10
+      },
+      "Mars": {
+        "sign": "Aries",
+        "house": 8
+      },
+      "Mercury": {
+        "sign": "Capricorn",
+        "house": 5
+      },
+      "Moon": {
+        "sign": "Pisces",
+        "house": 7
+      },
+      "Rahu": {
+        "sign": "Sagittarius",
+        "house": 4
+      },
+      "Saturn": {
+        "sign": "Libra",
+        "house": 2
+      },
+      "Sun": {
+        "sign": "Aquarius",
+        "house": 6
+      },
+      "Venus": {
+        "sign": "Sagittarius",
+        "house": 4
+      }
+    },
+    "functional_benefic_malefic": {
+      "status": "used",
+      "ascendant": "Virgo",
+      "functional_benefics": [
+        "Mercury",
+        "Saturn",
+        "Venus"
+      ],
+      "functional_malefics": [
+        "Mars",
+        "Moon",
+        "Sun"
+      ],
+      "functional_neutrals": [
+        "Jupiter"
+      ],
+      "yogakarakas": [
+        "Mercury"
+      ],
+      "owned_houses": {
+        "Jupiter": [
+          4,
+          7
+        ],
+        "Mars": [
+          3,
+          8
+        ],
+        "Mercury": [
+          1,
+          10
+        ],
+        "Moon": [
+          11
+        ],
+        "Saturn": [
+          5,
+          6
+        ],
+        "Sun": [
+          12
+        ],
+        "Venus": [
+          2,
+          9
+        ]
+      },
+      "effect_on_confidence": "高严谨模式下必须叠加功能性宫主吉凶与自然吉凶；若功能属性与自然属性冲突，应降低置信度或显式标记冲突。",
+      "source": "strict_functional_benefic_malefic_v1"
+    },
+    "vimshottari": {
+      "status": "ready",
+      "source": "chart.dasha.periods + dasha_analyzer.build_antardasha",
+      "method": "vimshottari_antardasha_proportional",
+      "current": {
+        "mahadasha": {
+          "lord": "Rahu",
+          "start": "2023-02-25",
+          "end": "2041-02-24"
+        },
+        "antardasha": {
+          "lord": "Jupiter",
+          "start": "2025-11-07",
+          "end": "2028-04-01"
+        }
+      },
+      "next": {
+        "lord": "Saturn",
+        "start": "2028-04-01",
+        "end": "2031-02-06"
+      },
+      "boundaries": [
+        {
+          "lord": "Rahu",
+          "start": "2023-02-25",
+          "end": "2025-11-07"
+        },
+        {
+          "lord": "Jupiter",
+          "start": "2025-11-07",
+          "end": "2028-04-01"
+        },
+        {
+          "lord": "Saturn",
+          "start": "2028-04-01",
+          "end": "2031-02-06"
+        },
+        {
+          "lord": "Mercury",
+          "start": "2031-02-06",
+          "end": "2033-08-25"
+        },
+        {
+          "lord": "Ketu",
+          "start": "2033-08-25",
+          "end": "2034-09-13"
+        },
+        {
+          "lord": "Venus",
+          "start": "2034-09-13",
+          "end": "2037-09-12"
+        },
+        {
+          "lord": "Sun",
+          "start": "2037-09-12",
+          "end": "2038-08-07"
+        },
+        {
+          "lord": "Moon",
+          "start": "2038-08-07",
+          "end": "2040-02-06"
+        },
+        {
+          "lord": "Mars",
+          "start": "2040-02-06",
+          "end": "2041-02-24"
+        }
+      ],
+      "boundary_count": 9,
+      "summary": "当前 Rahu 大运下的小运为 Jupiter，边界 2025-11-07 至 2028-04-01。更细的 Pratyantardasha 与行运触发不在本层计算范围内。"
+    },
+    "narayana_dasha": {
+      "current_dasha": {}
+    }
+  },
+  "domain": {
+    "vargas": {
+      "D12": {
+        "lagna": "Virgo",
+        "planets": {
+          "Sun": "Cancer",
+          "Moon": "Virgo",
+          "Mars": "Gemini",
+          "Mercury": "Libra",
+          "Jupiter": "Taurus",
+          "Venus": "Scorpio",
+          "Saturn": "Virgo",
+          "Rahu": "Aries",
+          "Ketu": "Libra"
+        },
+        "name": "Dwadasamsa",
+        "meaning": "父母"
+      }
+    },
+    "houses": {
+      "4": {
+        "sign": "Sagittarius",
+        "sign_idx": 8
+      },
+      "9": {
+        "sign": "Taurus",
+        "sign_idx": 1
+      }
+    },
+    "planets": {
+      "Sun": {
+        "degree": 13.9638,
+        "degree_in_sign": 13.9638,
+        "degree_raw": 313.96378728533347,
+        "house": 6,
+        "lon": 313.96378728533347,
+        "nakshatra": "Shatabhisha",
+        "retrograde": false,
+        "sign": "Aquarius",
+        "sign_idx": 10,
+        "status": "极敌(Great Enemy)"
+      },
+      "Moon": {
+        "degree": 15.9628,
+        "degree_in_sign": 15.9628,
+        "degree_raw": 345.9628222838024,
+        "house": 7,
+        "lon": 345.9628222838024,
+        "nakshatra": "Uttara Bhadrapada",
+        "retrograde": false,
+        "sign": "Pisces",
+        "sign_idx": 11,
+        "status": "入友(Friendly Sign)"
+      }
+    },
+    "arudha": {},
+    "karakas": {},
+    "yogas": null,
+    "transits": null,
+    "ashtakavarga": null,
+    "shadbala": null
+  },
+  "gaps": [],
+  "basis": [
+    "skills/jyotish-vedic-astrology/references/strict-workflow-router.md shared baseline: D12 for family/ancestral themes",
+    "references/birth-time-rectification-decision-tree.md section 4: 父母/家族 -> D12"
+  ]
+}
\ No newline at end of file
diff --git a/docs/research/consult_evidence_card_timings_2026_09_27.json b/docs/research/consult_evidence_card_timings_2026_09_27.json
new file mode 100644
index 00000000..ad26e303
--- /dev/null
+++ b/docs/research/consult_evidence_card_timings_2026_09_27.json
@@ -0,0 +1,35 @@
+{
+  "steve_jobs": {
+    "compute_chart": 0.0024,
+    "rectification_gate": 3.9655,
+    "varga_full": 0.0017,
+    "research_dn_loop": 0.0,
+    "varga_spectrum": 0.0031,
+    "attach_local_layers": 0.0352,
+    "thematic_report": 0.072,
+    "workflow_wall": 4.8122,
+    "research_dn_calls": 40
+  },
+  "barack_obama": {
+    "compute_chart": 0.0023,
+    "rectification_gate": 2.4683,
+    "varga_full": 0.0006,
+    "research_dn_loop": 0.0,
+    "varga_spectrum": 0.0019,
+    "attach_local_layers": 0.0309,
+    "thematic_report": 0.0082,
+    "workflow_wall": 2.5763,
+    "research_dn_calls": 40
+  },
+  "elizabeth_taylor": {
+    "compute_chart": 0.0024,
+    "rectification_gate": 2.4828,
+    "varga_full": 0.0005,
+    "research_dn_loop": 0.0002,
+    "varga_spectrum": 0.0019,
+    "attach_local_layers": 0.0204,
+    "thematic_report": 0.0088,
+    "workflow_wall": 2.5871,
+    "research_dn_calls": 40
+  }
+}
\ No newline at end of file
diff --git a/docs/tasks/PROGRESS-consult-evidence-card-research-20260927.md b/docs/tasks/PROGRESS-consult-evidence-card-research-20260927.md
new file mode 100644
index 00000000..3159809e
--- /dev/null
+++ b/docs/tasks/PROGRESS-consult-evidence-card-research-20260927.md
@@ -0,0 +1,30 @@
+# PROGRESS · 普通对话数据卡调研（2026-09-27）
+
+## 开工基线
+
+- 计量时 `origin/staging` 是 `76924e3362c0a47d9d8de896c448c66055826f70`（任务书自己的文档提交）。任务书里写的 `5f2e007f` 已被那次推送盖过。
+- 推送前 staging 又到了 `3b67d8e9`（BUG-1052、BUG-1053）。本地提交已接到这个 tip 上再快进。计量数字仍是 `76924e33` 上的引擎与投影；`toModelOutput` 的裁剪规则没有被这两单改动。
+- 工作树 `.worktrees/consult-evidence-card-research-20260927`，分支 `codex/consult-evidence-card-research-20260927`。
+- 主检出仍在 `staging`，没有在主检出上提交或切分支。
+- `PYTHONHASHSEED=0`。Python `C:\Users\74082\anaconda3\python.exe` 3.11.7。Node v22.23.2。
+
+## 做了什么
+
+- 3 张公开 AA 盘 × 10 种问法，调用 `JyotishAPIHandler._compute_consultation_workflow`，再用现有的 `toAgentConsultationContext` / `toModelOutput`，并按 `toModelDomainPlanContext` 的单领域分支包成模型可见文本。
+- 五类分区与总字符数一致。草案卡只复制投影。验收点名的事实与引擎逐字一致。
+- 投影丢掉当前 Narayana 段和子运日期，记为 BUG-1054，状态 `investigating`，没有改投影代码。
+- 本机计了本地层。外部 VedAstro 没有调用，也不计入耗时。
+- 报告：`docs/research/consult_evidence_card_research_2026_09_27.md`。
+
+## 没做什么
+
+- 没有改 `frontend/src/**`、`scripts/*.py`（`scripts/research/` 除外）、Skill 文本、数据库。
+- 没有推送，没有部署。
+- 没有下占星结论。
+- 没有重测线上约 31 秒/领域的外部取证等待。
+
+## 环境缺口
+
+- 预检 `scripts/pre_work_check.py` 退出 1。Python、远端、外部适配器正常。两条碎片扫描测试失败：这台机器没有 `.workbuddy/skills/jyotish-vedic-astrology`，工作树残留计数 3638。不挡住本单。没有往错误台账追加，因为这是本机工作树布局，不是新的引擎故障。
+- Windows 把 `skills/jyotish-vedic-astrology` 下的符号链接检出成小文本文件。投影前在工作树里接了 junction，并复制了 `SKILL.md`。这些改动不提交。
+- 无浏览器验收：本单不改界面。
diff --git a/docs/tasks/README.md b/docs/tasks/README.md
index b20fb49f..c8ce6b70 100644
--- a/docs/tasks/README.md
+++ b/docs/tasks/README.md
@@ -128,7 +128,7 @@
 | --- | --- | --- | --- | --- |
 | — （产品 09-27 拍板 D1–D4，直接执行） | [PROGRESS](PROGRESS-home-landing-blank-20260927.md) | **登录后 / 裸 `/` 落空白首页**：真机登录后在「首页」提问其实问进了上一次生时校正。删登录返回存根（401 / 次级页链接写、登录后写回 `?c=` 打开），裸 `/` 不再落最近会话，一律当前人物的空白首页（复用空草稿）；`?c=` / `?new=1` / 对话内刷新不变；推翻 BUG-1038 存根与 BUG-599 默认落点 | 已验收（真机欠） | `codex/home-landing-blank-20260927`（BUG-1052，本地未推） |
 | — （产品 09-26 口头拍板 D1–D3，直接执行） | `PROGRESS-consult-answer-truncation-20260926.md` | **普通咨询回答写到一半被掐断仍扣点（BUG-1051，复发自 BUG-305）**：工具循环与写回答共用 110 秒 signal；Mastra 1.50 超时不抛错（`abort` 块 + `finish(tripwire)` 后正常关流），结算只认抛错与 `length`。D1 写回答自有 70 秒时钟（首用起算，续写 / 回答重试共用，最坏 180 秒，`maxDuration` 240）；D2 写回答的最后一个流不是 `stop` 且有正文 → `answer_truncated`、不扣点、记 abort 步、不冲半句，`length` 续写不变；D3 观测加 `composeFinishReason` / `composeAborted` / `answerVisibleChars` | 已验收（真机欠） | `codex/consult-answer-truncation-20260926`（本地，未推送）；新回归 15 条用真实 Mastra `Agent`（修复前 11 条红）；全量失败名单 0 新增；Python 948/1；`/` ○、gzip 0%；真机清单 `docs/testing/consult-answer-truncation-20260926.md` |
-| `TASK-consult-evidence-card-research-20260927.md` | `PROGRESS-consult-evidence-card-research-20260927.md` | **普通对话数据卡调研**：引擎输出逐项分五类计量（现约 4 万 token、父母问题相关约 3.5%）；四处领域→技法来源对账并起草各领域数据卡（家庭拆父母/子女）；卡体量与逐字一致性；按卡算的提速空间；反馈迭代埋点方案。只调研不改线上 | 待领取 | 分支 `codex/consult-evidence-card-research-20260927`；与 BUG-1053 实现单并行，不碰 consult route / stream-agent-response |
+| `TASK-consult-evidence-card-research-20260927.md` | `PROGRESS-consult-evidence-card-research-20260927.md` | **普通对话数据卡调研**：引擎输出逐项分五类计量（现约 4 万 token、父母问题相关约 3.5%）；四处领域→技法来源对账并起草各领域数据卡（家庭拆父母/子女）；卡体量与逐字一致性；按卡算的提速空间；反馈迭代埋点方案。只调研不改线上 | 待验收 | `codex/consult-evidence-card-research-20260927` 快进 staging；报告 `docs/research/consult_evidence_card_research_2026_09_27.md`；投影缺口记 BUG-1054 investigating |
 | — （产品 09-27 拍板 D1–D3，直接执行） | `PROGRESS-consult-single-pass-answer-20260927.md` | **普通咨询回答没看过星盘（BUG-1053，引入 `04463e9a`，生产不受影响）**：本命主循环工具结果后那一步看得到证据、正文却被丢弃，用户看到的是另开的 compose 流（只有历史 + 问题、判断依据恒空）写的。D1 删 compose / interpret / drain，主循环最后一步的正文即回答（按步取答，调用工具的那一步正文整段丢）；写作要求搬进用户轮；续写带计算结果；工具 110 秒不变，拿到计算结果后循环交给 70 秒答案钟，最坏 180 秒；BUG-1051 结算规则保留（按写回答那一步判定）。D2 观测字段名不变、含义改为写回答那一步 | 已验收（真机欠） | `codex/consult-single-pass-answer-20260927`（本地，未推送）；新回归 15 条用真实 `getJyotishAgent` + 记录提示词的假模型 + golden 计算数据；全量失败名单 0 新增；Python 948/1；`/` ○、gzip +0.24%；真机清单 `docs/testing/consult-single-pass-answer-20260927.md` |
 | `TASK-scroll-anchor-hook-fixes-20260926.md` | `PROGRESS-scroll-anchor-hook-fixes-20260926.md` | **滚动锚两处老问题**：直接打开已有会话时监听未挂上（BUG-1043）、校正长回答钉顶后因 96px 阈值被拉到底（BUG-1044）。排在 BUG-1042 合入后。挂载改由容器元素本身驱动（每次提交比对元素 / active / resetKey）；钉顶只由用户滚动手势解除 | 已验收（Claude 09-26 直接执行：子代理复现两处根因并修复；Claude 独立复验 tsc/lint 0、全量 3970 条失败名单与基线逐条一致、四路由 ○、gzip 不变；iOS 惯性滚动留真机清单） | `da2613ff`（随 `f1d16405` 部署，health 一致） |
 | `TASK-latest-turn-actions-gap-20260926.md` | — | **最后一轮正文与点赞 / 踩之间空大半屏**：BUG-930 钉顶留白（`min-height: 视口 − 本轮开头`）加在 `.message-assistant` 上，把兄弟节点 `.message-actions` 推到留白之后；改为加在整轮外层，按钮紧贴正文、空白落在后面；不动滚动 hook | 已验收（Claude 09-26 直接执行：子代理实现，Claude 独立复验 tsc/lint 0、全量 3961 条失败名单与基线逐条一致、四路由 ○、gzip 不变；CDP 实测间距 450–600px → 23px，钉顶仍在） | `080ea5ca`（已部署 `509987b9`，health 一致） |
diff --git a/scripts/research/consult_evidence_card_lib.py b/scripts/research/consult_evidence_card_lib.py
new file mode 100644
index 00000000..59caa1ad
--- /dev/null
+++ b/scripts/research/consult_evidence_card_lib.py
@@ -0,0 +1,811 @@
+"""Pure helpers for the consultation evidence-card research.
+
+No network, no engine mutation. Classification partitions a JSON value so the
+five category sizes sum to the canonical serialization length.
+"""
+
+from __future__ import annotations
+
+import json
+import re
+from collections import Counter
+from pathlib import Path
+from typing import Any
+
+CATEGORIES = ("core", "status", "not_applicable", "research", "western")
+
+TOKEN_CHARS_PER_TOKEN = 3.5
+TOKEN_METHOD = (
+    "chars/3.5. The 2026-09-27 diagnosis measured about 144000 projected "
+    "characters as about 40000 tokens (3.6 chars/token). This estimate uses "
+    "3.5 so the research tables stay comparable. It is not a vendor tokenizer."
+)
+
+REFERENCE_DATE = "2026-09-27"
+AYANAMSA = "raman"
+NODE_MODE = "mean"
+
+QUESTIONS = (
+    {"id": "career", "domain": "career", "question": "未来一年，事业和收入该关注什么？"},
+    {"id": "marriage", "domain": "marriage", "question": "我的关系模式是什么？"},
+    {"id": "wealth", "domain": "wealth", "question": "我的财富增长方式和风险点是什么？"},
+    {"id": "health", "domain": "health", "question": "我近期的身心压力模式和调节重点是什么？"},
+    {"id": "education", "domain": "education", "question": "我的学习优势、瓶颈和进阶方向是什么？"},
+    {"id": "migration", "domain": "migration", "question": "迁居、置业或海外发展更适合怎样规划？"},
+    {"id": "family", "domain": "family", "question": "我的家庭关系与责任边界该如何理解？"},
+    {"id": "general", "domain": "general", "question": "请综合说明我当前最值得关注的主题。"},
+    {"id": "parents", "domain": "family", "question": "我和父母关系如何"},
+    {"id": "children", "domain": "family", "question": "我和子女的关系如何"},
+)
+
+CHART_SOURCES = (
+    {
+        "id": "steve_jobs",
+        "label": "Steve Jobs",
+        "path": "references/real_case_calibration/minute_rectification_development_v1.json",
+        "case_id": "steve_jobs_1955_development",
+    },
+    {
+        "id": "barack_obama",
+        "label": "Barack Obama",
+        "path": "references/real_case_calibration/minute_rectification_holdout_v4.json",
+        "case_id": "barack_obama_1961_aa_v4_holdout",
+    },
+    {
+        "id": "elizabeth_taylor",
+        "label": "Elizabeth Taylor",
+        "path": "references/real_case_calibration/minute_rectification_holdout_v4.json",
+        "case_id": "elizabeth_taylor_1932_aa_v4_holdout",
+    },
+)
+
+STATUS_TECHNIQUES = {
+    "mevg / global web evidence",
+    "real case calibration",
+    "vedastro main entry overview",
+    "vedastro cloud state",
+    "external oracle progress",
+    "interpretation source pack",
+    "module execution audit",
+    "exact cusp oracle",
+    "blind technical mode",
+    "timing precision gate",
+    "evidence packet",
+    "shadbala boundary",
+}
+RESEARCH_TECHNIQUES = {
+    "research d-n through d60",
+    "extended vargas d81/d108/d144",
+    "ashtottari dasha",
+}
+NOT_APPLICABLE_TECHNIQUES = {
+    "prashna chart",
+    "ashtakoota matching",
+    "adhana / niseka",
+    "muhurta election",
+}
+WESTERN_PREFIX = "western"
+
+STATUS_KEYS = {
+    "methodology",
+    "presentation",
+    "rectification",
+    "answer_policy",
+    "user_facing_limitation",
+    "hard_blockers",
+    "missing_route_layers",
+    "available_layers",
+    "must_use_layers",
+    "technique_truth",
+    "reference_transparency",
+    "shadbala_boundary",
+    "vedastro_cross_check",
+    "vedastro_gateway",
+    "commercial_evidence_status",
+    "success",
+    "omitted_domains",
+    "status",
+    "packet_version",
+    "schema_error",
+}
+
+# Domain card draft. Values are copied from the projection; nothing is rewritten.
+CARD_SPECS: dict[str, dict[str, Any]] = {
+    "career": {
+        "label": "事业",
+        "vargas": ["D10"],
+        "houses": [10],
+        "arudha": ["A10"],
+        "karakas": ["AmK"],
+        "planets": [],
+        "yogas": True,
+        "transits": True,
+        "ashtakavarga": False,
+        "shadbala": True,
+    },
+    "marriage": {
+        "label": "婚恋",
+        "vargas": ["D9"],
+        "houses": [7],
+        "arudha": ["UL", "A7"],
+        "karakas": ["DK"],
+        "planets": ["venus", "jupiter"],
+        "yogas": False,
+        "transits": True,
+        "ashtakavarga": False,
+        "shadbala": False,
+    },
+    "wealth": {
+        "label": "财富",
+        "vargas": ["D2", "D11"],
+        "houses": [2, 11, 9, 5],
+        "arudha": [],
+        "karakas": [],
+        "planets": [],
+        "yogas": True,
+        "transits": False,
+        "ashtakavarga": True,
+        "shadbala": True,
+    },
+    "health": {
+        "label": "健康",
+        "vargas": ["D6", "D8", "D30"],
+        "houses": [6, 8],
+        "arudha": [],
+        "karakas": [],
+        "planets": [],
+        "yogas": False,
+        "transits": True,
+        "ashtakavarga": False,
+        "shadbala": True,
+    },
+    "education": {
+        "label": "学习",
+        "vargas": ["D5", "D24"],
+        "houses": [5, 9],
+        "arudha": [],
+        "karakas": [],
+        "planets": ["mercury", "jupiter"],
+        "yogas": False,
+        "transits": False,
+        "ashtakavarga": False,
+        "shadbala": False,
+    },
+    "migration": {
+        "label": "迁居",
+        "vargas": ["D4", "D12"],
+        "houses": [4, 12],
+        "arudha": [],
+        "karakas": [],
+        "planets": [],
+        "yogas": False,
+        "transits": False,
+        "ashtakavarga": False,
+        "shadbala": False,
+    },
+    "family": {
+        "label": "家庭（现路由，父母与子女混在一起）",
+        "vargas": ["D7", "D12"],
+        "houses": [4, 5, 9],
+        "arudha": [],
+        "karakas": [],
+        "planets": [],
+        "yogas": False,
+        "transits": False,
+        "ashtakavarga": False,
+        "shadbala": False,
+    },
+    "parents": {
+        "label": "父母",
+        "vargas": ["D12"],
+        "houses": [4, 9],
+        "arudha": [],
+        "karakas": [],
+        "planets": ["sun", "moon"],
+        "yogas": False,
+        "transits": False,
+        "ashtakavarga": False,
+        "shadbala": False,
+        "basis": [
+            "skills/jyotish-vedic-astrology/references/strict-workflow-router.md shared baseline: D12 for family/ancestral themes",
+            "references/birth-time-rectification-decision-tree.md section 4: 父母/家族 -> D12",
+        ],
+    },
+    "children": {
+        "label": "子女",
+        "vargas": ["D7"],
+        "houses": [5],
+        "arudha": [],
+        "karakas": ["PK"],
+        "planets": ["jupiter"],
+        "yogas": False,
+        "transits": False,
+        "ashtakavarga": False,
+        "shadbala": False,
+        "basis": [
+            "skills/jyotish-vedic-astrology/references/strict-workflow-router.md shared baseline: D7 for children",
+            "references/birth-time-rectification-decision-tree.md section 4: 子女/生育 -> D7",
+        ],
+    },
+    "general": {
+        "label": "综合",
+        "vargas": ["D9", "D10", "D2"],
+        "houses": [1, 10, 7, 2],
+        "arudha": ["A10"],
+        "karakas": [],
+        "planets": [],
+        "yogas": True,
+        "transits": True,
+        "ashtakavarga": True,
+        "shadbala": True,
+    },
+}
+
+PART_B_BASE = (
+    "functional_benefic_malefic",
+    "vimshottari_md_ad_pd",
+    "narayana_current",
+    "ascendant_degree",
+)
+
+
+def dumps(value: Any) -> str:
+    return json.dumps(value, ensure_ascii=False, separators=(",", ":"))
+
+
+def estimate_tokens(text: str) -> dict[str, Any]:
+    chars = len(text)
+    return {
+        "chars": chars,
+        "token_estimate": int(round(chars / TOKEN_CHARS_PER_TOKEN)),
+        "token_method": TOKEN_METHOD,
+    }
+
+
+def _norm(value: str) -> str:
+    return re.sub(r"\s+", " ", value).strip().lower()
+
+
+def classify_audit_row(row: dict[str, Any]) -> str:
+    technique = _norm(str(row.get("technique") or ""))
+    system = _norm(str(row.get("system") or ""))
+    status = _norm(str(row.get("status") or ""))
+    if system == "western" or technique.startswith(WESTERN_PREFIX):
+        return "western"
+    if technique in RESEARCH_TECHNIQUES:
+        return "research"
+    if status == "not_applicable" or technique in NOT_APPLICABLE_TECHNIQUES:
+        return "not_applicable"
+    if technique in STATUS_TECHNIQUES or "vedastro" in technique or "mevg" in technique:
+        return "status"
+    return "core"
+
+
+def classify(path: tuple[str, ...], value: Any) -> str:
+    joined = ".".join(path).lower()
+    if "western_spectrum" in joined or joined.startswith("western"):
+        return "western"
+    if "research_dn" in joined or "extended" in joined and "varga" in joined:
+        return "research"
+    if isinstance(value, dict) and "technique" in value and "status" in value and "technique_audit" in joined:
+        return classify_audit_row(value)
+    leaf = path[-1].lower() if path else ""
+    if leaf in STATUS_KEYS or leaf.endswith("_boundary") or leaf.endswith("_status"):
+        return "status"
+    if isinstance(value, str) and _norm(value) == "not_applicable":
+        return "not_applicable"
+    return "core"
+
+
+def _whole(path: tuple[str, ...], value: Any) -> str | None:
+    joined = ".".join(path).lower()
+    if joined.endswith("western_spectrum"):
+        return "western"
+    if joined.endswith("research_dn") or joined.endswith("extended") and "varga_spectrum" in joined:
+        return "research"
+    if joined.endswith("methodology") or joined.endswith("presentation") or joined.endswith("rectification"):
+        return "status"
+    if (
+        isinstance(value, dict)
+        and "technique" in value
+        and "status" in value
+        and any(part == "technique_audit_table" for part in path)
+    ):
+        return classify_audit_row(value)
+    return None
+
+
+def _dominant(sizes: Counter[str]) -> str:
+    if not sizes:
+        return "status"
+    return max(CATEGORIES, key=lambda name: (sizes.get(name, 0), -CATEGORIES.index(name)))
+
+
+def account(value: Any, path: tuple[str, ...] = ()) -> Counter[str]:
+    """Partition dumps(value) across the five categories. Sum equals len(dumps(value))."""
+    whole = _whole(path, value)
+    if whole is not None:
+        return Counter({whole: len(dumps(value))})
+    if isinstance(value, dict):
+        sizes: Counter[str] = Counter()
+        if not value:
+            sizes[classify(path, value)] = 2
+            return sizes
+        items = list(value.items())
+        for index, (key, child) in enumerate(items):
+            child_path = path + (str(key),)
+            child_sizes = account(child, child_path)
+            sizes.update(child_sizes)
+            overhead = len(dumps(str(key))) + 1
+            if index:
+                overhead += 1
+            sizes[_dominant(child_sizes)] += overhead
+        sizes[_dominant(sizes)] += 2
+        return sizes
+    if isinstance(value, list):
+        sizes = Counter()
+        if not value:
+            sizes[classify(path, value)] = 2
+            return sizes
+        for index, child in enumerate(value):
+            child_sizes = account(child, path + (str(index),))
+            sizes.update(child_sizes)
+            if index:
+                sizes[_dominant(child_sizes)] += 1
+        sizes[_dominant(sizes)] += 2
+        return sizes
+    return Counter({classify(path, value): len(dumps(value))})
+
+
+def category_report(value: Any) -> dict[str, Any]:
+    sizes = account(value)
+    total = len(dumps(value))
+    covered = sum(sizes[name] for name in CATEGORIES)
+    return {
+        "categories": {name: int(sizes.get(name, 0)) for name in CATEGORIES},
+        "total_chars": total,
+        "category_sum": covered,
+        "sum_error_ratio": 0.0 if total == 0 else abs(covered - total) / total,
+        "tokens": estimate_tokens(dumps(value)),
+    }
+
+
+def duplicate_report(model_context: dict[str, Any]) -> dict[str, Any]:
+    consultations = model_context.get("consultations")
+    first = consultations[0] if isinstance(consultations, list) and consultations else None
+    spread_keys = [
+        key for key in (first or {})
+        if key in model_context and key != "consultations"
+    ]
+    matching = [
+        key for key in spread_keys
+        if dumps(model_context.get(key)) == dumps(first.get(key))
+    ]
+    named_copies: dict[str, int] = {}
+
+    def walk(node: Any, path: tuple[str, ...] = ()) -> None:
+        if isinstance(node, dict):
+            for key, child in node.items():
+                leaf = str(key)
+                if leaf in {"varga_spectrum", "western_spectrum", "technique_audit_table", "methodology"}:
+                    named_copies[leaf] = named_copies.get(leaf, 0) + 1
+                walk(child, path + (leaf,))
+        elif isinstance(node, list):
+            for index, child in enumerate(node):
+                walk(child, path + (str(index),))
+
+    walk(model_context)
+    consultation_chars = len(dumps(consultations)) if consultations is not None else 0
+    return {
+        "consultation_copies": 1 + (1 if isinstance(first, dict) else 0),
+        "spread_keys_matching_consultations_0": matching,
+        "consultations_chars": consultation_chars,
+        "named_subtree_copies": named_copies,
+    }
+
+
+def load_public_charts(root: Path) -> list[dict[str, Any]]:
+    charts = []
+    for spec in CHART_SOURCES:
+        payload = json.loads((root / spec["path"]).read_text(encoding="utf-8"))
+        case = next(item for item in payload["cases"] if item["case_id"] == spec["case_id"])
+        birth = case["birth"]
+        year, month, day = (int(part) for part in birth["date"].split("-"))
+        hour, minute = (int(part) for part in birth["time"].split(":")[:2])
+        charts.append({
+            "id": spec["id"],
+            "label": spec["label"],
+            "source": spec["path"],
+            "case_id": spec["case_id"],
+            "rodden_rating": (birth.get("source") or {}).get("rodden_rating"),
+            "place": birth.get("place"),
+            "body": {
+                "year": year,
+                "month": month,
+                "day": day,
+                "hour": hour,
+                "minute": minute,
+                "second": 0,
+                "lat": birth["latitude"],
+                "lon": birth["longitude"],
+                "tz": birth["timezone_offset"],
+                "city": birth.get("place") or spec["label"],
+                "ayanamsa": AYANAMSA,
+                "node_mode": NODE_MODE,
+                "today": REFERENCE_DATE,
+                "entry_mode": "direct_chart",
+                "defer_optional_external_evidence": True,
+                "declared_accuracy": "minute",
+                "birth_time_accuracy": "confirmed",
+            },
+        })
+    return charts
+
+
+def _dig(value: Any, *keys: str) -> Any:
+    current = value
+    for key in keys:
+        if not isinstance(current, dict) or key not in current:
+            return None
+        current = current[key]
+    return current
+
+
+def claim_evidence(model_context: dict[str, Any], category: str) -> dict[str, Any]:
+    cards = model_context.get("claim_cards")
+    if not isinstance(cards, list):
+        return {}
+    for card in cards:
+        if isinstance(card, dict) and card.get("category") == category and isinstance(card.get("evidence"), dict):
+            return card["evidence"]
+    return {}
+
+
+def _house_entry(houses: Any, number: int) -> Any:
+    if isinstance(houses, dict):
+        for key in (str(number), f"house_{number}", f"h{number}"):
+            if key in houses:
+                return houses[key]
+        for value in houses.values():
+            if isinstance(value, dict) and value.get("number") == number:
+                return value
+    if isinstance(houses, list):
+        for value in houses:
+            if isinstance(value, dict) and value.get("number") == number:
+                return value
+        if 1 <= number <= len(houses):
+            return houses[number - 1]
+    return None
+
+
+def _pick(mapping: Any, names: list[str]) -> dict[str, Any]:
+    if not isinstance(mapping, dict):
+        return {}
+    lowered = {str(key).lower(): key for key in mapping}
+    picked = {}
+    for name in names:
+        key = lowered.get(name.lower())
+        if key is not None:
+            picked[str(key)] = mapping[key]
+    return picked
+
+
+def cut_evidence_card(model_context: dict[str, Any], question_id: str) -> dict[str, Any]:
+    """Copy card fields from the projected model context. Missing paths stay gaps."""
+    spec = CARD_SPECS[question_id]
+    natal = claim_evidence(model_context, "natal_foundation")
+    timing = claim_evidence(model_context, "timing")
+    spectrum = natal.get("varga_spectrum") if isinstance(natal.get("varga_spectrum"), dict) else {}
+    formal = spectrum.get("formal") if isinstance(spectrum.get("formal"), dict) else {}
+    houses = natal.get("houses")
+    planets = natal.get("planets") if isinstance(natal.get("planets"), dict) else {}
+    functional = natal.get("functional_benefic_malefic")
+    dasha = timing.get("dasha_sub_periods") if isinstance(timing.get("dasha_sub_periods"), dict) else timing.get("dasha")
+    narayana = timing.get("narayana_dasha")
+    gaps = []
+    vargas = {}
+    for code in spec["vargas"]:
+        chart = formal.get(code)
+        if chart is None:
+            gaps.append(f"varga:{code}")
+        else:
+            vargas[code] = chart
+    house_rows = {}
+    for number in spec["houses"]:
+        row = _house_entry(houses, number)
+        if row is None:
+            gaps.append(f"house:{number}")
+        else:
+            house_rows[str(number)] = row
+    picked_planets = _pick(planets, spec["planets"])
+    for name in spec["planets"]:
+        if name.lower() not in {key.lower() for key in picked_planets}:
+            gaps.append(f"planet:{name}")
+    card = {
+        "card_id": question_id,
+        "label": spec["label"],
+        "question": model_context.get("question"),
+        "route": model_context.get("route"),
+        "base": {
+            "ascendant": natal.get("ascendant"),
+            "houses": houses,
+            "planet_placements": _planet_placements(planets),
+            "functional_benefic_malefic": functional,
+            "vimshottari": dasha,
+            "narayana_dasha": narayana,
+        },
+        "domain": {
+            "vargas": vargas,
+            "houses": house_rows,
+            "planets": picked_planets,
+            "arudha": _pick(natal.get("arudha_padas"), spec["arudha"]),
+            "karakas": _pick(_dig(natal, "jaimini", "chara_karakas") or natal.get("chara_karakas"), spec["karakas"]),
+            "yogas": natal.get("yogas") if spec["yogas"] else None,
+            "transits": timing.get("transits") if spec["transits"] else None,
+            "ashtakavarga": natal.get("ashtakavarga") if spec["ashtakavarga"] else None,
+            "shadbala": natal.get("shadbala") if spec["shadbala"] else None,
+        },
+        "gaps": gaps,
+        "basis": spec.get("basis", []),
+    }
+    if card["base"]["ascendant"] is None:
+        gaps.append("ascendant")
+    if functional is None:
+        gaps.append("functional_benefic_malefic")
+    if dasha is None:
+        gaps.append("vimshottari")
+    if narayana is None:
+        gaps.append("narayana_dasha")
+    text = dumps(card)
+    return {"card": card, "text": text, "size": estimate_tokens(text), "gaps": gaps}
+
+
+def _ci_get(mapping: Any, name: str) -> Any:
+    if not isinstance(mapping, dict):
+        return None
+    for key, value in mapping.items():
+        if str(key).lower() == name.lower():
+            return value
+    return None
+
+
+def _planet_placements(planets: Any) -> dict[str, Any]:
+    if not isinstance(planets, dict):
+        return {}
+    placed = {}
+    for name, row in planets.items():
+        if isinstance(row, dict):
+            placed[str(name)] = {
+                key: row[key] for key in ("sign", "house") if key in row
+            }
+        elif isinstance(row, str):
+            placed[str(name)] = {"sign": row}
+    return placed
+
+
+def engine_facts(workflow: dict[str, Any]) -> dict[str, Any]:
+    chart = workflow.get("chart") if isinstance(workflow.get("chart"), dict) else {}
+    modules = chart.get("modules") if isinstance(chart.get("modules"), dict) else {}
+    ascendant = chart.get("ascendant") if isinstance(chart.get("ascendant"), dict) else {}
+    planets = chart.get("planets") if isinstance(chart.get("planets"), dict) else {}
+    moon = _ci_get(planets, "moon")
+    moon = moon if isinstance(moon, dict) else {}
+    sub = modules.get("dasha_sub_periods") if isinstance(modules.get("dasha_sub_periods"), dict) else {}
+    current = sub.get("current") if isinstance(sub.get("current"), dict) else {}
+    mahadasha = current.get("mahadasha") if isinstance(current.get("mahadasha"), dict) else {}
+    antardasha = current.get("antardasha") if isinstance(current.get("antardasha"), dict) else {}
+    pratyantar = sub.get("pratyantar_dasha_timeline") if isinstance(sub.get("pratyantar_dasha_timeline"), dict) else {}
+    pratyantar_current = pratyantar.get("current") if isinstance(pratyantar.get("current"), dict) else {}
+    narayana = modules.get("narayana_dasha") if isinstance(modules.get("narayana_dasha"), dict) else {}
+    narayana_current = narayana.get("current_dasha") if isinstance(narayana.get("current_dasha"), dict) else {}
+    narayana_md = narayana_current.get("md") if isinstance(narayana_current.get("md"), dict) else {}
+    spectrum = modules.get("varga_spectrum") if isinstance(modules.get("varga_spectrum"), dict) else {}
+    formal = spectrum.get("formal") if isinstance(spectrum.get("formal"), dict) else {}
+    d12 = formal.get("D12") if isinstance(formal.get("D12"), dict) else {}
+    return {
+        "ascendant_sign": ascendant.get("sign"),
+        "moon_sign": moon.get("sign"),
+        "moon_house": moon.get("house"),
+        "vimshottari_lord": mahadasha.get("lord"),
+        "vimshottari_start": mahadasha.get("start"),
+        "vimshottari_end": mahadasha.get("end"),
+        "antardasha_start": antardasha.get("start"),
+        "antardasha_end": antardasha.get("end"),
+        "pratyantar_start": pratyantar_current.get("start"),
+        "pratyantar_end": pratyantar_current.get("end"),
+        "narayana_sign": narayana_md.get("sign"),
+        "d12_lagna": d12.get("lagna") if isinstance(d12.get("lagna"), str) else None,
+        "d12_moon": _ci_get(d12.get("planets"), "moon") if isinstance(d12.get("planets"), dict) else None,
+    }
+
+
+def card_facts(card: dict[str, Any]) -> dict[str, Any]:
+    base = card.get("base") if isinstance(card.get("base"), dict) else {}
+    domain = card.get("domain") if isinstance(card.get("domain"), dict) else {}
+    ascendant = base.get("ascendant") if isinstance(base.get("ascendant"), dict) else {}
+    moon = _ci_get(base.get("planet_placements"), "moon")
+    if not isinstance(moon, dict):
+        moon = _ci_get(domain.get("planets"), "moon")
+    moon = moon if isinstance(moon, dict) else {}
+    sub = base.get("vimshottari") if isinstance(base.get("vimshottari"), dict) else {}
+    current = sub.get("current") if isinstance(sub.get("current"), dict) else {}
+    mahadasha = current.get("mahadasha") if isinstance(current.get("mahadasha"), dict) else {}
+    antardasha = current.get("antardasha") if isinstance(current.get("antardasha"), dict) else {}
+    pratyantar = sub.get("pratyantar_dasha_timeline") if isinstance(sub.get("pratyantar_dasha_timeline"), dict) else {}
+    pratyantar_current = pratyantar.get("current") if isinstance(pratyantar.get("current"), dict) else {}
+    narayana = base.get("narayana_dasha") if isinstance(base.get("narayana_dasha"), dict) else {}
+    narayana_current = narayana.get("current_dasha") if isinstance(narayana.get("current_dasha"), dict) else {}
+    narayana_md = narayana_current.get("md") if isinstance(narayana_current.get("md"), dict) else {}
+    d12 = (domain.get("vargas") or {}).get("D12") if isinstance(domain.get("vargas"), dict) else None
+    d12 = d12 if isinstance(d12, dict) else {}
+    return {
+        "ascendant_sign": ascendant.get("sign"),
+        "moon_sign": moon.get("sign"),
+        "moon_house": moon.get("house"),
+        "vimshottari_lord": mahadasha.get("lord"),
+        "vimshottari_start": mahadasha.get("start"),
+        "vimshottari_end": mahadasha.get("end"),
+        "antardasha_start": antardasha.get("start"),
+        "antardasha_end": antardasha.get("end"),
+        "pratyantar_start": pratyantar_current.get("start"),
+        "pratyantar_end": pratyantar_current.get("end"),
+        "narayana_sign": narayana_md.get("sign"),
+        "d12_lagna": d12.get("lagna"),
+        "d12_moon": _ci_get(d12.get("planets"), "moon"),
+    }
+
+
+def verbatim_check(card: dict[str, Any], facts: dict[str, Any]) -> dict[str, Any]:
+    actual = card_facts(card)
+    has_d12 = isinstance((card.get("domain") or {}).get("vargas"), dict) and "D12" in card["domain"]["vargas"]
+    checks = {}
+    for key, expected in facts.items():
+        if key.startswith("d12_") and not has_d12:
+            checks[key] = {"status": "not_on_card", "expected": expected, "actual": None}
+            continue
+        got = actual.get(key)
+        if expected is None or expected == "":
+            checks[key] = {"status": "engine_missing", "expected": None, "actual": got}
+        elif got == expected:
+            checks[key] = {"status": "match", "expected": expected, "actual": got}
+        else:
+            checks[key] = {"status": "mismatch", "expected": expected, "actual": got}
+    mismatched = [key for key, row in checks.items() if row["status"] == "mismatch"]
+    return {"ok": not mismatched, "checks": checks, "mismatched": mismatched}
+
+
+def parse_registry_layers(source: str) -> dict[str, list[str]]:
+    found = {}
+    for match in re.finditer(r'id: "(\w+)".*?requiredLayers: \[([^\]]*)\]', source):
+        layers = re.findall(r'"([^"]+)"', match.group(2))
+        found[match.group(1)] = layers
+    return found
+
+
+def parse_methodology_routes(source: str) -> dict[str, str | None]:
+    found = {}
+    for match in re.finditer(r'(\w+): \{ strictRoute: (?:"([^"]+)"|null)', source):
+        found[match.group(1)] = match.group(2)
+    return found
+
+
+def parse_must_use_layers(source: str) -> dict[str, list[str]]:
+    block = re.search(r"DOMAIN_MUST_USE_LAYERS[\s\S]*?};", source)
+    if not block:
+        return {}
+    found = {}
+    for match in re.finditer(r'(\w+): \[([^\]]*)\]', block.group(0)):
+        found[match.group(1)] = re.findall(r'"([^"]+)"', match.group(2))
+    return found
+
+
+def source_matrix(root: Path) -> dict[str, Any]:
+    registry = parse_registry_layers((root / "frontend/src/lib/consultation-domain-registry.ts").read_text(encoding="utf-8"))
+    methodology = parse_methodology_routes((root / "frontend/src/lib/consultation-methodology.ts").read_text(encoding="utf-8"))
+    must_use = parse_must_use_layers((root / "frontend/src/mastra/consultation-workflow.ts").read_text(encoding="utf-8"))
+    from unified_consultation_orchestrator import UnifiedConsultationOrchestrator
+
+    python_routes = {
+        name: list(route.focus_techniques)
+        for name, route in UnifiedConsultationOrchestrator._ROUTE_DEFINITIONS.items()
+    }
+    domains = sorted(set(registry) | set(methodology) | set(python_routes) | set(CARD_SPECS))
+    rows = []
+    for domain in domains:
+        card_id = domain if domain in CARD_SPECS else None
+        rows.append({
+            "domain": domain,
+            "registry_required_layers": registry.get(domain, []),
+            "methodology_strict_route": methodology.get(domain),
+            "ts_must_use_layers": must_use.get(domain, []),
+            "python_focus_techniques": python_routes.get(domain, []),
+            "card_vargas": CARD_SPECS.get(card_id, {}).get("vargas", []) if card_id else [],
+            "parents_children_split": domain == "family",
+        })
+    return {"domains": rows, "skill_citations": {
+        "d12_family": "references/strict-workflow-router.md: D12 for family/ancestral themes",
+        "d7_children": "references/strict-workflow-router.md: D7 for children",
+        "decision_tree_parents": "references/birth-time-rectification-decision-tree.md: 父母/家族 -> D12",
+        "decision_tree_children": "references/birth-time-rectification-decision-tree.md: 子女/生育 -> D7",
+    }}
+
+
+def part_b_coverage(card: dict[str, Any], question_id: str) -> dict[str, Any]:
+    base = card.get("base") if isinstance(card.get("base"), dict) else {}
+    domain = card.get("domain") if isinstance(card.get("domain"), dict) else {}
+    spec = CARD_SPECS[question_id]
+    present = {
+        "functional_benefic_malefic": base.get("functional_benefic_malefic") is not None,
+        "vimshottari": base.get("vimshottari") is not None,
+        "narayana": base.get("narayana_dasha") is not None,
+        "ascendant_raw": base.get("ascendant") is not None,
+        "domain_vargas": sorted(domain.get("vargas") or {}),
+        "expected_vargas": spec["vargas"],
+    }
+    missing_vargas = [code for code in spec["vargas"] if code not in (domain.get("vargas") or {})]
+    return {
+        "dual_dasha": present["vimshottari"] and present["narayana"],
+        "domain_divisional": not missing_vargas,
+        "functional_benefic_malefic": present["functional_benefic_malefic"],
+        "raw_data": present["ascendant_raw"] and present["vimshottari"],
+        "mevg": "kept_backstage",
+        "real_case_calibration": "kept_backstage",
+        "missing_vargas": missing_vargas,
+        "present": present,
+    }
+
+
+TELEMETRY_SPEC = {
+    "stores": "numbers, enums, and field names only",
+    "does_not_store": [
+        "question text",
+        "answer text",
+        "birth date",
+        "birth time",
+        "birth place",
+        "name",
+        "email",
+        "user id",
+        "session id",
+        "matched substring",
+    ],
+    "fields": [
+        {"name": "domain", "type": "enum", "values": [item["id"] for item in QUESTIONS]},
+        {"name": "card_version", "type": "enum", "values": ["evidence-card-draft-20260927"]},
+        {"name": "card_chars", "type": "int"},
+        {"name": "card_token_estimate", "type": "int"},
+        {"name": "cited_field_ids", "type": "enum[]", "note": "ids from the card schema, not free text"},
+        {"name": "feedback", "type": "enum", "values": ["up", "down", "none"]},
+    ],
+    "citation_method": {
+        "rule": "A field is cited when its scalar value appears in the answer and the value is an ISO date, a degree token, or a compound planet-in-sign phrase of at least 8 characters. Bare planet or sign names are not counted.",
+        "false_positive": "A date or degree that also appears in the question, or a repeated stock phrase, can be counted without the model using that field.",
+        "false_negative": "A paraphrase that names the period without copying the date is not counted.",
+        "stored": "Only the field id. The matched text is discarded.",
+    },
+    "aggregates": [
+        "count of answers by domain and card_version",
+        "fields whose cited rate stays under 5 percent after 30 answers in that domain",
+        "down rate by domain and card_version",
+    ],
+}
+
+
+def card_dependencies(question_id: str) -> list[str]:
+    spec = CARD_SPECS[question_id]
+    modules = ["compute_chart", "functional_benefic_malefic", "dasha_sub_periods", "narayana_dasha"]
+    if spec["vargas"]:
+        modules.append("varga_requested_only")
+    if spec["arudha"] or spec["karakas"]:
+        modules.append("arudha_padas")
+    if spec["karakas"]:
+        modules.append("chara_karakas")
+    if spec["transits"]:
+        modules.append("transits")
+    if spec["ashtakavarga"]:
+        modules.append("ashtakavarga")
+    if spec["shadbala"]:
+        modules.append("shadbala")
+    if spec["yogas"]:
+        modules.append("yogas")
+    return modules
diff --git a/scripts/research/consult_evidence_card_run.py b/scripts/research/consult_evidence_card_run.py
new file mode 100644
index 00000000..7d009d6b
--- /dev/null
+++ b/scripts/research/consult_evidence_card_run.py
@@ -0,0 +1,263 @@
+"""Run the consultation evidence-card inventory. Read-only toward the engine.
+
+External VedAstro is not called. The product foreground path still joins a
+background gateway; this process replaces that join with the engine's own
+blocked payload so local timing is not a network wait. Status text from that
+blocked payload is what the model sees when the gateway does not return.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import subprocess
+import sys
+import time
+from pathlib import Path
+from typing import Any
+
+ROOT = Path(__file__).resolve().parents[2]
+SCRIPTS = ROOT / "scripts"
+RESEARCH = Path(__file__).resolve().parent
+for path in (ROOT, SCRIPTS, RESEARCH):
+    if str(path) not in sys.path:
+        sys.path.insert(0, str(path))
+
+from consult_evidence_card_lib import (  # noqa: E402
+    QUESTIONS,
+    card_dependencies,
+    category_report,
+    cut_evidence_card,
+    duplicate_report,
+    engine_facts,
+    estimate_tokens,
+    load_public_charts,
+    part_b_coverage,
+    source_matrix,
+    verbatim_check,
+)
+
+
+def _block_external_vedastro() -> None:
+    import vedastro_foreground as gateway
+
+    def start(self):
+        self.meta = {
+            "freshness": "research_not_called",
+            "external_vedastro": "not_called",
+        }
+        self.cached_gateway = gateway._blocked_foreground_vedastro(
+            reason="research_external_vedastro_not_called",
+        )
+        self.future = None
+        return self
+
+    gateway.ForegroundVedastroSession.start = start
+
+
+def _workflow_body(chart: dict[str, Any], question: dict[str, str]) -> dict[str, Any]:
+    from consultation_plan_contract import PLAN_VERSION, plan_route_contract
+
+    domain = question["domain"]
+    contract = plan_route_contract(domain)
+    if contract is None:
+        raise RuntimeError(f"no plan contract for {domain}")
+    body = dict(chart["body"])
+    body.update({
+        "question": question["question"],
+        "question_text": question["question"],
+        "theme": list(contract.themes),
+        "plan_version": PLAN_VERSION,
+        "strict_workflow_route": domain,
+        "required_layers": list(contract.required_layers),
+        "claim_boundary": contract.claim_boundary,
+        "plan_depth": "standard",
+        "requested_domains": list(contract.requested_domains),
+        "timing_horizon": None,
+        "precision_boundary": "server_evidence_required",
+        "required_evidence_categories": list(contract.required_evidence_categories),
+        "surface": "api_web",
+    })
+    return body
+
+
+def _run_workflow(body: dict[str, Any]) -> dict[str, Any]:
+    from jyotish_api_server import JyotishAPIHandler
+
+    handler = JyotishAPIHandler.__new__(JyotishAPIHandler)
+    return handler._compute_consultation_workflow(body)
+
+
+def _project(jobs: list[dict[str, str]], summary_path: Path) -> list[dict[str, Any]]:
+    spec_path = summary_path.with_suffix(".jobs.json")
+    spec_path.write_text(json.dumps({"items": jobs}), encoding="utf-8")
+    tsx = ROOT / "frontend" / "node_modules" / "tsx" / "dist" / "cli.mjs"
+    env = os.environ.copy()
+    env["JYOTISHA_PROJECT_ROOT"] = str(ROOT)
+    command = [
+        "node",
+        str(tsx),
+        str(ROOT / "scripts" / "research" / "project_consult_model_context.ts"),
+        "project",
+        str(spec_path),
+        str(summary_path),
+    ]
+    completed = subprocess.run(command, cwd=ROOT, env=env, capture_output=True, text=True)
+    if completed.returncode != 0:
+        raise RuntimeError(completed.stderr[-4000:] or completed.stdout[-4000:])
+    return json.loads(summary_path.read_text(encoding="utf-8"))
+
+
+def _time_layers(chart_body: dict[str, Any]) -> dict[str, float]:
+    """Time local layers on one birth payload. VedAstro stays blocked."""
+    from jyotish_api_server import (
+        JyotishAPIHandler,
+        _attach_local_consultation_layers,
+        _build_consultation_varga_spectrum,
+        _custom_research_dn_chart,
+        _planet_longitudes,
+    )
+
+    handler = JyotishAPIHandler.__new__(JyotishAPIHandler)
+    timings: dict[str, float] = {}
+
+    def elapsed(name: str, fn, *args, **kwargs):
+        started = time.perf_counter()
+        result = fn(*args, **kwargs)
+        timings[name] = round(time.perf_counter() - started, 4)
+        return result
+
+    chart = elapsed("compute_chart", handler._compute_chart, {
+        **chart_body,
+        "skip_vedastro_main_entry_overview": True,
+    })
+    planets = chart.get("planets") if isinstance(chart, dict) else {}
+    ascendant = chart.get("ascendant") if isinstance(chart, dict) else {}
+    elapsed("attach_local_layers", _attach_local_consultation_layers, handler, chart, chart_body, chart_body)
+    if isinstance(planets, dict) and isinstance(ascendant, dict) and planets and ascendant:
+        elapsed("varga_spectrum", _build_consultation_varga_spectrum, handler, planets, ascendant)
+        elapsed("shadbala", handler._compute_shadbala, {**chart_body, "planets": planets, "ascendant": ascendant})
+        elapsed("ashtakavarga", handler._compute_ashtakavarga, {"planets": planets, "ascendant": ascendant})
+        elapsed("functional_benefic_malefic", handler._functional_benefic_malefic_snapshot, planets, ascendant)
+        try:
+            module = __import__("divisional_charts_extended", fromlist=["DivisionalChartsCalculator"])
+            calc = module.DivisionalChartsCalculator()
+            planet_lons = _planet_longitudes(planets)
+            asc_lon = float(ascendant.get("lon"))
+            elapsed("one_research_division", _custom_research_dn_chart, calc, planet_lons, asc_lon, 3)
+        except Exception as exc:
+            timings["one_research_division_error"] = exc.__class__.__name__
+    return timings
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--out", default=str(ROOT / "docs" / "research" / "consult_evidence_card_inventory_2026_09_27.json"))
+    parser.add_argument("--cache", default="")
+    parser.add_argument("--only-chart", action="append", default=[])
+    parser.add_argument("--only-question", action="append", default=[])
+    parser.add_argument("--skip-timing", action="store_true")
+    args = parser.parse_args()
+    if os.environ.get("PYTHONHASHSEED") != "0":
+        raise SystemExit("Set PYTHONHASHSEED=0 before starting this process (ERR-111).")
+
+    _block_external_vedastro()
+    cache = Path(args.cache) if args.cache else Path(os.environ.get("TEMP", ".")) / "consult-evidence-card-20260927"
+    cache.mkdir(parents=True, exist_ok=True)
+    charts = load_public_charts(ROOT)
+    questions = list(QUESTIONS)
+    if args.only_chart:
+        charts = [chart for chart in charts if chart["id"] in args.only_chart]
+    if args.only_question:
+        questions = [item for item in questions if item["id"] in args.only_question]
+
+    runs = []
+    jobs = []
+    for chart in charts:
+        for question in questions:
+            run_id = f"{chart['id']}__{question['id']}"
+            workflow_path = cache / f"{run_id}.workflow.json"
+            started = time.perf_counter()
+            workflow = _run_workflow(_workflow_body(chart, question))
+            wall = round(time.perf_counter() - started, 3)
+            workflow_path.write_text(json.dumps(workflow, ensure_ascii=False), encoding="utf-8")
+            projected_path = cache / f"{run_id}.model.json"
+            jobs.append({
+                "id": run_id,
+                "domain": question["domain"],
+                "question": question["question"],
+                "workflow_path": str(workflow_path),
+                "out_path": str(projected_path),
+            })
+            runs.append({
+                "id": run_id,
+                "chart_id": chart["id"],
+                "chart_label": chart["label"],
+                "question_id": question["id"],
+                "domain": question["domain"],
+                "wall_seconds": wall,
+                "workflow_chars": workflow_path.stat().st_size,
+                "route": (workflow.get("routing") or {}).get("question_type"),
+                "focus_techniques": (workflow.get("routing") or {}).get("focus_techniques"),
+                "success": workflow.get("success"),
+            })
+            print(f"{run_id} wall={wall}s route={runs[-1]['route']}", flush=True)
+
+    summary_path = cache / "projection-summary.json"
+    projected = {item["id"]: item for item in _project(jobs, summary_path)}
+    inventory = []
+    for run, job in zip(runs, jobs):
+        model_context = json.loads(Path(job["out_path"]).read_text(encoding="utf-8"))
+        workflow = json.loads(Path(job["workflow_path"]).read_text(encoding="utf-8"))
+        categories = category_report(model_context)
+        card = cut_evidence_card(model_context, run["question_id"])
+        facts = engine_facts(workflow)
+        check = verbatim_check(card["card"], facts)
+        inventory.append({
+            **run,
+            "projection": projected.get(run["id"]),
+            "categories": categories,
+            "duplicates": duplicate_report(model_context),
+            "card_size": card["size"],
+            "card_gaps": card["gaps"],
+            "part_b": part_b_coverage(card["card"], run["question_id"]),
+            "verbatim": check,
+            "card_dependencies": card_dependencies(run["question_id"]),
+            "sample_card": card["card"] if run["chart_id"] == "steve_jobs" and run["question_id"] in {"parents", "career"} else None,
+        })
+
+    timings = {}
+    if not args.skip_timing:
+        for chart in charts:
+            print(f"timing {chart['id']}", flush=True)
+            try:
+                timings[chart["id"]] = _time_layers(chart["body"])
+            except Exception as exc:
+                timings[chart["id"]] = {"error": exc.__class__.__name__, "message": str(exc)[:300]}
+
+    payload = {
+        "baseline": "76924e3362c0a47d9d8de896c448c66055826f70",
+        "reference_date": "2026-09-27",
+        "ayanamsa": "raman",
+        "node_mode": "mean",
+        "pythonhashseed": "0",
+        "external_vedastro": "not_called",
+        "token_method": estimate_tokens("")["token_method"],
+        "charts": [
+            {"id": chart["id"], "label": chart["label"], "source": chart["source"], "case_id": chart["case_id"], "rodden_rating": chart["rodden_rating"]}
+            for chart in load_public_charts(ROOT)
+        ],
+        "source_matrix": source_matrix(ROOT),
+        "runs": inventory,
+        "layer_timings_seconds": timings,
+    }
+    out = Path(args.out)
+    out.parent.mkdir(parents=True, exist_ok=True)
+    out.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
+    print(f"wrote {out}", flush=True)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/scripts/research/consult_evidence_card_time.py b/scripts/research/consult_evidence_card_time.py
new file mode 100644
index 00000000..829b4483
--- /dev/null
+++ b/scripts/research/consult_evidence_card_time.py
@@ -0,0 +1,88 @@
+"""Time local consultation layers on the real workflow path. No VedAstro network."""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+import time
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+sys.path[:0] = [str(ROOT), str(ROOT / "scripts"), str(ROOT / "scripts" / "research")]
+
+from consult_evidence_card_lib import QUESTIONS, load_public_charts  # noqa: E402
+import consult_evidence_card_run as runner  # noqa: E402
+import jyotish_api_server as api  # noqa: E402
+
+
+def _wrap(bucket: dict[str, float], name: str, fn):
+    def inner(*args, **kwargs):
+        started = time.perf_counter()
+        try:
+            return fn(*args, **kwargs)
+        finally:
+            bucket[name] = round(bucket.get(name, 0.0) + time.perf_counter() - started, 4)
+    return inner
+
+
+def main() -> int:
+    if os.environ.get("PYTHONHASHSEED") != "0":
+        raise SystemExit("Set PYTHONHASHSEED=0")
+    runner._block_external_vedastro()
+    charts = load_public_charts(ROOT)
+    question = QUESTIONS[0]
+    results = {}
+    originals = {
+        "compute_chart": api.JyotishAPIHandler._compute_chart,
+        "thematic": api.JyotishAPIHandler._compute_thematic_report,
+        "rectification": api.JyotishAPIHandler._compute_rectification_gate,
+        "attach": api._attach_local_consultation_layers,
+        "varga_spectrum": api._build_consultation_varga_spectrum,
+        "research_chart": api._custom_research_dn_chart,
+        "varga_full": api.JyotishAPIHandler._compute_varga_full,
+    }
+    for chart in charts:
+        bucket: dict[str, float] = {}
+        calls = {"research_chart": 0}
+
+        def counting_research(*args, **kwargs):
+            calls["research_chart"] += 1
+            return originals["research_chart"](*args, **kwargs)
+
+        api.JyotishAPIHandler._compute_chart = _wrap(bucket, "compute_chart", originals["compute_chart"])
+        api.JyotishAPIHandler._compute_thematic_report = _wrap(bucket, "thematic_report", originals["thematic"])
+        api.JyotishAPIHandler._compute_rectification_gate = _wrap(bucket, "rectification_gate", originals["rectification"])
+        api._attach_local_consultation_layers = _wrap(bucket, "attach_local_layers", originals["attach"])
+        api._build_consultation_varga_spectrum = _wrap(bucket, "varga_spectrum", originals["varga_spectrum"])
+        api._custom_research_dn_chart = _wrap(bucket, "research_dn_loop", counting_research)
+        api.JyotishAPIHandler._compute_varga_full = _wrap(bucket, "varga_full", originals["varga_full"])
+        started = time.perf_counter()
+        runner._run_workflow(runner._workflow_body(chart, question))
+        bucket["workflow_wall"] = round(time.perf_counter() - started, 4)
+        bucket["research_dn_calls"] = calls["research_chart"]
+        results[chart["id"]] = bucket
+        print(chart["id"], bucket, flush=True)
+    for name, fn in originals.items():
+        if name == "compute_chart":
+            api.JyotishAPIHandler._compute_chart = fn
+        elif name == "thematic":
+            api.JyotishAPIHandler._compute_thematic_report = fn
+        elif name == "rectification":
+            api.JyotishAPIHandler._compute_rectification_gate = fn
+        elif name == "attach":
+            api._attach_local_consultation_layers = fn
+        elif name == "varga_spectrum":
+            api._build_consultation_varga_spectrum = fn
+        elif name == "research_chart":
+            api._custom_research_dn_chart = fn
+        elif name == "varga_full":
+            api.JyotishAPIHandler._compute_varga_full = fn
+    out = ROOT / "docs" / "research" / "consult_evidence_card_timings_2026_09_27.json"
+    out.write_text(json.dumps(results, indent=2), encoding="utf-8")
+    print(f"wrote {out}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/scripts/research/project_consult_model_context.ts b/scripts/research/project_consult_model_context.ts
new file mode 100644
index 00000000..888eb68a
--- /dev/null
+++ b/scripts/research/project_consult_model_context.ts
@@ -0,0 +1,107 @@
+/**
+ * Read-only projection of a consultation workflow payload into the text the
+ * answer model sees. Does not modify frontend runtime files.
+ *
+ * The single-domain wrap matches consultation-tools.ts toModelDomainPlanContext
+ * when consultations.length === 1 and omittedDomains.length === 0:
+ *   return { ...consultations[0], ...plan, consultations };
+ */
+import { readFileSync, writeFileSync } from "node:fs";
+import { createConsultationPlan } from "../../frontend/src/lib/consultation-plan.ts";
+import { consultationMethodologyForDomains } from "../../frontend/src/lib/consultation-methodology.ts";
+import type { ConsultationDomain } from "../../frontend/src/lib/consultation-domain-registry.ts";
+import {
+  consultationWorkflowResponseSchema,
+  toAgentConsultationContext,
+  toModelOutput,
+} from "../../frontend/src/mastra/consultation-workflow.ts";
+
+type JsonRecord = Record<string, unknown>;
+
+function readJson(path: string): JsonRecord {
+  return JSON.parse(readFileSync(path, "utf8")) as JsonRecord;
+}
+
+function planFields(domain: ConsultationDomain, question: string) {
+  const plan = createConsultationPlan({
+    userIntent: question,
+    theme: domain,
+    consultationMode: "verified_chart",
+  });
+  return {
+    plan_version: plan.plan_version,
+    depth: plan.depth,
+    requested_domains: plan.requestedDomains,
+    timing_horizon: plan.timingHorizon,
+    precision_boundary: plan.precisionBoundary,
+    required_evidence_categories: plan.requiredEvidenceCategories,
+    birthTimeMode: plan.birthTimeMode,
+  };
+}
+
+function projectOne(workflow: JsonRecord, domain: ConsultationDomain, question: string) {
+  const parsed = consultationWorkflowResponseSchema.safeParse(workflow);
+  const agentContext = toAgentConsultationContext(parsed.success ? parsed.data : workflow);
+  const consultationPlan = createConsultationPlan({
+    userIntent: question,
+    theme: domain,
+    consultationMode: "verified_chart",
+  });
+  const modelOutput = toModelOutput(agentContext, consultationPlan);
+  const consultation = { domain, ...modelOutput };
+  const methodology = consultationMethodologyForDomains([domain]);
+  const plan = {
+    success: agentContext.success === true,
+    domains: [domain],
+    omitted_domains: [] as ConsultationDomain[],
+    ...(methodology ? { methodology } : {}),
+  };
+  const modelContext = { ...consultation, ...plan, consultations: [consultation] };
+  return {
+    schema_ok: parsed.success,
+    schema_error: parsed.success ? null : parsed.error.issues.slice(0, 8).map((issue) => ({
+      path: issue.path.join("."),
+      code: issue.code,
+    })),
+    methodology_sections: methodology?.sections.length ?? 0,
+    methodology_chars: methodology
+      ? JSON.stringify(methodology).length
+      : 0,
+    model_context: modelContext,
+  };
+}
+
+const [mode, ...rest] = process.argv.slice(2);
+
+if (mode === "plans") {
+  const spec = readJson(rest[0]);
+  const questions = spec.questions as Array<{ id: string; domain: ConsultationDomain; question: string }>;
+  const plans: JsonRecord = {};
+  for (const item of questions) {
+    plans[item.id] = planFields(item.domain, item.question);
+  }
+  writeFileSync(rest[1], JSON.stringify(plans));
+} else if (mode === "project") {
+  const jobs = readJson(rest[0]) as {
+    items: Array<{ id: string; domain: ConsultationDomain; question: string; workflow_path: string; out_path: string }>;
+  };
+  const summary: JsonRecord[] = [];
+  for (const item of jobs.items) {
+    const workflow = readJson(item.workflow_path);
+    const projected = projectOne(workflow, item.domain, item.question);
+    const text = JSON.stringify(projected.model_context);
+    writeFileSync(item.out_path, text);
+    summary.push({
+      id: item.id,
+      schema_ok: projected.schema_ok,
+      schema_error: projected.schema_error,
+      methodology_sections: projected.methodology_sections,
+      methodology_chars: projected.methodology_chars,
+      model_chars: text.length,
+    });
+  }
+  writeFileSync(rest[1], JSON.stringify(summary));
+} else {
+  process.stderr.write("usage: plans <spec.json> <out.json> | project <jobs.json> <summary.json>\n");
+  process.exit(2);
+}
diff --git a/tests/test_consult_evidence_card_research.py b/tests/test_consult_evidence_card_research.py
new file mode 100644
index 00000000..f2c895df
--- /dev/null
+++ b/tests/test_consult_evidence_card_research.py
@@ -0,0 +1,127 @@
+"""Pure-function checks for the consultation evidence-card research scripts."""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(ROOT / "scripts" / "research"))
+
+from consult_evidence_card_lib import (  # noqa: E402
+    CARD_SPECS,
+    CATEGORIES,
+    TELEMETRY_SPEC,
+    account,
+    category_report,
+    cut_evidence_card,
+    dumps,
+    parse_methodology_routes,
+    parse_must_use_layers,
+    parse_registry_layers,
+    verbatim_check,
+)
+
+
+def test_category_partition_sums_exactly():
+    payload = {
+        "ascendant": {"sign": "Leo", "degree": 12.5},
+        "methodology": {"sections": ["checklist"]},
+        "western_spectrum": {"zodiac": "tropical", "natal": {"sun": "Aries"}},
+        "varga_spectrum": {
+            "formal": {"D1": {"lagna": "Leo"}},
+            "research_dn": {"D3": {"lagna": "Virgo"}},
+            "extended": {"D81": {"lagna": "Cancer"}},
+        },
+        "technique_audit_table": [
+            {"technique": "Functional Benefic/Malefic", "status": "executed"},
+            {"technique": "MEVG / Global Web Evidence", "status": "blocked"},
+            {"technique": "Prashna chart", "status": "not_applicable"},
+            {"technique": "Research D-N through D60", "status": "executed"},
+            {"technique": "Western natal (tropical)", "status": "executed", "system": "western"},
+        ],
+    }
+    report = category_report(payload)
+    assert report["sum_error_ratio"] == 0.0
+    assert report["category_sum"] == report["total_chars"] == len(dumps(payload))
+    assert set(report["categories"]) == set(CATEGORIES)
+    assert report["categories"]["western"] > 0
+    assert report["categories"]["research"] > 0
+    assert report["categories"]["status"] > 0
+    assert report["categories"]["not_applicable"] > 0
+    assert report["categories"]["core"] > 0
+    assert sum(account(payload).values()) == len(dumps(payload))
+
+
+def test_card_copies_projection_values_without_rewriting():
+    model = {
+        "question": "我和父母关系如何",
+        "route": "family",
+        "claim_cards": [
+            {
+                "category": "natal_foundation",
+                "evidence": {
+                    "ascendant": {"sign": "Capricorn", "degree": 3.25},
+                    "houses": [{"number": 4, "sign": "Aries", "lord": "Mars"}],
+                    "planets": {"sun": {"sign": "Aquarius", "house": 2}, "moon": {"sign": "Cancer", "house": 7}},
+                    "functional_benefic_malefic": {"functional_benefics": ["Venus"], "functional_malefics": ["Mars"]},
+                    "varga_spectrum": {"formal": {"D12": {"lagna": "Pisces", "planets": {"moon": "Leo"}}}},
+                },
+            },
+            {
+                "category": "timing",
+                "evidence": {
+                    "dasha_sub_periods": {
+                        "current": {
+                            "mahadasha": {"lord": "Saturn", "start": "2020-01-01", "end": "2026-12-31"},
+                            "antardasha": {"lord": "Mercury", "start": "2024-01-01", "end": "2025-01-01"},
+                        },
+                    },
+                    "narayana_dasha": {"current_dasha": {"md": {"sign": "Scorpio"}}},
+                },
+            },
+        ],
+    }
+    cut = cut_evidence_card(model, "parents")
+    assert cut["card"]["domain"]["vargas"]["D12"]["lagna"] == "Pisces"
+    assert cut["card"]["base"]["ascendant"]["degree"] == 3.25
+    assert "D7" not in cut["card"]["domain"]["vargas"]
+    check = verbatim_check(cut["card"], {
+        "ascendant_sign": "Capricorn",
+        "d12_lagna": "Pisces",
+        "d12_moon": "Leo",
+        "vimshottari_start": "2020-01-01",
+        "vimshottari_end": "2026-12-31",
+        "moon_sign": "Cancer",
+        "moon_house": 7,
+    })
+    assert check["ok"] is True
+    assert check["checks"]["vimshottari_start"]["status"] == "match"
+
+
+def test_source_parsers_keep_family_split_gap():
+    registry = (ROOT / "frontend/src/lib/consultation-domain-registry.ts").read_text(encoding="utf-8")
+    methodology = (ROOT / "frontend/src/lib/consultation-methodology.ts").read_text(encoding="utf-8")
+    workflow = (ROOT / "frontend/src/mastra/consultation-workflow.ts").read_text(encoding="utf-8")
+    layers = parse_registry_layers(registry)
+    routes = parse_methodology_routes(methodology)
+    must_use = parse_must_use_layers(workflow)
+    assert "D12" in layers["family"] and "D7" in layers["family"]
+    assert "父母" not in "".join(layers["family"])
+    assert routes["family"] is None
+    assert "family" not in must_use
+    assert CARD_SPECS["parents"]["vargas"] == ["D12"]
+    assert CARD_SPECS["children"]["vargas"] == ["D7"]
+
+
+def test_telemetry_spec_stores_no_user_text():
+    banned = {"question text", "answer text", "birth date", "name", "email", "user id"}
+    assert banned <= set(TELEMETRY_SPEC["does_not_store"])
+    stored = {field["name"] for field in TELEMETRY_SPEC["fields"]}
+    assert stored == {"domain", "card_version", "card_chars", "card_token_estimate", "cited_field_ids", "feedback"}
+    assert "matched substring" in TELEMETRY_SPEC["does_not_store"]
+
+
+def test_single_domain_wrap_source_still_matches_projector():
+    source = (ROOT / "frontend/src/mastra/consultation-tools.ts").read_text(encoding="utf-8")
+    assert "return { ...consultations[0], ...plan, consultations };" in source