sync(upstream): port astrologer branch d09feab7 (public-sync-20261107) calculation changes

Product 2026-11-07: sync the astrologer's working branch (ea2a9d65..d09feab7).

- 0266b6ad: year lord picks by the native five-fold Panchavargiya only; a
  PyJHora score (research switch) is attached per candidate as
  external_oracle_comparison (observation_only_not_selection_input) and
  never selects. panchavargiya_selection_policy on the result; candidate_list
  and the reader-report candidate table carry the five components and raw total.
  The legacy Sun/Mars/Saturn table relabel is not applicable: calc_sodhita_av
  was already removed here (BUG-1209).
- 8c4bff8a + a5b75886: Sodhita no longer votes in finance adjudication; the
  bridge keeps raw 2/11 scores with prediction_scoring_allowed false.
- ba8e36ec: finance delivery inventory (raw, no vote), wrapped producer status
  counts as blocked in machine-evidence sections, transit section, report gate
  evidence_claims bindings, finance support review readiness.
- 5962368d: dispositor chain dispositor_sign is the dispositor's own sign.
- 8813c851: BCP observed at the reading date (bcp_reference, PL9 row).
- d09feab7: nakshatra_advanced.calculate_stellar_jeeva_sareera and the
  nadi-stellar-roles CLI; specialized-jyotish SKILL.md, usage packs, ontology
  and gap scanner mirrored.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01DbBXoyn7Hj3LCW3BUs5bZ8

docs/research/stellar_jeeva_sareera_2026_11_07.md

@@ -0,0 +1,100 @@
+# Stellar Jeeva/Sareera: bounded native calculation
+
+## Scope and current-window exploration
+
+Repository maintenance, not a personal interpretation or a customer export.
+Starting HEAD b88fdb3b was clean on codex/public-sync-20261107. Pre-work check
+passed, including external-adapter diagnostics and remote visibility. Seven
+worktrees were listed. Existing current-capability index, report authority,
+PL9 dashboard and error ledger were consulted. Governance reports only
+main_worktree_dirty during this implementation; that is not an adapter failure.
+Earlier whole-machine inventory is documented in knowledge_call_chain_followup_2026_11_07.md;
+it is not represented as a fresh full-content scan here. This round searched
+the native scripts, tests, specialized skill, review/extraction queues and the
+registered local stellar book. No mirror, frozen tree or personal report changed.
+
+Reuse: find_nakshatra for half-open stellar boundaries; Jaimini module's
+traditional sign-owner table only (not its dual-owner/strength rules);
+existing Nadi review queue for discovery; native engine CLI for actual execution.
+
+## Source record and conflict
+
+Local corpus registration:
+`Nadi_Stellar Effects -- Jyotish -- 2022 -- f8eef571147711ee4eb4479a35bd2428 -- Anna’s Archive.md`.
+Text SHA256: `f30db43d842a9484316d6608f6385dfabe7232265469e67938f42459e25c4b42`.
+The filename year is not a verified publication edition. Chapter 4 is the
+Jeeva/Sareera chapter in this Kalamsa-Gunas/Meena source. The book cites
+N. V. Raghava Chary, Practical Stellar Astrology, second edition 2004,
+pp108–111; that original edition has NOT been independently checked.
+
+| Topic | PDF page | Printed page | Corpus line locator |
+|---|---:|---:|---:|
+| Four starting rules | 87 | 84 | 4513 onward |
+| Conflicting exalted-Venus example | 89 | 86 | 4626 onward |
+| Detailed controlling-planet hierarchy and Saturn exception | 92 | 89 | 4800 onward |
+| Comparative summary with different qualifications | 93–94 | 90–91 | 4882 onward |
+| Anonymous structural table | 95–99 | 92–96 | 4979 onward |
+
+Used search_jyotish_books.py with the registered filename, query Jeeva and
+read-unit 92. Visually inspected original PDF pages 89 and 92. Page89 actually
+names Mercury then Jupiter as Sareera in the same example; it is a printed
+conflict, not merely OCR. No copyrighted source pages/text are added to Git.
+
+The explicit runtime profile follows the detailed procedure on printed p89:
+original Saturn in Anuradha retains control; otherwise sign owner, exaltation,
+stellar Digbala, own-star among Digbala candidates, listed strength order,
+then retain the original seed. It does not silently substitute the later
+comparative list's broader own-star/debility qualifications. The own-star
+Sareera fallback applies to the final Jeeva, as the printed pp93–95 table
+demonstrates even when the initial bhava lord is different.
+
+## Callable contract
+
+`scripts.nakshatra_advanced.calculate_stellar_jeeva_sareera` accepts:
+
+- Exactly nine already-sidereal planetary longitudes, one explicit bhava lord,
+  explicit ayanamsa label and mean/true node mode. It does not derive birth data.
+- Optional stellar_digbala boolean map. Missing values are not false. Numeric
+  Shadbala scores are rejected. These flags remain caller-supplied assumptions.
+- Optional nodal_exaltation_signs: explicit zero-based sign or null for each node.
+  No cross-school nodal exaltation is silently adopted. If this matters to an
+  unresolved group and is absent, that branch is blocked.
+
+Native CLI: `python3 scripts/jyotish_engine.py nadi-stellar-roles --request <local.json>`.
+The local JSON fields are the function's argument names. It prints JSON without
+writing charts, profiles or exports. Roles, selected profile, source identity,
+stage seeds/companions, decision reasons and missing inputs remain visible.
+Status is executed or blocked; evidence is parameter_sensitive;
+external_verified and prediction_scoring_allowed remain false.
+
+The existing Nadi review queue now points to the real function. A queue listing
+still says not_executed and does not approve a rule or bypass admission.
+No customer frozen pin, annual score, finance score, Dasha date or interpretation
+is changed. No automatic forecasting use is claimed.
+
+## External cross-check, not new rule admission
+
+- [Practitioner article, 2012-02-28](https://srigurucriticalcareastrologer.blogspot.com/2012/02/nadi-jyothisha-jeeva-and-sareera.html):
+  own-star and substitution examples overlap the existing book. Its Venus example
+  names Mercury without the following Jupiter sentence. Corroboration supports
+  an editorial-error hypothesis, not a verified erratum or predictive validation.
+- [Iranganti Rangacharya article](https://saptarishisshop.com/jeeva-sareera-theory-of-prediction-i-by-iranganti-rangacharya/):
+  distinct same-name tradition, not admitted into this Meena profile.
+
+No new web-only rule enters runtime; these are source-comparison/discovery URLs.
+No community testimony or repeated example is treated as independent calibration.
+
+## Verification and remaining work
+
+269 related tests passed, including native CLI execution, seven traditional
+planet roles from the anonymous source table under explicit stellar assumptions,
+own-star fallback, owner/exaltation precedence, seed-specific Saturn exception,
+missing inputs, invalid numbers and Nadi queue admission boundaries.
+That table replay is not an independent oracle; the uncertain Mars OCR minute
+is represented by a same-star/sign value and is not a precise longitude check.
+
+Still open: source-specific automatic Nakshatra Digbala and its aspect rules;
+adjudication of the comparative-list differences and nodal exaltations;
+independent numerical cases; predictive calibration; optional report routing.
+This is source-bounded structural execution, not global closure or permission
+to turn these roles alone into financial, medical or event predictions.

mcp_server.py

@@ -2090,18 +2090,25 @@ def _derive_sodhita_finance_support(ashtakavarga: Any, asc_sign: Optional[str])
             sign_to_score[str(sign)] = float(score)
 
     raw_scores: Dict[str, Any] = {}
-    numeric_scores: Dict[int, float] = {}
     for house in (2, 11):
         sign = _SIGNS[(asc_idx + house - 1) % 12]
         if sign in sign_to_score:
-            numeric_scores[house] = sign_to_score[sign]
             value = sign_to_score[sign]
             raw_scores[str(house)] = int(value) if value.is_integer() else value
 
     base["raw_scores"] = raw_scores
-    if len(numeric_scores) == 2 and max(numeric_scores.values()) <= 19:
-        base["level"] = "obstructive"
-        base["signals"] = ["sodhita_wealth_friction"]
+    producer = _safe_get(ashtakavarga, "sodhita") or {}
+    # Upstream a5b75886: no source-adjudicated finance threshold exists for this
+    # bridge. Caller method/permission labels cannot make the legacy <=19 penalty valid.
+    known_legacy = (
+        producer.get("method_id") == "legacy_malefic_contribution_subtraction_v1"
+        or producer.get("method") == "Sodhita Ashtakavarga (BPHS标准)"
+    )
+    base["status"] = producer.get("status") or (
+        "legacy_reference_only" if known_legacy else "method_unverified"
+    )
+    base["prediction_scoring_allowed"] = False
+    base["reason"] = "unadjudicated_contribution_subtraction_not_wealth_evidence"
     return base
 
 
@@ -2610,9 +2617,9 @@ def _derive_event_judgement(route: str, present: Dict[str, Any], missing: List[s
         pav_finance_support = present.get("pav_finance_support") or {}
         if pav_finance_support.get("level") == "supportive":
             score += 2
-        sodhita_finance_support = present.get("sodhita_finance_support") or {}
-        if sodhita_finance_support.get("level") == "obstructive":
-            score -= 2
+        # Upstream a5b75886: Sodhita packets remain available as raw evidence,
+        # never a finance vote. No admitted threshold/profile exists, including
+        # for historical caches.
         kakshya_finance_support = present.get("kakshya_finance_support") or {}
         if kakshya_finance_support.get("level") == "supportive":
             score += 2
@@ -2680,8 +2687,6 @@ def _derive_event_judgement(route: str, present: Dict[str, Any], missing: List[s
             secondary_context.append("functional_benefic_malefic_used")
         if pav_finance_support.get("level") == "supportive":
             secondary_context.append("pav_finance_support")
-        if sodhita_finance_support.get("level") == "obstructive":
-            secondary_context.append("sodhita_wealth_friction")
         if kakshya_finance_support.get("level") == "supportive":
             secondary_context.append("kakshya_finance_support")
         elif kakshya_finance_support.get("level") == "obstructive":
@@ -4005,6 +4010,13 @@ def _collect_strict_evidence(route: str, result: Dict[str, Any]) -> Dict[str, An
                 "plus at least one wealth-related convergence domain."
             ),
         }
+        # Upstream ba8e36ec: optional existing producers are delivered as raw
+        # inventory only; they never vote or fill required evidence.
+        try:
+            from scripts.finance_astrology_support_review import build_finance_delivery_inventory
+        except ImportError:  # pragma: no cover - scripts/ on sys.path
+            from finance_astrology_support_review import build_finance_delivery_inventory
+        strict["finance_delivery_inventory"] = build_finance_delivery_inventory(modules)
         strict["official_primary_evidence"] = _build_official_primary_evidence(route, present)
         strict["local_supplemental_evidence"] = _build_local_supplemental_evidence(route, present)
         strict["fallback_used"], strict["blocked_items"] = _build_fallback_and_blocked(

references/technique_ontology.json

@@ -707,12 +707,13 @@
       "calculation_status": "source_bounded_wired",
       "doctrine_status": "usage_pack_present",
       "variant_status": "profile_inventory_present",
-      "variant_profile_ids": ["niryaana_shoola_goel_profile", "niryaana_shoola_raman_profile", "niryaana_shoola_pyjhora_observation_profile"],
+      "variant_profile_ids": ["pvr_niryaana_shoola_v1", "niryaana_shoola_pyjhora_observation_profile"],
       "routing_status": "skill_linked",
       "report_status": "source_bounded_wired",
       "local_paths": ["scripts/niryaana_shoola_dasha.py", "scripts/niryaana_shoola_family_contract.py"],
       "report_paths": ["jyotish_engine.worksheets.timing_and_predictive_systems.dasha_master_pack.families.niryaana_shoola", "references/oracle/pl9_p92_p103_field_audit_2026_09_11.json"],
-      "producer_contract": {"entrypoint": "scripts.niryaana_shoola_dasha.calculate_niryaana_shoola_dasha", "maturity": "source_bounded_wired", "verification_scope": "stronger Lagna/seventh selection, explicit tie-break, named Goel/Raman/PyJHora duration profiles and MD/AD/PD boundaries", "claim_boundary": "Named profile support only; worksheet path is wired but parameter-sensitive parity remains open."}
+      "producer_contract": {"entrypoint": "scripts.niryaana_shoola_dasha.calculate_niryaana_shoola_dasha", "maturity": "source_bounded_wired", "verification_scope": "PVR second/eighth ayur-strength selection with unresolved ties blocked; movable/fixed/dual 7/8/9 calendar-year MD; external observation separate", "claim_boundary": "Named MD profile only, longevity-domain research rather than relationship timing; AD/PD source rule and same-profile external parity remain open."},
+      "next_required": ["source-backed AD/PD rule and row-level replay", "independent same-profile MD case; no predictive or global admission"]
     },
     "kalachakra_dasha": {"calculation_status":"source_bounded_wired","doctrine_status":"usage_pack_present","variant_status":"profile_inventory_present","variant_profile_ids":["kalachakra_native_recursive_profile","kalachakra_pl9_pages_83_88_boundary_profile","kalachakra_pyjhora_observation_profile"],"routing_status":"skill_linked","report_status":"source_bounded_wired","local_paths":["scripts/kalachakra_dasha.py","scripts/kalachakra_pl9_report_boundary_packet.py"],"report_paths":["jyotish_engine.worksheets.timing_and_predictive_systems.dasha_master_pack.families.kala_chakra","kalachakra_pl9_report_boundary_packet.boundary_rows","references/oracle/kalachakra_pl9_p83_88_structural_contract_2026_08_11.json"],"producer_contract":{"entrypoint":"scripts.kalachakra_dasha.calculate_kalachakra_dasha","maturity":"source_bounded_wired","verification_scope":"savya/apasavya selection, balance, Jeeva/Deha and recursive MD/AD/PD with PL9 conflict packet","claim_boundary":"Conflict-labeled Kala Chakra output; PL9 continuation and external parity remain unclosed."}},
     "lagna_kendradi_moola_dasha": {"calculation_status":"source_bounded_wired","doctrine_status":"usage_pack_present","variant_status":"profile_inventory_present","variant_profile_ids":["lagna_kendradi_explicit_seed_profile","lagna_kendradi_pyjhora_observation_profile"],"routing_status":"skill_linked","report_status":"source_bounded_wired","local_paths":["scripts/lagna_kendradi_dasha.py","scripts/lagna_kendradi_family_contract.py"],"report_paths":["jyotish_engine.worksheets.timing_and_predictive_systems.dasha_master_pack.families.lagna_kendradi","references/oracle/pl9_p92_p103_field_audit_2026_09_11.json"],"producer_contract":{"entrypoint":"scripts.lagna_kendradi_dasha.calculate_lagna_kendradi_dasha","maturity":"source_bounded_wired","verification_scope":"explicit Lagna seed, Kendra/Panaphara/Apoklima group order and profile arbitration","claim_boundary":"Explicit profile producer; automatic selector and source parity remain open."}},

scripts/bhrigu_pada_dasha.py

@@ -136,7 +136,7 @@ def calc_pada_dasha_marriage_timing(birth_moon_lon, birth_date_jd,
     return analysis
 
 def bhrigu_pada_dasha_full_report(birth_moon_lon, birth_date_jd,
-                                   d9_7lord_sign=None, d9_planets=None):
+                                   d9_7lord_sign=None, d9_planets=None, *, target_date_jd=None):
     """
     Bhrigu Pada Dasha 完整报告 v7.0
 
@@ -147,6 +147,7 @@ def bhrigu_pada_dasha_full_report(birth_moon_lon, birth_date_jd,
     - birth_date_jd: 出生 JD
     - d9_7lord_sign: D9 7宫主星座 (0-11)
     - d9_planets: D9 行星数据 {name: longitude}
+    - target_date_jd: BCP 观测 JD；省略时只输出明确标记的出生时点（上游 8813c851）
 
     Returns:
     - dict: 完整报告
@@ -221,7 +222,12 @@ def bhrigu_pada_dasha_full_report(birth_moon_lon, birth_date_jd,
             report['d9_verification']['window_details'] = window_details
 
     # BCP周期整合
-    report['bcp_cycle'] = calc_bcp_cycle(birth_moon_lon, birth_date_jd, birth_date_jd)
+    bcp_target_jd = birth_date_jd if target_date_jd is None else target_date_jd
+    report['bcp_cycle'] = calc_bcp_cycle(birth_moon_lon, birth_date_jd, bcp_target_jd)
+    report['bcp_reference'] = {
+        'target_jd': bcp_target_jd,
+        'scope': 'birth_epoch_default' if target_date_jd is None else 'explicit_target',
+    }
 
     return report
 

scripts/finance_astrology_support_review.py

@@ -20,9 +20,55 @@ FINANCE_PRIORITY_GAPS = [
 
 
 def _present(value: Any) -> str:
+    if isinstance(value, dict) and str(value.get("status", "")).lower() in {
+        "blocked", "missing", "error", "failed", "not_available_yet", "not_executed", "not_applicable"
+    }:
+        return "blocked"
     return "present" if bool(value) else "missing"
 
 
+FINANCE_EXISTING_MODULES = {
+    "argala": "scripts/argala.py",
+    "dispositor_chains": "scripts/jyotish_engine.py",
+    "tajika": "scripts/solar_return.py",
+    "bhrigu_pada_dasha": "scripts/bhrigu_pada_dasha.py",
+    "sudasa": "scripts/sudasa.py",
+}
+
+
+def build_finance_delivery_inventory(modules: dict[str, Any]) -> dict[str, Any]:
+    """Preserve existing optional data without calling presence execution or a vote."""
+    from copy import deepcopy
+
+    rows = []
+    for name, producer in FINANCE_EXISTING_MODULES.items():
+        value = modules.get(name)
+        presence = _present(value)
+        rows.append({
+            "technique": name, "producer": producer,
+            "source_path": "modules." + name,
+            "delivery_status": {"present": "payload_delivered", "missing": "not_delivered",
+                                "blocked": "producer_status_blocked"}[presence],
+            "source_status": value.get("status") if isinstance(value, dict) else None,
+            "execution_status": "not_verified_by_inventory",
+            "raw": deepcopy(value),
+        })
+    return {
+        "rows": rows,
+        "claim_boundary": "delivery_inventory_only_not_execution_or_prediction_validation",
+        "missing_means": "not_delivered_in_this_packet_not_missing_from_repository",
+        "presentation_order": ["executive_summary", "thematic_narrative", "evidence_appendix"],
+        "inference_constraints": [
+            "Strength is not outcome valence; SAV and Bhava Bala do not prove retention.",
+            "Repeated planet or house evidence is not independent confirmation.",
+            "Drig is not a wealth vote without a named source-specific domain rule.",
+            "Unknown birth precision requires sensitivity evidence for narrow windows.",
+            "Retain varga methods, full period boundaries and dispositor chains.",
+            "Repeated model agreement is not event validation or calibrated probability.",
+        ],
+    }
+
+
 def build_finance_astrology_support_review(
     *,
     route_packet: dict[str, Any] | None,
@@ -48,7 +94,7 @@ def build_finance_astrology_support_review(
             "d2": _present(sections.get("D2")),
             "d11": _present(machine_evidence_packet.get("D11") or sections.get("D11")),
             "vimshottari": _present(sections.get("dasha_boundaries")),
-            "narayana": _present(runtime_evidence_log.get("cross_system_arbitration")),
+            "narayana": _present(sections.get("narayana") or sections.get("narayana_dasha")),
             "shadbala": _present(sections.get("shadbala")),
             "ashtakavarga": _present(sections.get("ashtakavarga")),
             "transit": _present(sections.get("transit")),
@@ -67,13 +113,19 @@ def build_finance_astrology_support_review(
         ],
     }
 
-    finance_surface["status"] = "used" if route in {"finance", "wealth"} else "not_applicable"
+    finance_surface["missing_evidence"] = [
+        key for key, state in finance_surface["coverage"].items() if state != "present"
+    ]
+    finance_surface["readiness"] = (
+        "not_applicable" if route not in {"finance", "wealth"} else
+        "incomplete" if finance_surface["missing_evidence"] else "payloads_present_execution_unverified"
+    )
     finance_surface["audit_rows"] = [
         {
             "technique": "Finance Astrology Support Review",
             "status": finance_surface["status"],
             "used": finance_surface["status"] == "used",
-            "effect_on_confidence": "finance_route_support_ready" if finance_surface["status"] == "used" else "not_applicable",
+            "effect_on_confidence": finance_surface["readiness"],
         }
     ]
     return finance_surface

scripts/full_report_quality_gate.py

@@ -140,6 +140,45 @@ def _promotion_status(blocking_reasons: list[str], review_reasons: list[str], wa
     return "passed"
 
 
+def evaluate_evidence_claims(packet: dict[str, Any]) -> dict[str, Any]:
+    """Validate explicit claim bindings, not arbitrary free-text astrological prose.
+
+    Each claim has a path (list of dictionary keys/list indices) and a value.
+    Model-declared 'used' or a repeated answer never counts as a receipt.
+    """
+    claims = packet.get("evidence_claims")
+    if claims is None or claims == []:
+        return {"status": "not_supplied", "checked": 0, "errors": [],
+                "boundary": "free_text_not_semantically_verified"}
+    if not isinstance(claims, list):
+        return {"status": "blocked", "checked": 0, "errors": ["claims_not_list"]}
+    errors = []
+    for i, claim in enumerate(claims):
+        if not isinstance(claim, dict) or "value" not in claim:
+            errors.append(f"claim_{i}:invalid_binding")
+            continue
+        path = claim.get("path")
+        if not isinstance(path, list) or not path or path[0] == "evidence_claims":
+            errors.append(f"claim_{i}:invalid_path")
+            continue
+        value = packet
+        try:
+            for key in path:
+                if isinstance(value, dict) and isinstance(key, str):
+                    value = value[key]
+                elif isinstance(value, list) and type(key) is int and key >= 0:
+                    value = value[key]
+                else:
+                    raise KeyError("invalid_path_component")
+        except (KeyError, IndexError, TypeError):
+            errors.append(f"claim_{i}:source_missing")
+            continue
+        if type(value) is not type(claim["value"]) or value != claim["value"]:
+            errors.append(f"claim_{i}:value_mismatch")
+    return {"status": "blocked" if errors else "bindings_match", "checked": len(claims),
+            "errors": errors, "boundary": "bound_values_only_not_formula_or_prediction_validation"}
+
+
 def evaluate_full_report(packet: dict[str, Any], rendered_markdown: str | None = None) -> dict[str, Any]:
     """Evaluate an assembled report without mutating calculation or report content."""
     packet = _as_dict(packet)
@@ -147,6 +186,9 @@ def evaluate_full_report(packet: dict[str, Any], rendered_markdown: str | None =
     blocking_reasons: list[str] = []
     review_reasons: list[str] = []
     warning_reasons: list[str] = []
+    claim_validation = evaluate_evidence_claims(packet)
+    if claim_validation["status"] == "blocked":
+        blocking_reasons.append("evidence_claim_bindings_invalid")
 
     source_schema = str(packet.get("schema") or "")
     if source_schema != REPORT_SCHEMA:
@@ -557,6 +599,7 @@ def evaluate_full_report(packet: dict[str, Any], rendered_markdown: str | None =
         "status": status,
         "checks": checks,
         "blocking_reasons": blocking_reasons,
+        "evidence_claim_validation": claim_validation,
         "review_reasons": review_reasons,
         "warning_reasons": warning_reasons,
         "professional_coverage_manifest": professional_coverage_manifest,

scripts/jyotish_engine.py

@@ -592,12 +592,14 @@ def calc_dispositor_chain(planet_name, planets_data, max_depth=12):
             break
         sign = pdata['sign']
         dispositor = SIGN_LORDS.get(sign, '')
+        # Upstream 5962368d: the dispositor's own location, not the sign it owns.
+        dispositor_data = planets_data.get(dispositor)
         chain.append({
             'planet': current_planet,
             'sign': sign,
             'sign_cn': SIGNS_CN.get(sign, ''),
             'dispositor': dispositor,
-            'dispositor_sign': sign,  # 定位星所在的星座（即当前行星所在星座）
+            'dispositor_sign': dispositor_data.get('sign') if isinstance(dispositor_data, dict) else None,
         })
         if not dispositor:
             break
@@ -9934,7 +9936,7 @@ def render_pl9_markdown(packet: dict) -> str:
             raw_timing_rows.append((
                 'Bhrigu Pada / BCP',
                 bhrigu_raw.get('status', 'blocked'),
-                f"出生月亮={birth_moon.get('longitude', '-')}°；序列行数={len(bhrigu_raw.get('dasha_sequence', []))}",
+                f"出生月亮={birth_moon.get('longitude', '-')}°；序列行数={len(bhrigu_raw.get('dasha_sequence', []))}；BCP观测日期={bhrigu_raw.get('bcp_reference_date', '未指定；核对原始时点')}",
                 'raw_full_reading.modules.bhrigu_pada_dasha',
             ))
         pac_raw = timing_sheet.get('double_transit_pac') if isinstance(timing_sheet.get('double_transit_pac'), dict) else {}
@@ -14753,6 +14755,14 @@ def cmd_nakshatra_dasha(args):
     return _build_response_envelope('nakshatra-dasha', _impl(args), args=args, execution_status='executed')
 
 
+def cmd_nadi_stellar_roles(args):
+    """Upstream d09feab7: explicit Meena Jeeva/Sareera structure; no prediction or scoring."""
+    from nakshatra_advanced import calculate_stellar_jeeva_sareera
+
+    request = json.loads(Path(args.request).read_text(encoding='utf-8'))
+    return calculate_stellar_jeeva_sareera(**request)
+
+
 def cmd_nakshatra_full(args):
     from cmd_nakshatra_adv import cmd_nakshatra_full as _impl
     return _build_response_envelope('nakshatra-full', _impl(args), args=args, execution_status='executed')
@@ -16246,11 +16256,17 @@ def cmd_full_reading(args):
                 d9_seventh_lord_data = d9_data.get(d9_seventh_lord, {}) if isinstance(d9_data, dict) else {}
                 if isinstance(d9_seventh_lord_data, dict) and d9_seventh_lord_data.get('sign') in SIGNS:
                     d9_7lord_sign = SIGNS.index(d9_seventh_lord_data['sign'])
+            # Upstream 8813c851: BCP is observed at the reading date, not the birth epoch.
+            bcp_reference_date = getattr(args, 'transit_date', None) or getattr(args, 'today', None) or datetime.now().strftime('%Y-%m-%d')
+            bcp_year, bcp_month, bcp_day = map(int, bcp_reference_date.split('-'))
+            bcp_target_jd = swe.julday(bcp_year, bcp_month, bcp_day, 12.0 - args.tz)
             bpd_result = bhrigu_pada_dasha_full_report(
                 moon_lon, birth_jd,
                 d9_7lord_sign=d9_7lord_sign,
                 d9_planets=d9_planets,
+                target_date_jd=bcp_target_jd,
             )
+            bpd_result['bcp_reference_date'] = bcp_reference_date
             bpd_result['status'] = 'parameter_sensitive'
             bpd_result['claim_boundary'] = (
                 'Bhrigu Pada / BCP is a source-limited approximate progression family. '
@@ -18796,6 +18812,10 @@ def main():
     p.add_argument('--age', type=float, default=None, help='当前年龄')
     p.add_argument('--transit-date', default=None, help='过境日期 YYYY-MM-DD（默认今天）')
 
+    # 18.7 nadi-stellar-roles (upstream d09feab7)
+    p = sub.add_parser('nadi-stellar-roles', help='显式 Meena Jeeva/Sareera 结构计算；不生成预测或评分')
+    p.add_argument('--request', required=True, help='本地 JSON：九星恒星经度、宫主、岁差、交点及可选星宿方向力')
+
     # 19. argala (v3.7新增)
     p = sub.add_parser('argala', help='Argala门闩系统')
     _add_chart_args(p)
@@ -18980,7 +19000,7 @@ def main():
             'validate': cmd_validate, 'audit': cmd_audit, 'report': cmd_report,
             'varga-full': cmd_varga_full, 'aspects': cmd_aspects, 'jaimini': cmd_jaimini,
             'nakshatra-adv': cmd_nakshatra_adv, 'nakshatra-dasha': cmd_nakshatra_dasha,
-            'nakshatra-full': cmd_nakshatra_full, 'argala': cmd_argala, 'tajika': cmd_tajika,
+            'nakshatra-full': cmd_nakshatra_full, 'nadi-stellar-roles': cmd_nadi_stellar_roles, 'argala': cmd_argala, 'tajika': cmd_tajika,
             'marriage-match': cmd_marriage_match, 'solar-return': cmd_solar_return,
             'narayana-dasha': cmd_narayana_dasha, 'muhurta': cmd_muhurta,
             'full-reading': cmd_full_reading, 'pl9-export': cmd_pl9_export, 'prashna': cmd_prashna,

scripts/nakshatra_advanced.py

@@ -111,6 +111,115 @@ def find_nakshatra(longitude: float) -> Dict:
     }
 
 
+def calculate_stellar_jeeva_sareera(
+    positions: Dict, *, bhava_lord: str, ayanamsa: str, node_mode: str,
+    stellar_digbala: Optional[Dict] = None,
+    nodal_exaltation_signs: Optional[Dict] = None,
+) -> Dict:
+    """Structural Meena classification, explicit printed-p89 procedure only.
+
+    Input longitudes are already sidereal; this function does not convert them.
+    Stellar Digbala is a supplied boolean relationship result, NOT Shadbala.
+    Nodal exaltations have no implicit default. Unknown comparisons stay blocked.
+    See docs/research/stellar_jeeva_sareera_2026_11_07.md for source conflicts.
+    """
+    if __package__:
+        from .jaimini import SIGNS, SIGN_LORDS
+    else:
+        from jaimini import SIGNS, SIGN_LORDS
+    planets = ("Sun", "Moon", "Mars", "Mercury", "Jupiter", "Venus",
+               "Saturn", "Rahu", "Ketu")
+    if not isinstance(positions, dict) or set(positions) != set(planets):
+        raise ValueError("Supply exactly nine planetary sidereal longitudes")
+    for value in positions.values():
+        if isinstance(value, bool) or not isinstance(value, (int, float)) or not math.isfinite(value):
+            raise ValueError("Planetary longitudes must be finite numbers")
+    if bhava_lord not in planets or not isinstance(ayanamsa, str) or not ayanamsa.strip():
+        raise ValueError("Explicit bhava_lord and ayanamsa are required")
+    if node_mode not in {"mean", "true"}:
+        raise ValueError("node_mode must be mean or true")
+    strengths = {} if stellar_digbala is None else stellar_digbala
+    if not isinstance(strengths, dict) or any(
+        p not in planets or type(v) is not bool for p, v in strengths.items()
+    ):
+        raise ValueError("stellar_digbala requires planetary booleans, not strength scores")
+    nodes = {} if nodal_exaltation_signs is None else nodal_exaltation_signs
+    if not isinstance(nodes, dict) or any(
+        p not in {"Rahu", "Ketu"} or (v is not None and (type(v) is not int or not 0 <= v < 12))
+        for p, v in nodes.items()
+    ):
+        raise ValueError("Explicit nodal exaltation: sign index 0..11 or None")
+    signs = {p: int(v % 360 // 30) for p, v in positions.items()}
+    stars = {p: find_nakshatra(v) for p, v in positions.items()}
+    exaltation = dict(Sun=0, Moon=1, Mars=9, Mercury=5, Jupiter=3, Venus=11, Saturn=6)
+    exaltation.update(nodes)
+    order = {p: i for i, p in enumerate(("Rahu", "Ketu", "Sun", "Moon", "Venus",
+                                         "Jupiter", "Saturn", "Mars", "Mercury"))}
+    trace = []
+
+    def choose(seed, stage):
+        group = [p for p in planets if signs[p] == signs[seed]]
+        row = {"stage": stage, "seed": seed, "companions": group}
+        trace.append(row)
+
+        def finish(selected, reason):
+            row.update(selected=selected, reason=reason)
+            return selected
+
+        if seed == "Saturn" and signs[seed] == 7 and stars[seed]["nakshatra_idx"] == 16:
+            return finish(seed, "original_saturn_anuradha_exception")
+        if len(group) == 1:
+            return finish(seed, "alone")
+        owner = SIGN_LORDS[SIGNS[signs[seed]]]
+        if owner in group:
+            return finish(owner, "sign_owner")
+        unknown_nodes = [p for p in group if p in {"Rahu", "Ketu"} and p not in nodes]
+        if unknown_nodes:
+            row["missing"] = unknown_nodes
+            return finish(None, "nodal_exaltation_profile_required")
+        exalted = [p for p in group if exaltation.get(p) == signs[p]]
+        if len(exalted) > 1:
+            return finish(None, "multiple_exalted_comparison_unresolved")
+        if exalted:
+            return finish(exalted[0], "exalted")
+        missing = [p for p in group if p not in strengths]
+        if missing:
+            row["missing"] = missing
+            return finish(None, "stellar_digbala_required")
+        directional = [p for p in group if strengths[p]]
+        if not directional:
+            return finish(seed, "no_stronger_companion")
+        own_star = [p for p in directional if stars[p]["nakshatra_lord"] == p]
+        return finish(min(own_star or directional, key=order.get),
+                      "stellar_digbala_own_star" if own_star else "stellar_digbala_order")
+
+    jeeva = choose(stars[bhava_lord]["nakshatra_lord"], "jeeva")
+    sareera = None
+    if jeeva is not None:
+        seed = stars[jeeva]["nakshatra_lord"]
+        if seed == jeeva:
+            seed = SIGN_LORDS[SIGNS[signs[jeeva]]]
+        sareera = choose(seed, "sareera")
+    return {
+        "schema": "jyotish.stellar_jeeva_sareera.v1",
+        "method": "meena_stellar_detailed_procedure_printed_p89",
+        "status": "executed" if sareera is not None else "blocked",
+        "evidence_grade": "parameter_sensitive",
+        "prediction_scoring_allowed": False,
+        "external_verified": False,
+        "profile": {"ayanamsa": ayanamsa, "node_mode": node_mode,
+                    "stellar_digbala": dict(strengths), "nodal_exaltation_signs": dict(nodes)},
+        "bhava_lord": bhava_lord, "jeeva": jeeva, "sareera": sareera, "trace": trace,
+        "source": {"corpus_file": "Nadi_Stellar Effects -- Jyotish -- 2022 -- f8eef571147711ee4eb4479a35bd2428 -- Anna’s Archive.md",
+                   "text_sha256": "f30db43d842a9484316d6608f6385dfabe7232265469e67938f42459e25c4b42",
+                   "pdf_pages": [87, 89, 90, 92, 96], "printed_pages": [84, 86, 87, 89, 93]},
+        "boundaries": ["Structural roles only; no event, date or outcome inference",
+                       "Printed p86 example names two different Sareera planets",
+                       "Printed pp90-91 comparative list is not silently merged into p89",
+                       "Supplied stellar Digbala and nodal exaltation require separate source review"],
+    }
+
+
 def calc_tara_bala(moon_nak_idx: int, target_nak_idx: int) -> Dict:
     """
     Tara Bala计算：月亮星宿到目标星宿的9星宿循环关系

scripts/pl9_reader_export.py

@@ -2439,15 +2439,20 @@ def render_pl9_parity_markdown(packet: dict) -> str:
                 lines.append('')
                 if candidates:
                     lines.extend([
-                        '| Candidate source | Planet | House | Sign | Panchavargiya score |',
-                        '|------------------|--------|-------|------|---------------------|',
+                        # Upstream 0266b6ad: the selecting score is the native five-fold
+                        # profile; its five components are shown beside it.
+                        '| Candidate source | Planet | House | Sign | Graha | Uchcha | Hudda | Drekkana | Navamsha | Raw (of 80) | Panchavargiya score |',
+                        '|------------------|--------|-------|------|-------|--------|-------|----------|----------|-------------|---------------------|',
                     ])
                     for row in candidates:
                         if not isinstance(row, dict):
                             continue
+                        parts = _dict(row.get('panchavargiya_components'))
                         lines.append(
                             f"| {_cell(row.get('source'))} | {_cell(_token(row.get('planet')))} | {_cell(row.get('planet_house'))} | "
-                            f"{_cell(_token(row.get('planet_sign')))} | {_cell(row.get('panchavargiya_score'))} |"
+                            f"{_cell(_token(row.get('planet_sign')))} | "
+                            + ''.join(f"{_cell(parts.get(key))} | " for key in ('graha_bala', 'uchcha_bala', 'hudda_bala', 'drekkana_bala', 'navamsha_bala'))
+                            + f"{_cell(row.get('panchavargiya_raw_total'))} | {_cell(row.get('panchavargiya_score'))} |"
                         )
                     lines.append('')
             planet_longitudes = _dict(annual_chart_data.get('planet_longitudes'))

scripts/tajika.py

@@ -313,6 +313,7 @@ def calc_panchadhikari_year_lord(
                 'panchavargiya_raw_total': pvb.get('raw_total'),
                 'panchavargiya_engine': pvb['engine'],
                 'panchavargiya_components': pvb['components'],
+                'external_oracle_comparison': pvb.get('external_oracle_comparison', {'status': 'unavailable'}),
             }
         )
 
@@ -351,6 +352,7 @@ def calc_panchadhikari_year_lord(
         'muntha_sign': SIGNS[muntha_sign_idx],
         'is_daytime': is_daytime,
         'panchavargiya_engine': winner['panchavargiya_engine'],
+        'panchavargiya_selection_policy': 'native_components_external_observation_only',
         'candidates': candidates,
     }
 
@@ -1627,8 +1629,13 @@ def _resolve_year_lord_panchavargiya_score(
         tz=tz,
         ayanamsa_name=ayanamsa_name,
     )
-    if external is not None:
-        return external
+    # Upstream 0266b6ad: the annual strength table uses the same native profile;
+    # external availability must not silently change the year-lord selection
+    # method. PyJHora (research switch only) is an observation beside it.
+    comparison = (
+        {**external, 'comparison_role': 'observation_only_not_selection_input'}
+        if external is not None else {'status': 'unavailable'}
+    )
     if native_scores is None:
         # Upstream c7117f92 behaviour (dignity proxy); no product caller.
         proxy = _calc_panchavargiya_bala_for_planet(planet, lon_value)
@@ -1636,6 +1643,7 @@ def _resolve_year_lord_panchavargiya_score(
             'score': proxy['score'],
             'engine': 'native_proxy',
             'components': proxy['components'],
+            'external_oracle_comparison': comparison,
         }
     # BUG-1217: Tajika five-fold Panchavargiya; None when it cannot be computed.
     native = native_scores.get(planet) or {}
@@ -1646,6 +1654,7 @@ def _resolve_year_lord_panchavargiya_score(
         'engine': 'tajika_native_five_fold',
         'raw_total': native['raw_total'],
         'components': native['components'],
+        'external_oracle_comparison': comparison,
     }
 
 

scripts/tajika_year_lord.py

@@ -25,7 +25,10 @@ Q5) the candidates are compared by the Tajika five-fold Panchavargiya
 Drekkana, Navamsa; raw out of 80, score = raw / 4 out of 20;
 `engine: tajika_native_five_fold`); the dignity proxy no longer selects a year
 lord. Set JYOTISH_YEAR_LORD_PYJHORA_REFERENCE=1 to pass the annual JD and let
-the upstream PyJHora lookup run (research comparison only).
+the upstream PyJHora lookup run (research comparison only). Since upstream
+0266b6ad (2026-11-07 sync) that lookup never selects: it is attached to each
+candidate as `external_oracle_comparison` (`comparison_role:
+observation_only_not_selection_input`) and the native five-fold score decides.
 
 No stand-in year lord (BUG-1223, product owner 2026-10-04, aligned with
 upstream 03bea6ed `docs/research/tajika_shared_entrypoint_repair_2026_10_03.md`
@@ -140,6 +143,10 @@ def _candidate_list(candidates: List[Dict[str, Any]], winner: Optional[str]) ->
         "panchavargiya_score": row.get("panchavargiya_score"),
         "panchavargiya_raw_total": row.get("panchavargiya_raw_total"),
         "panchavargiya_engine": row.get("panchavargiya_engine"),
+        # Upstream 0266b6ad: the native components that produced the score;
+        # an external engine is an observation beside it, never the selector.
+        "panchavargiya_components": row.get("panchavargiya_components"),
+        "external_oracle_comparison": row.get("external_oracle_comparison"),
         "selected": row.get("planet") == winner,
     } for row in candidates if isinstance(row, dict)]
 

scripts/technique_gap_scanner.py

@@ -28,6 +28,7 @@ CALCULATION_READINESS = {
 }
 FAMILY_VALUE = {"dasha": 18, "kp": 17, "pravesha": 16, "sphuta": 12, "chakra": 11, "panchanga": 14}
 NON_IMPLEMENTATION_SCRIPTS = {
+    "scripts/audit_local_knowledge_copies.py",
     "scripts/book_rule_lineage.py",
     "scripts/technique_gap_scanner.py",
     "scripts/technique_source_adapters.py",

scripts/unified_consultation_orchestrator.py

@@ -788,9 +788,15 @@ class UnifiedConsultationOrchestrator:
     @staticmethod
     def _section(value: Any, source_path: str) -> dict[str, Any]:
         present = bool(value)
+        # Upstream ba8e36ec: a wrapped producer status is not a delivered section.
+        unavailable = isinstance(value, dict) and value.get("status") in {
+            "blocked", "missing", "error", "failed", "not_executed", "not_applicable",
+            "not_available_yet",
+        }
         return {
-            "status": "used" if present else "missing",
+            "status": "blocked" if unavailable else "used" if present else "missing",
             "source_path": source_path,
+            "claim_boundary": "payload_presence_not_independent_execution_verification",
         }
 
     @staticmethod
@@ -981,6 +987,7 @@ class UnifiedConsultationOrchestrator:
             # policy can require the second without the first standing in for it.
             "dasha_sub_periods": self._section(modules.get("dasha_sub_periods"), "modules.dasha_sub_periods"),
             "narayana_dasha": self._section(modules.get("narayana_dasha"), "modules.narayana_dasha"),
+            "transit": self._section(modules.get("transit_multi_reference"), "modules.transit_multi_reference"),
             "shadbala": self._section(modules.get("shadbala") or chart_data.get("shadbala"), "modules.shadbala"),
             "ashtakavarga": self._section(modules.get("ashtakavarga") or chart_data.get("ashtakavarga"), "modules.ashtakavarga"),
             "yogas": self._section(modules.get("yogas") or chart_data.get("yogas"), "modules.yogas"),
@@ -1045,7 +1052,7 @@ class UnifiedConsultationOrchestrator:
             spectrum if spectrum.get("status") == "used" else None,
             "modules.varga_spectrum",
         )
-        missing = [name for name, section in sections.items() if section.get("status") == "missing"]
+        missing = [name for name, section in sections.items() if section.get("status") in {"missing", "blocked"}]
         signals = chart_data.get("cross_system_signals")
         if not isinstance(signals, list):
             signals = modules.get("cross_system_signals") if isinstance(modules.get("cross_system_signals"), list) else []

skills/jaimini-timing/references/generated-usage-pack.md

@@ -17,9 +17,9 @@ Generated from ontology, family templates and public interface documentation. It
 - Use for: doctrine pack required before interpretation
 - Never use as: hand-written period dates, standalone event certainty
 - Required rule fields: seed, applicability, sequence, duration_model, birth_balance, child_period_model, year_definition
-- Local evidence hits: references/book_rule_technique_lineage.json, references/technique_registry.json, scripts/bhrigu_pada_dasha.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_pd_source_closure_ledger.py, scripts/chara_narayana_public_dated_examples_round2.py, scripts/chara_narayana_public_dated_examples_round3.py, scripts/chara_narayana_public_dated_examples_round4.py, scripts/chara_narayana_public_dated_examples_round5.py, scripts/chara_narayana_public_dated_examples_round7.py, scripts/chara_narayana_source_field_extraction.py, scripts/chara_narayana_source_rule_ledger.py, scripts/event_prediction_model.py, scripts/full_technique_invocation_matrix.py, scripts/jaimini.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_next_gap_closure_ledger.py, scripts/jyotish_public_gap_intake_round2.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/marriage_counting.py, scripts/narayana_continuation_source_sweep.py, scripts/pl9_core_table_extractor.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/reading_orchestrator.py, scripts/relocation_signal.py, scripts/specialized_indian_closure_review.py, scripts/sthira_brahma_selector_contract.py, scripts/technique_promotion_audit_varga_karaka.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/vedastro_official_capability_runner.py, scripts/vedastro_parity_matrix.py, scripts/vedastro_python_bridge.py, scripts/vedastro_service_adapter.py
-- Local implementation-candidate hits: scripts/bhrigu_pada_dasha.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_pd_source_closure_ledger.py, scripts/chara_narayana_public_dated_examples_round2.py, scripts/chara_narayana_public_dated_examples_round3.py, scripts/chara_narayana_public_dated_examples_round4.py, scripts/chara_narayana_public_dated_examples_round5.py, scripts/chara_narayana_public_dated_examples_round7.py, scripts/chara_narayana_source_field_extraction.py, scripts/chara_narayana_source_rule_ledger.py, scripts/event_prediction_model.py, scripts/full_technique_invocation_matrix.py, scripts/jaimini.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_next_gap_closure_ledger.py, scripts/jyotish_public_gap_intake_round2.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/marriage_counting.py, scripts/narayana_continuation_source_sweep.py, scripts/pl9_core_table_extractor.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/reading_orchestrator.py, scripts/relocation_signal.py, scripts/specialized_indian_closure_review.py, scripts/sthira_brahma_selector_contract.py, scripts/technique_promotion_audit_varga_karaka.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/vedastro_official_capability_runner.py, scripts/vedastro_parity_matrix.py, scripts/vedastro_python_bridge.py, scripts/vedastro_service_adapter.py
-- Book rule links: boney_major_life_events_composite_parashari_jaimini_timing
+- Local evidence hits: references/book_rule_technique_lineage.json, references/technique_registry.json, scripts/bhrigu_pada_dasha.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_pd_source_closure_ledger.py, scripts/chara_narayana_public_dated_examples_round2.py, scripts/chara_narayana_public_dated_examples_round3.py, scripts/chara_narayana_public_dated_examples_round4.py, scripts/chara_narayana_public_dated_examples_round5.py, scripts/chara_narayana_public_dated_examples_round7.py, scripts/chara_narayana_source_field_extraction.py, scripts/chara_narayana_source_rule_ledger.py, scripts/event_prediction_model.py, scripts/full_technique_invocation_matrix.py, scripts/jaimini.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_next_gap_closure_ledger.py, scripts/jyotish_public_gap_intake_round2.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/narayana_continuation_source_sweep.py, scripts/pl9_core_table_extractor.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/reading_orchestrator.py, scripts/relocation_signal.py, scripts/specialized_indian_closure_review.py, scripts/sthira_brahma_selector_contract.py, scripts/technique_promotion_audit_varga_karaka.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/vedastro_official_capability_runner.py, scripts/vedastro_parity_matrix.py, scripts/vedastro_python_bridge.py, scripts/vedastro_service_adapter.py
+- Local implementation-candidate hits: scripts/bhrigu_pada_dasha.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_pd_source_closure_ledger.py, scripts/chara_narayana_public_dated_examples_round2.py, scripts/chara_narayana_public_dated_examples_round3.py, scripts/chara_narayana_public_dated_examples_round4.py, scripts/chara_narayana_public_dated_examples_round5.py, scripts/chara_narayana_public_dated_examples_round7.py, scripts/chara_narayana_source_field_extraction.py, scripts/chara_narayana_source_rule_ledger.py, scripts/event_prediction_model.py, scripts/full_technique_invocation_matrix.py, scripts/jaimini.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_next_gap_closure_ledger.py, scripts/jyotish_public_gap_intake_round2.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/narayana_continuation_source_sweep.py, scripts/pl9_core_table_extractor.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/reading_orchestrator.py, scripts/relocation_signal.py, scripts/specialized_indian_closure_review.py, scripts/sthira_brahma_selector_contract.py, scripts/technique_promotion_audit_varga_karaka.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/vedastro_official_capability_runner.py, scripts/vedastro_parity_matrix.py, scripts/vedastro_python_bridge.py, scripts/vedastro_service_adapter.py
+- Book rule links: boney_major_life_events_composite_parashari_jaimini_timing, jaimini_seventh_from_karakamsha_marriage, jaimini_seventh_from_swamsha_marriage, spouse_meeting_place_via_seventh_from_venus
 - Book topic links: jaimini_chara_narayana
 - Documented external module: `jhora.horoscope.dhasa.raasi.chara`
 - Documented external methods: `get_dhasa_antardhasa(dob,tob,place,divisional_chart_factor=1,years=1,months=1,sixty_hours=1,include_antardasa=True)`
@@ -89,8 +89,8 @@ Generated from ontology, family templates and public interface documentation. It
 - Use for: doctrine pack required before interpretation
 - Never use as: hand-written period dates, standalone event certainty
 - Required rule fields: seed, applicability, sequence, duration_model, birth_balance, child_period_model, year_definition
-- Local evidence hits: references/book_rule_technique_lineage.json, references/technique_registry.json, scripts/active_rectification_candidates.py, scripts/active_rectification_event_engine.py, scripts/active_rectification_questions.py, scripts/buddhi_gati.py, scripts/candidate_multi_engine_observation_replay_2026_07_23.py, scripts/canonical_profile_regression.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_karan_singh_public_replay.py, scripts/chara_narayana_krymsk_d1_row_replay.py, scripts/chara_narayana_maneka_gandhi_md_table_replay.py, scripts/chara_narayana_public_dated_examples_replay.py, scripts/chara_narayana_rath_d16_table40_replay.py, scripts/chara_narayana_rath_vimsamsa_md_ad_replay.py, scripts/chara_narayana_rath_vimsamsa_runtime_probe.py, scripts/chara_narayana_rath_wadiyar_table25_replay.py, scripts/chara_narayana_round6_pd_order_reverse_probe.py, scripts/chara_narayana_round6_runtime_probe.py, scripts/chara_narayana_source_rule_ledger.py, scripts/chara_narayana_us_election_public_candidate_compatibility.py, scripts/chara_narayana_vajpayee_md_table_replay.py, scripts/cmd_narayana_dasha.py, scripts/commercial_astrology_e2e_acceptance_runner.py, scripts/current_blocked_optimization_audit.py, scripts/event_adjudication_receipt.py, scripts/evidence_labeled_reporting.py, scripts/extended_dashas.py, scripts/extract_research_export_sample.py, scripts/full_report_quality_gate.py, scripts/full_spectrum_invocation_plan.py, scripts/full_technique_invocation_matrix.py, scripts/global_top3_jyotish_audit.py, scripts/guided_topic_discovery.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_skill_architecture_registry.py, scripts/karan_singh_narayana_dated_event_stack_replay.py, scripts/karan_singh_narayana_duration_profile_arbitration.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/karan_singh_narayana_real_chart_duration_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/lagnamsaka_dasha.py, scripts/life_stage_hook.py, scripts/local_accepted_evidence_fixtures.py, scripts/narayana_dasha.py, scripts/narayana_direction_closure_packet.py, scripts/narayana_pl9_profile_probe.py, scripts/narayana_variant_regression.py, scripts/padanadhamsa.py, scripts/pl9_full_parity_dashboard.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/profile_aware_benchmark_boundary_dashboard.py, scripts/public_oracle_replay.py, scripts/public_real_case_benchmark.py, scripts/real_case_website_e2e_eval.py, scripts/rectification_report_replay.py, scripts/sanjay_rath_narayana_book_ledger.py, scripts/specialized_dasha_external_replay.py, scripts/specialized_dasha_router.py, scripts/sudarsana_dasha.py, scripts/sudasa.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/trikona_dasha.py, scripts/trikona_raman.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/varnada_dasha.py, scripts/varsha_narayana.py, scripts/vedastro_evidence_orchestrator.py, scripts/vedastro_parity_matrix.py
-- Local implementation-candidate hits: scripts/active_rectification_candidates.py, scripts/active_rectification_event_engine.py, scripts/active_rectification_questions.py, scripts/buddhi_gati.py, scripts/candidate_multi_engine_observation_replay_2026_07_23.py, scripts/canonical_profile_regression.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_karan_singh_public_replay.py, scripts/chara_narayana_krymsk_d1_row_replay.py, scripts/chara_narayana_maneka_gandhi_md_table_replay.py, scripts/chara_narayana_public_dated_examples_replay.py, scripts/chara_narayana_rath_d16_table40_replay.py, scripts/chara_narayana_rath_vimsamsa_md_ad_replay.py, scripts/chara_narayana_rath_vimsamsa_runtime_probe.py, scripts/chara_narayana_rath_wadiyar_table25_replay.py, scripts/chara_narayana_round6_pd_order_reverse_probe.py, scripts/chara_narayana_round6_runtime_probe.py, scripts/chara_narayana_source_rule_ledger.py, scripts/chara_narayana_us_election_public_candidate_compatibility.py, scripts/chara_narayana_vajpayee_md_table_replay.py, scripts/cmd_narayana_dasha.py, scripts/commercial_astrology_e2e_acceptance_runner.py, scripts/current_blocked_optimization_audit.py, scripts/event_adjudication_receipt.py, scripts/evidence_labeled_reporting.py, scripts/extended_dashas.py, scripts/extract_research_export_sample.py, scripts/full_report_quality_gate.py, scripts/full_spectrum_invocation_plan.py, scripts/full_technique_invocation_matrix.py, scripts/global_top3_jyotish_audit.py, scripts/guided_topic_discovery.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_skill_architecture_registry.py, scripts/karan_singh_narayana_dated_event_stack_replay.py, scripts/karan_singh_narayana_duration_profile_arbitration.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/karan_singh_narayana_real_chart_duration_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/lagnamsaka_dasha.py, scripts/life_stage_hook.py, scripts/local_accepted_evidence_fixtures.py, scripts/narayana_dasha.py, scripts/narayana_direction_closure_packet.py, scripts/narayana_pl9_profile_probe.py, scripts/narayana_variant_regression.py, scripts/padanadhamsa.py, scripts/pl9_full_parity_dashboard.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/profile_aware_benchmark_boundary_dashboard.py, scripts/public_oracle_replay.py, scripts/public_real_case_benchmark.py, scripts/real_case_website_e2e_eval.py, scripts/rectification_report_replay.py, scripts/sanjay_rath_narayana_book_ledger.py, scripts/specialized_dasha_external_replay.py, scripts/specialized_dasha_router.py, scripts/sudarsana_dasha.py, scripts/sudasa.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/trikona_dasha.py, scripts/trikona_raman.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/varnada_dasha.py, scripts/varsha_narayana.py, scripts/vedastro_evidence_orchestrator.py, scripts/vedastro_parity_matrix.py
+- Local evidence hits: references/book_rule_technique_lineage.json, references/technique_registry.json, scripts/active_rectification_candidates.py, scripts/active_rectification_event_engine.py, scripts/active_rectification_questions.py, scripts/buddhi_gati.py, scripts/candidate_multi_engine_observation_replay_2026_07_23.py, scripts/canonical_profile_regression.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_karan_singh_public_replay.py, scripts/chara_narayana_krymsk_d1_row_replay.py, scripts/chara_narayana_maneka_gandhi_md_table_replay.py, scripts/chara_narayana_public_dated_examples_replay.py, scripts/chara_narayana_rath_d16_table40_replay.py, scripts/chara_narayana_rath_vimsamsa_md_ad_replay.py, scripts/chara_narayana_rath_vimsamsa_runtime_probe.py, scripts/chara_narayana_rath_wadiyar_table25_replay.py, scripts/chara_narayana_round6_pd_order_reverse_probe.py, scripts/chara_narayana_round6_runtime_probe.py, scripts/chara_narayana_source_rule_ledger.py, scripts/chara_narayana_us_election_public_candidate_compatibility.py, scripts/chara_narayana_vajpayee_md_table_replay.py, scripts/cmd_narayana_dasha.py, scripts/commercial_astrology_e2e_acceptance_runner.py, scripts/current_blocked_optimization_audit.py, scripts/event_adjudication_receipt.py, scripts/evidence_labeled_reporting.py, scripts/extended_dashas.py, scripts/extract_research_export_sample.py, scripts/finance_astrology_support_review.py, scripts/full_report_quality_gate.py, scripts/full_spectrum_invocation_plan.py, scripts/full_technique_invocation_matrix.py, scripts/global_top3_jyotish_audit.py, scripts/goel_jaimini_strength.py, scripts/guided_topic_discovery.py, scripts/jaimini.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_skill_architecture_registry.py, scripts/karan_singh_narayana_dated_event_stack_replay.py, scripts/karan_singh_narayana_duration_profile_arbitration.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/karan_singh_narayana_real_chart_duration_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/lagnamsaka_dasha.py, scripts/life_stage_hook.py, scripts/local_accepted_evidence_fixtures.py, scripts/narayana_dasha.py, scripts/narayana_direction_closure_packet.py, scripts/narayana_pl9_profile_probe.py, scripts/narayana_variant_regression.py, scripts/padanadhamsa.py, scripts/pl9_full_parity_dashboard.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/profile_aware_benchmark_boundary_dashboard.py, scripts/public_oracle_replay.py, scripts/public_real_case_benchmark.py, scripts/real_case_website_e2e_eval.py, scripts/rectification_report_replay.py, scripts/sanjay_rath_narayana_book_ledger.py, scripts/specialized_dasha_external_replay.py, scripts/specialized_dasha_router.py, scripts/sudarsana_dasha.py, scripts/sudasa.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/trikona_dasha.py, scripts/trikona_raman.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/varnada_dasha.py, scripts/varsha_narayana.py, scripts/vedastro_evidence_orchestrator.py, scripts/vedastro_parity_matrix.py
+- Local implementation-candidate hits: scripts/active_rectification_candidates.py, scripts/active_rectification_event_engine.py, scripts/active_rectification_questions.py, scripts/buddhi_gati.py, scripts/candidate_multi_engine_observation_replay_2026_07_23.py, scripts/canonical_profile_regression.py, scripts/chara_narayana_book_golden_cases.py, scripts/chara_narayana_book_runtime_replay.py, scripts/chara_narayana_karan_singh_public_replay.py, scripts/chara_narayana_krymsk_d1_row_replay.py, scripts/chara_narayana_maneka_gandhi_md_table_replay.py, scripts/chara_narayana_public_dated_examples_replay.py, scripts/chara_narayana_rath_d16_table40_replay.py, scripts/chara_narayana_rath_vimsamsa_md_ad_replay.py, scripts/chara_narayana_rath_vimsamsa_runtime_probe.py, scripts/chara_narayana_rath_wadiyar_table25_replay.py, scripts/chara_narayana_round6_pd_order_reverse_probe.py, scripts/chara_narayana_round6_runtime_probe.py, scripts/chara_narayana_source_rule_ledger.py, scripts/chara_narayana_us_election_public_candidate_compatibility.py, scripts/chara_narayana_vajpayee_md_table_replay.py, scripts/cmd_narayana_dasha.py, scripts/commercial_astrology_e2e_acceptance_runner.py, scripts/current_blocked_optimization_audit.py, scripts/event_adjudication_receipt.py, scripts/evidence_labeled_reporting.py, scripts/extended_dashas.py, scripts/extract_research_export_sample.py, scripts/finance_astrology_support_review.py, scripts/full_report_quality_gate.py, scripts/full_spectrum_invocation_plan.py, scripts/full_technique_invocation_matrix.py, scripts/global_top3_jyotish_audit.py, scripts/goel_jaimini_strength.py, scripts/guided_topic_discovery.py, scripts/jaimini.py, scripts/jyotish_api_server.py, scripts/jyotish_engine.py, scripts/jyotish_skill_architecture_registry.py, scripts/karan_singh_narayana_dated_event_stack_replay.py, scripts/karan_singh_narayana_duration_profile_arbitration.py, scripts/karan_singh_narayana_event_pd_replay.py, scripts/karan_singh_narayana_real_chart_duration_replay.py, scripts/kn_rao_bhrigu_aggregation_ledger.py, scripts/lagnamsaka_dasha.py, scripts/life_stage_hook.py, scripts/local_accepted_evidence_fixtures.py, scripts/narayana_dasha.py, scripts/narayana_direction_closure_packet.py, scripts/narayana_pl9_profile_probe.py, scripts/narayana_variant_regression.py, scripts/padanadhamsa.py, scripts/pl9_full_parity_dashboard.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/profile_aware_benchmark_boundary_dashboard.py, scripts/public_oracle_replay.py, scripts/public_real_case_benchmark.py, scripts/real_case_website_e2e_eval.py, scripts/rectification_report_replay.py, scripts/sanjay_rath_narayana_book_ledger.py, scripts/specialized_dasha_external_replay.py, scripts/specialized_dasha_router.py, scripts/sudarsana_dasha.py, scripts/sudasa.py, scripts/technique_registry.py, scripts/timing_evidence_packets.py, scripts/trikona_dasha.py, scripts/trikona_raman.py, scripts/unified_calculation_archive.py, scripts/unified_consultation_orchestrator.py, scripts/varnada_dasha.py, scripts/varsha_narayana.py, scripts/vedastro_evidence_orchestrator.py, scripts/vedastro_parity_matrix.py
 - Book rule links: web_pvr_varsha_narayana_ch30_4
 - Book topic links: jaimini_chara_narayana
 - Documented external module: `jhora.horoscope.dhasa.raasi.narayana`
@@ -387,12 +387,12 @@ Generated from ontology, family templates and public interface documentation. It
 - Canonical ID: `niryaana_shoola_dasha`
 - Legacy family priority (not scoped development count): P0 / 88
 - Next work: complete_variant_and_report_contract
-- Remaining requirements: See missing dimensions and source-specific usage notes
+- Remaining requirements: source-backed AD/PD rule and row-level replay; independent same-profile MD case; no predictive or global admission
 - Native producer: `scripts.niryaana_shoola_dasha.calculate_niryaana_shoola_dasha`
 - Producer maturity: `source_bounded_wired`
-- Producer verification scope: stronger Lagna/seventh selection, explicit tie-break, named Goel/Raman/PyJHora duration profiles and MD/AD/PD boundaries
+- Producer verification scope: PVR second/eighth ayur-strength selection with unresolved ties blocked; movable/fixed/dual 7/8/9 calendar-year MD; external observation separate
 - Report paths: `jyotish_engine.worksheets.timing_and_predictive_systems.dasha_master_pack.families.niryaana_shoola`, `references/oracle/pl9_p92_p103_field_audit_2026_09_11.json`
-- Variant profiles: `niryaana_shoola_goel_profile` (adopted_source_bounded), `niryaana_shoola_raman_profile` (optional_source_profile), `niryaana_shoola_pyjhora_observation_profile` (external_observation_only)
+- Variant profiles: `pvr_niryaana_shoola_v1` (adopted_source_bounded), `niryaana_shoola_pyjhora_observation_profile` (external_observation_only)
 - Required inputs: birth_datetime, birth_location, ayanamsa, rule_profile
 - Use for: doctrine pack required before interpretation
 - Never use as: hand-written period dates, standalone event certainty
@@ -445,8 +445,8 @@ Generated from ontology, family templates and public interface documentation. It
 - Use for: doctrine pack required before interpretation
 - Never use as: hand-written period dates, standalone event certainty
 - Required rule fields: seed, applicability, sequence, duration_model, birth_balance, child_period_model, year_definition
-- Local evidence hits: scripts/extended_dashas.py, scripts/jyotish_engine.py, scripts/niryaana_shoola_dasha.py, scripts/niryaana_shoola_family_contract.py, scripts/pl9_named_dasha_row_replay.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/shoola_dasha.py, scripts/shoola_family_contract.py
-- Local implementation-candidate hits: scripts/extended_dashas.py, scripts/jyotish_engine.py, scripts/niryaana_shoola_dasha.py, scripts/niryaana_shoola_family_contract.py, scripts/pl9_named_dasha_row_replay.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/shoola_dasha.py, scripts/shoola_family_contract.py
+- Local evidence hits: scripts/dasha_profile_arbitration.py, scripts/extended_dashas.py, scripts/jyotish_engine.py, scripts/niryaana_shoola_dasha.py, scripts/niryaana_shoola_family_contract.py, scripts/pl9_named_dasha_row_replay.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/shoola_dasha.py, scripts/shoola_family_contract.py
+- Local implementation-candidate hits: scripts/dasha_profile_arbitration.py, scripts/extended_dashas.py, scripts/jyotish_engine.py, scripts/niryaana_shoola_dasha.py, scripts/niryaana_shoola_family_contract.py, scripts/pl9_named_dasha_row_replay.py, scripts/pl9_p92_p103_field_audit.py, scripts/pl9_report_corpus_audit.py, scripts/professional_parity_closure.py, scripts/shoola_dasha.py, scripts/shoola_family_contract.py
 - Book rule links: not mapped
 - Book topic links: not mapped
 - Documented external module: `jhora.horoscope.dhasa.raasi.shoola`

skills/specialized-jyotish/SKILL.md

@@ -107,6 +107,8 @@ Sudarsana Dasha 已有两个独立的原生太阳弧 MD/AD/PD profile，见
 [原生与外部用法包](references/sudarsana-dasha-usage.md)。教材从父星座起子期，2004研究从父宫主本命落座起；必须显式选择，不混合。外部固定年观察和旧占位拒绝保持独立。静态 Sudarshana 三参考盘已可调用
 [严格结构用法包](references/sudarshana-structure-usage.md)，不要混同二者。
 Chandra Kala Nadi 已有[非均匀具名分段及误差候选入口](references/chandra-kala-nadi-usage.md)：Patel十六分盘边界并集，保留均分对照profile、三类星座编号和几何子段；不是D150落座或命运判断。
+
+Meena Jeeva/Sareera 结构入口：`jyotish_engine.py nadi-stellar-roles --request <local.json>`，复用 `nakshatra_advanced.calculate_stellar_jeeva_sareera`。采用具名的原书 printed-p89 步骤；缺星宿方向力或交点尊贵口径时保留 blocked，不得代入 Shadbala。详见 `docs/research/stellar_jeeva_sareera_2026_11_07.md`；尚不启用预测评分或客户导出。
 这些条目可以用于方法比较或缺口研究，但必须保留原始状态，不得写入确定性
 应期或客户报告。
 

skills/specialized-jyotish/references/generated-usage-pack.md

@@ -557,8 +557,8 @@ Static entrypoint presence is not a runtime claim: not_run_by_scanner. Original
 - Use for: named nonuniform Nadi amsa lookup, geometric subparts and uncertainty candidates
 - Never use as: generic equal D150 substitution, standalone predictive or rectification verdict
 - Required rule fields: boundary union, sign modality numbering, named source list, half-open endpoints, uncertainty and geometric subparts
-- Local evidence hits: references/book_rule_packets.json, references/book_rule_technique_lineage.json, references/internet_technique_gap_registry.json, scripts/chandra_kala_nadi.py, scripts/nadi_book_extraction_workflow.py, scripts/nadi_knowledge_extraction_plan.py
-- Local implementation-candidate hits: scripts/chandra_kala_nadi.py, scripts/nadi_book_extraction_workflow.py, scripts/nadi_knowledge_extraction_plan.py
+- Local evidence hits: references/book_rule_packets.json, references/book_rule_technique_lineage.json, references/internet_technique_gap_registry.json, scripts/audit_local_knowledge_copies.py, scripts/chandra_kala_nadi.py, scripts/nadi_book_extraction_workflow.py, scripts/nadi_knowledge_extraction_plan.py, scripts/nadi_leaf_assistant.py
+- Local implementation-candidate hits: scripts/chandra_kala_nadi.py, scripts/nadi_book_extraction_workflow.py, scripts/nadi_knowledge_extraction_plan.py, scripts/nadi_leaf_assistant.py
 - Book rule links: patel_nadi_ch1_ch2_named_nonuniform
 - Book topic links: nadi
 - Documented external module: `not documented`
@@ -1073,7 +1073,7 @@ Static entrypoint presence is not a runtime claim: not_run_by_scanner. Original
 - Use for: source-labelled sensitive-point sums and classical_local D9 parity
 - Never use as: fertility diagnosis, medical probability, event timing or outcome verdict
 - Required rule fields: formula, point_names, normalization, gulika_or_mandi_convention, interpretation_scope
-- Local evidence hits: scripts/beeja_kshetra_sphuta.py
+- Local evidence hits: scripts/audit_local_knowledge_copies.py, scripts/beeja_kshetra_sphuta.py
 - Local implementation-candidate hits: scripts/beeja_kshetra_sphuta.py
 - Book rule links: not mapped
 - Book topic links: not mapped

tests/test_bhrigu_bcp_observation_date.py

@@ -0,0 +1,45 @@
+"""Ported from upstream 8813c851 (astrologer branch d09feab7, 2026-11-07 sync):
+BCP is observed at an explicit target date; the birth epoch is only a labelled default."""
+import ast
+from pathlib import Path
+
+
+def test_bcp_report_uses_explicit_target_epoch_and_labels_birth_default():
+    from scripts.bhrigu_pada_dasha import bhrigu_pada_dasha_full_report
+    natal = bhrigu_pada_dasha_full_report(10., 2451545.)
+    later = bhrigu_pada_dasha_full_report(10., 2451545., target_date_jd=2451910.25)
+    assert natal['bcp_cycle']['years_elapsed'] == 0
+    assert natal['bcp_reference']['scope'] == 'birth_epoch_default'
+    assert later['bcp_cycle']['years_elapsed'] == 1
+    assert later['bcp_cycle']['bcp_longitude'] == 40.
+    assert later['bcp_reference'] == {'target_jd': 2451910.25, 'scope': 'explicit_target'}
+    assert later['dasha_sequence'] == natal['dasha_sequence']
+
+
+def test_full_reading_passes_the_reading_date_to_bcp(monkeypatch):
+    import sys
+    from types import SimpleNamespace
+    from datetime import datetime
+    import swisseph as swe
+    sys.path.insert(0, str(Path(__file__).resolve().parents[1] / 'scripts'))
+    import bhrigu_pada_dasha
+    calls = []
+
+    def calculate(moon, jd, **kwargs):
+        calls.append((moon, jd, kwargs.get('target_date_jd')))
+        return {'dasha_sequence': []}
+    monkeypatch.setattr(bhrigu_pada_dasha, 'bhrigu_pada_dasha_full_report', calculate)
+    tree = ast.parse((Path(__file__).resolve().parents[1] / 'scripts/jyotish_engine.py').read_text())
+    blocks = [n for n in ast.walk(tree) if isinstance(n, ast.Try) and any(
+        isinstance(item, ast.ImportFrom) and item.module == 'bhrigu_pada_dasha' for item in n.body)]
+    assert len(blocks) == 1
+    env = {'report': {'modules': {}, 'errors': []}, 'planet_lons': {'Moon': 10.}, 'jd': 2451545.,
+           '_varga_planet_lons': lambda value: {}, 'SIGNS': [], 'SIGN_LORDS': {},
+           'args': SimpleNamespace(transit_date='2001-01-01', today='2000-01-01', tz=0),
+           'swe': swe, 'datetime': datetime}
+    exec(compile(ast.Module(body=blocks, type_ignores=[]), '<bhrigu-full-reading>', 'exec'), env)
+    assert calls == [(10., 2451545., 2451911.)]
+    assert not env['report']['errors']
+    module = env['report']['modules']['bhrigu_pada_dasha']
+    assert module['status'] == 'parameter_sensitive'
+    assert module['bcp_reference_date'] == '2001-01-01'

tests/test_dispositor_chain_locations.py

@@ -0,0 +1,24 @@
+import pytest
+
+from scripts.jyotish_engine import calc_dispositor_chain
+
+
+def test_dispositor_location_is_not_the_owned_sign():
+    chain = calc_dispositor_chain("Mercury", {
+        "Mercury": {"sign": "Leo"}, "Sun": {"sign": "Cancer"},
+        "Moon": {"sign": "Cancer"},
+    })
+    assert [(row["planet"], row["dispositor"], row["dispositor_sign"]) for row in chain] == [
+        ("Mercury", "Sun", "Cancer"), ("Sun", "Moon", "Cancer"), ("Moon", "Moon", "Cancer")]
+
+
+@pytest.mark.parametrize("lord", [None, {}, "unavailable"])
+def test_missing_dispositor_location_is_not_invented(lord):
+    chain = calc_dispositor_chain("Mercury", {"Mercury": {"sign": "Leo"}, "Sun": lord})
+    assert len(chain) == 1
+    assert chain[0]["dispositor_sign"] is None
+
+
+def test_exchange_keeps_both_actual_locations_without_infinite_loop():
+    chain = calc_dispositor_chain("Mars", {"Mars": {"sign": "Taurus"}, "Venus": {"sign": "Aries"}})
+    assert [r["dispositor_sign"] for r in chain] == ["Aries", "Taurus"]

tests/test_finance_delivery_integrity.py

@@ -0,0 +1,78 @@
+from copy import deepcopy
+import pytest
+
+from scripts.finance_astrology_support_review import (
+    build_finance_astrology_support_review, build_finance_delivery_inventory,
+)
+from scripts.full_report_quality_gate import evaluate_evidence_claims, evaluate_full_report
+from scripts.unified_consultation_orchestrator import UnifiedConsultationOrchestrator
+
+
+@pytest.mark.parametrize("status", ["blocked", "missing", "error", "failed",
+                                   "not_executed", "not_applicable", "not_available_yet"])
+def test_unavailable_narayana_cannot_become_available_by_wrapping(status):
+    packet = UnifiedConsultationOrchestrator().machine_evidence_packet(
+        chart={"modules": {"narayana_dasha": {"status": status, "reason": "fixture"}}},
+        route_packet={"question_type": "finance"})
+    review = build_finance_astrology_support_review(
+        route_packet={"question_type": "finance"}, machine_evidence_packet=packet,
+        runtime_evidence_log={})
+    assert review["coverage"]["narayana"] == "blocked"
+    assert "narayana_dasha" in packet["missing_sections"]
+
+
+
+def test_actual_native_sections_reach_finance_review():
+    chart = {"modules": {
+        "varga_full": {"D11_Rudramsa": {"fixture": True}, "D4_Turyamsa": {"fixture": True}},
+        "narayana_dasha": {"periods": [{"sign": "Leo"}]},
+        "transit_multi_reference": {"status": "blocked"},
+    }}
+    packet = UnifiedConsultationOrchestrator().machine_evidence_packet(
+        chart=chart, route_packet={"question_type": "finance"})
+    assert packet["sections"]["D11"]["status"] == "used"
+    assert packet["sections"]["D4"]["status"] == "used"
+    review = build_finance_astrology_support_review(
+        route_packet={"question_type": "finance"}, machine_evidence_packet=packet,
+        runtime_evidence_log={})
+    assert review["coverage"]["narayana"] == "present"
+    assert review["coverage"]["transit"] == "blocked"
+    assert review["readiness"] == "incomplete"
+
+
+def test_arbitration_is_not_a_narayana_execution_receipt():
+    review = build_finance_astrology_support_review(
+        route_packet={"question_type": "finance"}, machine_evidence_packet={},
+        runtime_evidence_log={"cross_system_arbitration": {"status": "used"}})
+    assert review["coverage"]["narayana"] == "missing"
+    assert review["audit_rows"][0]["effect_on_confidence"] == "incomplete"
+
+
+def test_delivery_preserves_raw_without_promoting_or_mutating():
+    modules = {"argala": {"status": "blocked", "candidate": [1]},
+               "dispositor_chains": {"chain": ["Mercury", "Jupiter"]}}
+    original = deepcopy(modules)
+    inventory = build_finance_delivery_inventory(modules)
+    rows = {r["technique"]: r for r in inventory["rows"]}
+    assert rows["argala"]["delivery_status"] == "producer_status_blocked"
+    assert rows["sudasa"]["delivery_status"] == "not_delivered"
+    assert rows["dispositor_chains"]["execution_status"] == "not_verified_by_inventory"
+    rows["argala"]["raw"]["candidate"].append(2)
+    assert modules == original
+
+
+def test_conflicting_claim_binding_blocks_gate():
+    packet = {"points": {"A11": "Leo"}, "evidence_claims": [
+        {"path": ["points", "A11"], "value": "Taurus"}]}
+    assert evaluate_evidence_claims(packet)["errors"] == ["claim_0:value_mismatch"]
+    assert "evidence_claim_bindings_invalid" in evaluate_full_report(packet)["blocking_reasons"]
+    packet["evidence_claims"][0]["value"] = "Leo"
+    assert evaluate_evidence_claims(packet)["status"] == "bindings_match"
+
+
+def test_missing_and_empty_bindings_never_claim_verification():
+    assert evaluate_evidence_claims({"evidence_claims": []})["status"] == "not_supplied"
+    assert evaluate_evidence_claims({})["status"] == "not_supplied"
+    for path, value in [(["absent"], 0), (["evidence_claims"], []), (["zero"], False)]:
+        packet = {"zero": 0, "evidence_claims": [{"path": path, "value": value}]}
+        assert evaluate_evidence_claims(packet)["status"] == "blocked"

tests/test_mcp_strict_workflow_finance.py

@@ -3,6 +3,8 @@
 
 from __future__ import annotations
 
+import pytest
+
 import jyotish_engine
 
 from mcp_server import (
@@ -518,7 +520,10 @@ def test_finance_sodhita_and_kakshya_friction_reduce_score_without_forcing_label
 
     assert base["dominant_label"] == "public_wealth_status"
     assert weighted["dominant_label"] == "public_wealth_status"
-    assert weighted["score"] == base["score"] - 4
+    # 原值: base - 4（Sodhita -2 + Kakshya -2）; 新值: base - 2，且无 sodhita_wealth_friction;
+    # 原因: 产品 2026-11-07 同步占星师工作分支 d09feab7（a5b75886 Sodhita 无已裁定财富阈值，不再投票）。
+    assert weighted["score"] == base["score"] - 2
+    assert "sodhita_wealth_friction" not in weighted["secondary_context"]
 
 
 def test_collect_strict_evidence_finance_derives_wealth_promise_from_dhana_yogas() -> None:
@@ -763,7 +768,7 @@ def test_collect_strict_evidence_finance_adds_pav_and_kakshya_support_as_seconda
     assert "kakshya_finance_support" in strict["event_judgement"]["secondary_context"]
 
 
-def test_collect_strict_evidence_finance_flags_sodhita_wealth_friction() -> None:
+def test_collect_strict_evidence_retains_unproven_sodhita_without_friction() -> None:
     result = {
         "modules": {
             "chart": {"ascendant": {"sign": "Aries"}},
@@ -814,14 +819,20 @@ def test_collect_strict_evidence_finance_flags_sodhita_wealth_friction() -> None
 
     strict = _collect_strict_evidence("finance", result)
 
+    # 原值: level obstructive + signals [sodhita_wealth_friction]，且进入 secondary_context;
+    # 新值: level none、signals []、status method_unverified、prediction_scoring_allowed False;
+    # 原因: 产品 2026-11-07 同步占星师工作分支 d09feab7（a5b75886）。
     assert strict["present_evidence"]["sodhita_finance_support"] == {
-        "level": "obstructive",
+        "level": "none",
         "source": "ashtakavarga_sodhita_bridge_v1",
-        "signals": ["sodhita_wealth_friction"],
+        "signals": [],
         "target_houses": [2, 11],
         "raw_scores": {"2": 18, "11": 17},
+        "status": "method_unverified",
+        "prediction_scoring_allowed": False,
+        "reason": "unadjudicated_contribution_subtraction_not_wealth_evidence",
     }
-    assert "sodhita_wealth_friction" in strict["event_judgement"]["secondary_context"]
+    assert "sodhita_wealth_friction" not in strict["event_judgement"]["secondary_context"]
 
 
 def test_collect_strict_evidence_finance_flags_kakshya_friction_as_secondary_only() -> None:
@@ -1494,3 +1505,79 @@ def test_finance_narrative_payload_forces_monthly_adjudication_layers_into_final
     assert any("月度主状态" in item for item in payload["strengths"])
     assert any("阻力来源" in item for item in payload["risks"])
     assert "时间置信度" in payload["markdown"]
+
+
+# Ported from upstream 0266b6ad / 8c4bff8a / a5b75886 (d09feab7 branch).
+@pytest.mark.parametrize('metadata', [
+    {},
+    {'prediction_scoring_allowed': True},
+    {'method_id': 'unspecified_historical_method'},
+    {'method_id': 'unregistered_method', 'prediction_scoring_allowed': True},
+    {'prediction_scoring_allowed': False},
+    {'method': 'Sodhita Ashtakavarga (BPHS标准)'},
+    {'status': 'executed', 'method': 'Trikona Shodhana -> Ekadhipatya Shodhana'},
+])
+def test_legacy_sodhita_retains_raw_values_without_wealth_penalty(metadata):
+    from mcp_server import _derive_sodhita_finance_support
+    result = _derive_sodhita_finance_support({'sodhita': {
+        **metadata, 'sodhita_sav': {'assessment': [
+            {'sign': 'Taurus', 'score': 5}, {'sign': 'Aquarius', 'score': 6}]}}}, 'Aries')
+    assert result['raw_scores'] == {'2': 5, '11': 6}
+    assert result['level'] == 'none'
+    assert result['signals'] == []
+    assert result['prediction_scoring_allowed'] is False
+
+
+@pytest.mark.parametrize('metadata', [
+    {},
+    {'prediction_scoring_allowed': True},
+    {'method_id': 'unspecified_historical_method'},
+    {'method_id': 'unregistered_method', 'prediction_scoring_allowed': True},
+    {'prediction_scoring_allowed': False},
+    {'status': 'legacy_reference_only'},
+    {'status': 'reference_only'},
+    {'status': 'blocked'},
+    {'status': 'incomplete'},
+    {'status': 'not_available_yet'},
+    {'status': 'unavailable'},
+    {'method_id': 'legacy_malefic_contribution_subtraction_v1'},
+    {'method': 'Sodhita Ashtakavarga (BPHS标准)'},
+])
+def test_cached_sodhita_restrictions_survive_finance_adjudication(metadata):
+    from copy import deepcopy
+    present = {'vimshottari_current': {'mahadasha': 'Venus'}}
+    baseline = _derive_event_judgement('finance', present, [])
+    present['sodhita_finance_support'] = {
+        **metadata, 'level': 'obstructive',
+        'signals': ['sodhita_wealth_friction'], 'raw_scores': {'2': 5, '11': 6},
+    }
+    original = deepcopy(present)
+    assert _derive_event_judgement('finance', present, []) == baseline
+    assert present == original
+
+
+@pytest.mark.parametrize('status', ['blocked', 'reference_only', 'unavailable'])
+def test_sodhita_producer_restriction_survives_bridge(status):
+    from mcp_server import _derive_sodhita_finance_support
+    result = _derive_sodhita_finance_support({'sodhita': {
+        'status': status, 'sodhita_sav': {'assessment': [
+            {'sign': 'Taurus', 'score': 5}, {'sign': 'Aquarius', 'score': 6}]}}}, 'Aries')
+    assert result['raw_scores'] == {'2': 5, '11': 6}
+    assert result['status'] == status
+    assert result['prediction_scoring_allowed'] is False
+    assert result['level'] == 'none'
+    assert result['signals'] == []
+
+
+# Ported from upstream ba8e36ec.
+def test_optional_delivery_inventory_does_not_vote_or_fill_required_evidence():
+    baseline = _collect_strict_evidence("finance", {"modules": {}})
+    result = _collect_strict_evidence("finance", {"modules": {
+        "argala": {"status": "blocked", "candidate": "retained"},
+        "sudasa": {"periods": [{"sign": "Leo"}]},
+    }})
+    rows = {r["technique"]: r for r in result["finance_delivery_inventory"]["rows"]}
+    assert rows["argala"]["raw"]["candidate"] == "retained"
+    assert rows["sudasa"]["delivery_status"] == "payload_delivered"
+    assert result["event_judgement"] == baseline["event_judgement"]
+    assert result["missing_evidence"] == baseline["missing_evidence"]

tests/test_stellar_jeeva_sareera.py

@@ -0,0 +1,117 @@
+"""Synthetic structural cases; no personal data or predictive validation."""
+import json
+from pathlib import Path
+import subprocess
+import sys
+
+import pytest
+
+from scripts.nakshatra_advanced import calculate_stellar_jeeva_sareera
+
+
+BASE = dict(Sun=125., Moon=45., Mars=215., Mercury=75.,
+            Jupiter=255., Venus=185., Saturn=305., Rahu=10., Ketu=190.)
+
+
+def run(lord, positions=None, **kwargs):
+    return calculate_stellar_jeeva_sareera(
+        positions or BASE, bhava_lord=lord, ayanamsa="synthetic",
+        node_mode="mean", **kwargs)
+
+
+def test_own_star_uses_sign_lord_instead_of_self_loop():
+    result = run("Moon")
+    assert (result["jeeva"], result["sareera"]) == ("Moon", "Venus")
+    assert result["prediction_scoring_allowed"] is False
+
+
+def test_own_star_and_own_sign_retains_both():
+    result = run("Sun", dict(BASE, Sun=148.))
+    assert (result["jeeva"], result["sareera"]) == ("Sun", "Sun")
+
+
+def test_owner_beats_exalted_companion():
+    result = run("Mercury", dict(BASE, Mercury=20., Saturn=200.))
+    assert result["jeeva"] == "Venus"
+
+
+def test_original_saturn_anuradha_retains_against_owner():
+    result = run("Saturn", dict(BASE, Saturn=220.))
+    assert result["jeeva"] == "Saturn"
+
+
+def test_missing_stellar_digbala_is_not_false():
+    result = run("Moon", dict(BASE, Moon=275., Sun=65., Mercury=100., Jupiter=70.))
+    assert result["status"] == "blocked"
+    assert result["jeeva"] is None
+    assert "stellar_digbala" in result["trace"][0]["reason"]
+
+
+def test_explicit_stellar_digbala_transfers_then_recomputes_sareera():
+    result = run("Moon", dict(BASE, Moon=275., Sun=65., Mercury=100., Jupiter=70.),
+                 stellar_digbala={"Sun": False, "Jupiter": True})
+    assert result["jeeva"] == "Jupiter"
+    assert result["sareera"] == "Rahu"
+
+
+@pytest.mark.parametrize("value", [float("nan"), float("inf"), True, "45"])
+def test_invalid_longitude_rejected(value):
+    with pytest.raises(ValueError):
+        run("Moon", dict(BASE, Moon=value))
+
+
+def test_missing_planet_cannot_hide_a_companion():
+    with pytest.raises(ValueError):
+        run("Moon", {k: v for k, v in BASE.items() if k != "Ketu"})
+
+
+def test_numeric_shadbala_cannot_masquerade_as_stellar_digbala():
+    with pytest.raises(ValueError):
+        run("Moon", stellar_digbala={"Sun": 60})
+
+
+def test_exalted_companion_replaces_seed_without_strength_scores():
+    result = run("Moon", dict(BASE, Moon=275., Sun=332., Venus=355.))
+    assert result["jeeva"] == "Venus"
+    assert result["trace"][0]["reason"] == "exalted"
+
+
+def test_unselected_saturn_does_not_override_owner_under_p89_profile():
+    result = run("Venus", dict(BASE, Saturn=220.))
+    assert result["jeeva"] == "Mars"
+
+
+def test_nodal_exaltation_not_silently_imported_from_another_school():
+    result = run("Moon", dict(BASE, Moon=275., Sun=65., Mercury=100., Rahu=70.))
+    assert result["status"] == "blocked"
+    assert result["trace"][0]["reason"] == "nodal_exaltation_profile_required"
+
+
+def test_source_table_roles_replay_with_explicit_stellar_assumption():
+    # Anonymous printed pp92-96 structural example. Not independent verification.
+    # Mars uses 29 degrees: OCR minute is uncertain, same star/sign throughout.
+    chart = dict(Sun=157+52/60, Moon=147+28/60, Mars=239., Mercury=144+51/60,
+                 Jupiter=250+29/60, Venus=184+48/60, Saturn=200+2/60,
+                 Rahu=36+43/60, Ketu=216+43/60)
+    expected = dict(Sun=("Sun", "Mercury"), Moon=("Sun", "Mercury"),
+                    Mars=("Mercury", "Venus"), Mercury=("Venus", "Mars"),
+                    Jupiter=("Mars", "Mercury"), Venus=("Mars", "Mercury"),
+                    Saturn=("Jupiter", "Mars"))
+    for lord, pair in expected.items():
+        result = run(lord, chart, stellar_digbala={"Moon": False, "Mercury": True})
+        assert (result["jeeva"], result["sareera"]) == pair
+        assert result["external_verified"] is False
+
+
+def test_native_cli_executes_without_export_or_prediction(tmp_path):
+    request = tmp_path / "synthetic.json"
+    request.write_text(json.dumps(dict(positions=BASE, bhava_lord="Moon",
+                                      ayanamsa="synthetic", node_mode="mean")))
+    root = Path(__file__).resolve().parents[1]
+    completed = subprocess.run(
+        [sys.executable, "scripts/jyotish_engine.py", "nadi-stellar-roles", "--request", str(request)],
+        cwd=root, text=True, capture_output=True, check=True)
+    result = json.loads(completed.stdout)
+    assert result["status"] == "executed"
+    assert result["sareera"] == "Venus"
+    assert result["prediction_scoring_allowed"] is False

tests/test_strength_source_integrity.py

@@ -0,0 +1,66 @@
+"""Ported from upstream 0266b6ad (astrologer branch d09feab7, 2026-11-07 sync).
+
+The year lord is selected by the native Tajika five-fold Panchavargiya; an
+external (PyJHora) score is an observation beside it and cannot change the
+selection, the components, or fill missing native inputs. The annual strength
+table shows the same native score and components.
+
+Local divergence: upstream's third test relabels the legacy Sun/Mars/Saturn
+subtraction (`calc_sodhita_av`). That table was removed here (BUG-1209), so the
+test asserts it stays absent and that the product chain is the classical one.
+"""
+from scripts import ashtakavarga, tajika
+from scripts import tajika_year_lord
+
+
+POSITIONS = {'Sun': 10., 'Moon': 42., 'Mars': 75., 'Mercury': 108.,
+             'Jupiter': 141., 'Venus': 174., 'Saturn': 207.}
+
+
+def test_external_score_cannot_change_year_lord_or_native_components(monkeypatch):
+    monkeypatch.setattr(tajika, '_external_pyjhora_panchavargiya_score', lambda *a, **kw: None)
+    baseline = tajika.calc_panchadhikari_year_lord(POSITIONS, 0, 10, 25)
+    monkeypatch.setattr(tajika, '_external_pyjhora_panchavargiya_score',
+                        lambda *a, **kw: {'score': 999, 'engine': 'external_fixture', 'components': {}})
+    observed = tajika.calc_panchadhikari_year_lord(POSITIONS, 0, 10, 25)
+    assert observed['year_lord'] == baseline['year_lord']
+    assert observed['panchavargiya_selection_policy'] == 'native_components_external_observation_only'
+    native = tajika._calc_native_panchavargiya_bala(POSITIONS)
+    for row in observed['candidates']:
+        assert row['panchavargiya_score'] == native[row['planet']]['score']
+        assert row['panchavargiya_components'] == native[row['planet']]['components']
+        assert row['panchavargiya_engine'] == 'tajika_native_five_fold'
+        assert row['external_oracle_comparison']['score'] == 999
+        assert row['external_oracle_comparison']['comparison_role'] == 'observation_only_not_selection_input'
+
+
+def test_external_score_cannot_fill_missing_native_inputs(monkeypatch):
+    monkeypatch.setattr(tajika, '_external_pyjhora_panchavargiya_score',
+                        lambda *a, **kw: {'score': 10, 'engine': 'fixture', 'components': {}})
+    assert tajika.calc_panchadhikari_year_lord({'Sun': 10., 'Moon': 42.}, 0, 10, 25)['status'] == 'blocked'
+
+
+def test_year_lord_selection_and_strength_table_show_the_same_native_score():
+    selected = tajika.calc_panchadhikari_year_lord(POSITIONS, 0, 10, 25)
+    table = tajika.calc_tajika_strength_layers(POSITIONS, 0.0, selected['year_lord'])['panchavargiya_bala']
+    listed = tajika_year_lord._candidate_list(selected['candidates'], selected['year_lord'])
+    assert listed and any(row['selected'] for row in listed)
+    for row in listed:
+        shown = table[row['planet']]
+        assert row['panchavargiya_score'] == shown['score']
+        assert row['panchavargiya_raw_total'] == shown['raw_total']
+        assert row['panchavargiya_components'] == shown['components']
+        assert set(row['panchavargiya_components']) == {
+            'graha_bala', 'uchcha_bala', 'hudda_bala', 'drekkana_bala', 'navamsha_bala'}
+
+
+def test_legacy_subtraction_table_stays_absent_from_the_product():
+    assert not hasattr(ashtakavarga, 'calc_sodhita_av')
+    planets = {name: {'sign': tajika.SIGNS[int(lon // 30)]} for name, lon in POSITIONS.items()}
+    planets.update({'Rahu': {'sign': 'Aries'}, 'Ketu': {'sign': 'Libra'}})
+    av = ashtakavarga.calc_ashtakavarga(planets, 0)
+    from scripts.ashtakavarga_shodhana import sodhita_chain
+    chain = sodhita_chain(av['bav'], planets)
+    assert chain['status'] == 'executed'
+    assert 'BPHS标准' not in chain['method']
+    assert len(chain['sodhita_sav']['assessment']) == 12