Jesse_ChenandClaude Opus 5.5
147ebc1789
The natal system prompt now says: the card in claim_cards is the chart evidence for this answer, quote it as given, look up one further section of this calculation with read-consultation-evidence before writing, and read evidence_card.backstage as a confidence cap. The "use every executed layer" and must_use_layers sentences are replaced; local_layers paths now point at the card. SKILL.md 关联技法完整调取 / 0.0.1 and router 0.7 state that the full result stays in receipts, the 本轮技法 panel and reports while web chat answers from the card; computing the full spectrum is unchanged. Skill and package version 6.9.16 -> 6.9.17 (tests/run_all.py 三栏). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017eEAG8HD3mm8gsKXgk8uU8
267 lines
14 KiB
TypeScript
267 lines
14 KiB
TypeScript
import assert from "node:assert/strict";
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import { readFileSync } from "node:fs";
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import test from "node:test";
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import { createConsultationPlan } from "../src/lib/consultation-plan.ts";
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import { toAgentConsultationContext, toModelOutput } from "../src/mastra/consultation-workflow.ts";
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test("passes transparent public-case references into the agent context", () => {
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const workflowSource = readFileSync(new URL("../src/mastra/consultation-workflow.ts", import.meta.url), "utf8");
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const agentSource = readFileSync(new URL("../src/mastra/index.ts", import.meta.url), "utf8");
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assert.match(workflowSource, /reference_transparency:\s*record\(data\.reference_transparency\)/);
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assert.match(workflowSource, /vedastro_gateway:\s*record\(data\.vedastro_gateway\)/);
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assert.match(workflowSource, /ashtakavarga:\s*chart\.ashtakavarga/);
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assert.match(agentSource, /high_similarity_public_references_available/);
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assert.match(agentSource, /requested_uncovered_domains/);
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assert.match(agentSource, /public_context_only/);
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assert.match(agentSource, /timing_state/);
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assert.match(agentSource, /partial_match/);
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assert.match(agentSource, /narayana_status/);
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assert.match(agentSource, /transit_status/);
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assert.match(agentSource, /Jupiter and Saturn relative houses/);
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assert.match(agentSource, /exact_triggers as technical trigger points/);
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assert.match(agentSource, /production_tuning_allowed=false/);
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assert.match(agentSource, /no_majority_vote/);
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assert.match(agentSource, /method_variant_not_majority_vote/);
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assert.match(agentSource, /Shadbala\/Ashtakavarga component differences/);
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assert.match(agentSource, /D2, D11/);
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assert.match(agentSource, /gender-specific spouse significators are supplements/);
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assert.match(agentSource, /male.*Venus/);
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assert.match(agentSource, /female.*Jupiter\/Mars/);
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});
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test("keeps strength, Ashtakavarga, and timing evidence available to the answer model", () => {
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const workflowSource = readFileSync(new URL("../src/mastra/consultation-workflow.ts", import.meta.url), "utf8");
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const agentSource = readFileSync(new URL("../src/mastra/index.ts", import.meta.url), "utf8");
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assert.match(workflowSource, /shadbala: chart\.shadbala/);
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assert.match(workflowSource, /shadbala_boundary:/);
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assert.match(workflowSource, /ashtakavarga: modules\.ashtakavarga/);
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// This line used to pin the misspelling: it asserted the packet read
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// `modules.dasha_boundaries` without anything checking that the engine writes
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// that key. tests/test_consultation_consumer_context.py now compares the names
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// across the boundary; this only pins that timing evidence is still passed.
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assert.match(workflowSource, /dasha_sub_periods: modules\.dasha_sub_periods/);
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assert.match(workflowSource, /varga_spectrum: modules\.varga_spectrum/);
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assert.match(workflowSource, /technique_audit_table: consumerContext\.technique_audit_table/);
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// 原值: assert.match(agentSource, /evidence_contract\.technique_audit_table/)（提示要求模型通读审计表）
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// 新值: 审计表仍由工作流带回、留在服务端回执与「本轮技法」面板；提示改为数据卡是清单、审计记录留在服务端
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// 原因: TASK-consult-evidence-card-20260927 D3/T4（推翻「technique_audit_table is the invocation record… Use every executed layer」）
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assert.doesNotMatch(agentSource, /evidence_contract\.technique_audit_table/);
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assert.match(agentSource, /the full invocation record \(executed \/ blocked \/ not applicable per technique\) stays with the server/);
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assert.match(workflowSource, /evidence_contract:/);
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assert.match(workflowSource, /missing_route_layers: consumerContext\.missing_route_layers/);
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assert.match(workflowSource, /answer_policy: consumerContext\.answer_policy/);
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assert.match(agentSource, /evidence_contract\.answer_policy/);
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assert.match(agentSource, /can_answer_precise_timing/);
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assert.match(workflowSource, /function rectificationBoundaryFromGate/);
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assert.match(agentSource, /rectification\.boundary=not_auto_rectified/);
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assert.match(workflowSource, /external_engine_evidence:/);
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assert.match(workflowSource, /runtime_truth: record\(data\.runtime_truth\)/);
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assert.match(workflowSource, /numerical_parity: record\(data\.external_parity_gate\)/);
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assert.match(workflowSource, /real_case_calibration: record\(data\.real_case_calibration\)/);
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});
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test("projects only bounded server-selected evidence to the model", () => {
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const context = toAgentConsultationContext({
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success: true,
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question: "事业如何",
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chart: {
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birth: { date: "1990-01-02", time: "03:04", latitude: 25.03, longitude: 121.56 },
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ascendant: { sign: "Leo", degree: 12.5, reported_time: "private-reported-time" },
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planets: [{ name: "Sun", sign: "Capricorn", degree: 4.2, lng: "private-lng" }],
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houses: { first: { sign: "Leo" } },
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dasha: { current: "Mars", next: "Rahu", utc_offset: "private-utc-offset" },
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shadbala: { planets: { Sun: { total_rupa: 7.1 } } },
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ashtakavarga: { house_scores: { "10": 31 } },
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modules: {
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shadbala: { total: 412 },
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ashtakavarga: { total: 28 },
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varga_spectrum: {
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status: "used",
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mode: "full_spectrum",
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counts: { formal: 20, research_dn: 40, extended: 3, blocked: 0 },
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formal: { D9: { lagna: "Leo", planets: { Sun: "Capricorn" }, name: "Navamsa" } },
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research_dn: { D13: { lagna: "Aries", planets: { Moon: "Taurus" }, boundary: "generic D-N; not a formal named varga" } },
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},
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dasha_sub_periods: {
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current: { antardasha: { lord: "Saturn", start: "2025-10-17", end: "2027-05-18" } },
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boundary_count: 9,
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utc_offset: "private-module-utc-offset",
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},
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narayana_dasha: { current: "Aries" },
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functional_benefic_malefic: {
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status: "used",
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functional_benefics: ["Jupiter"],
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functional_malefics: ["Mercury"],
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},
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kakshya: { status: "observation_only", boundary: "not verified day/month timing" },
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yogas: { status: "executed", count: 1, yogas: [{ name: "Gaja Kesari", planets: ["Jupiter", "Moon"] }] },
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arudha_padas: {
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padas: {
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A10: { name: "Karma Pada (A10)", sign: "Capricorn" },
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UL: { name: "Upapada (UL)", sign: "Libra" },
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},
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},
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gulika: { sign: "Scorpio", claim_boundary: "observation_only" },
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kp_cusps: { houses: { "10": { sign: "Taurus", sublord: "Saturn" } } },
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chara_dasha: {
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status: "executed",
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current: { sign: "Libra", lord: "Venus", duration_years: 8 },
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sequence: [{ sign: "Libra", lord: "Venus", duration_years: 8 }],
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},
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transits: {
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status: "executed",
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sade_sati: { phase: "none", moon_sign: "Taurus", saturn_sign: "Pisces" },
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search_period: { start: "2026-07-14", end: "2026-10-12" },
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triggers: [{ date: "2026-08-21", planet: "Saturn", target: "Moon", kind: "exact_hit", orb: 0.08 }],
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boundary: "observation windows, not guaranteed events",
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},
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},
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},
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routing: { primary_theme: "career" },
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thematic_report: {
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themes: {
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career: {
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theme: "career",
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summary: "保留这条服务端证据摘要",
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narrative: "事业证据叙事",
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strength: "strong",
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account_balance: "private-account-balance",
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recommendations: ["保持稳健推进"],
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evidence: [{
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technique: "D10-Dashamsha-local",
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chart: "D10",
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conclusion: "D10 事业分盘已进入证据链",
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sentiment: "positive",
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strength: "strong",
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details: {
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source: "chart",
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derived: true,
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entitlements: "private-entitlements",
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access_scopes: "private-access-scopes",
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},
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}],
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},
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},
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},
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consumer_context: {
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route: "career", core_status: "ready", available_layers: ["natal", "timing"],
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missing_route_layers: [], hard_blockers: [],
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technique_truth: { status: "verified", access_scopes: "private-validation-scopes" },
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answer_policy: {
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can_answer_direction: true,
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can_answer_precise_timing: false,
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entitlements: "private-policy-entitlements",
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},
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user_facing_limitation: "精确月份暂不可用",
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technique_audit_table: [
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{ technique: "Formal Vargas D1–D60", status: "executed", system: "jyotish", boundary: "20/20 named traditional charts" },
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{ technique: "Yogas", status: "executed", system: "jyotish" },
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{ technique: "Arudha / UL / A10", status: "executed", system: "jyotish" },
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{ technique: "Narayana Dasha", status: "executed", system: "jyotish" },
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{ technique: "Functional Benefic/Malefic", status: "executed", key_functional_benefics: ["Jupiter"] },
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{ technique: "Western natal (tropical)", status: "executed", system: "western" },
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{ technique: "VedAstro Cloud State", status: "executed", boundary: "official_cloud_evidence_available" },
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{ technique: "MEVG / Global Web Evidence", status: "blocked", boundary: "caps_claims_until_global_web_evidence_runs" },
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],
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varga_spectrum: {
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status: "used",
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counts: { formal: 20, research_dn: 40 },
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formal: { D9: { lagna: "Leo", planets: { Sun: "Capricorn" } } },
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},
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western_spectrum: {
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status: "executed",
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natal: { sun: "Aries", moon: "Taurus", ascendant: "Leo" },
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techniques: {
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transits: {
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status: "executed",
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target_date: "2026-07-14",
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aspects: [{ transit_planet: "saturn", natal_point: "moon", aspect: "square", orb: 0.4 }],
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},
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},
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},
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vedastro_cross_check: {
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status: "executed",
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official_closure_state: "official_verified",
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natal: { sun: "Leo", moon: "Cancer", ascendant: "Scorpio" },
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},
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},
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reference_transparency: { similar_public_cases: { status: "public_context_only" } },
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rectification: { summary: "none" },
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vedastro_gateway: {
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official_closure_state: "official_verified",
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official_raw_response: { lat: 25.03, lon: 121.56, hour: 3, minute: 4 },
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},
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});
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const output = toModelOutput(context);
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const careerPlan = createConsultationPlan({ userIntent: "事业如何", theme: "career" });
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const careerOutput = toModelOutput(context, careerPlan);
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const serialized = JSON.stringify(output);
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assert.equal(output.packet_version, "consultation-evidence-packet-v2");
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assert.equal("birth" in output, false);
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assert.equal(serialized.includes("1990-01-02"), false);
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assert.equal(serialized.includes("03:04"), false);
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assert.equal(serialized.includes("25.03"), false);
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assert.equal(serialized.includes("121.56"), false);
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for (const privateValue of [
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"private-reported-time", "private-lng", "private-utc-offset", "private-module-utc-offset",
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"private-account-balance", "private-entitlements", "private-access-scopes",
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"private-validation-scopes", "private-policy-entitlements",
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]) {
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assert.equal(serialized.includes(privateValue), false);
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}
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for (const privateKey of [
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"reported_time", "lng", "utc_offset", "account_balance", "entitlements", "access_scopes",
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]) {
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assert.equal(serialized.includes(`"${privateKey}"`), false);
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}
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assert.equal(serialized.includes("保留这条服务端证据摘要"), true);
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assert.equal(serialized.includes("D10-Dashamsha-local"), true);
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assert.equal(serialized.includes("total_rupa"), true);
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assert.equal(serialized.includes("house_scores"), true);
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assert.equal(serialized.includes('"dasha"'), true);
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assert.equal(serialized.includes("narayana_dasha"), true);
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// Antardasha boundaries are what an answer needs to name a month at all, and
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// they were absent from every packet while this field named a module key the
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// engine never wrote.
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assert.equal(serialized.includes("dasha_sub_periods"), true);
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assert.equal(serialized.includes("2027-05-18"), true);
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assert.equal(serialized.includes('"status":"verified"'), true);
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const answerPolicy = output.evidence_contract.answer_policy as Record<string, unknown>;
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assert.equal(answerPolicy.can_answer_precise_timing, false);
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assert.deepEqual(output.claim_cards.map((card) => card.category), ["natal_foundation", "domain", "timing", "validation"]);
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assert.deepEqual(careerOutput.claim_cards.map((card) => card.category), ["natal_foundation", "domain", "timing", "validation"]);
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assert.equal(JSON.stringify(careerOutput).includes('"dasha"'), true);
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assert.equal(serialized.includes("consultation-evidence-packet-v2"), true);
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assert.equal(output.presentation.template, "skill_level_2");
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assert.equal(output.presentation.required_blocks.includes("technique_audit_table"), true);
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assert.equal(serialized.includes("Formal Vargas"), true);
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assert.equal(serialized.includes("varga_spectrum"), true);
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assert.equal(serialized.includes('"D13"'), true);
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assert.equal(serialized.includes("western_spectrum"), true);
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assert.equal(serialized.includes("technique_audit_table"), true);
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assert.equal(serialized.includes("functional_benefics"), true);
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assert.equal(serialized.includes("Jupiter"), true);
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assert.equal(serialized.includes("Gaja Kesari"), true);
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assert.equal(serialized.includes("Karma Pada (A10)"), true);
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assert.equal(serialized.includes("chara_dasha"), true);
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assert.equal(serialized.includes("Venus"), true);
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assert.equal(serialized.includes("sade_sati"), true);
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assert.equal(serialized.includes("Taurus"), true);
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assert.equal(serialized.includes("2026-08-21"), true);
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assert.equal(serialized.includes("search_period"), true);
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assert.equal(serialized.includes('"square"'), true);
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const mustUse = output.evidence_contract.must_use_layers;
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assert.equal(Array.isArray(mustUse), true);
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assert.equal((mustUse as string[]).includes("Yogas"), true);
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assert.equal((mustUse as string[]).includes("Arudha / UL / A10"), true);
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assert.equal((mustUse as string[]).includes("VedAstro Cloud State"), true);
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assert.equal((mustUse as string[]).includes("MEVG / Global Web Evidence"), false);
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assert.equal(serialized.includes("Scorpio"), true);
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assert.equal(serialized.includes("official_verified"), true);
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assert.equal(serialized.includes("https://"), false);
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});
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