docs: product-level README, AGENTS.md split into code/reading parts, add CLAUDE.md, move task briefs to docs/tasks

- README.md is now the product/repo front door (architecture, repo map,
  local dev, test tiers, delivery flow, doc map). Engine positioning,
  VedAstro/Codex setup and the oracle/benchmark command reference move
  verbatim to docs/engine/README.md, docs/engine/vedastro-gateway.md and
  docs/benchmark/README.md. Capability badges realigned with the registry
  (91/78/8/0); tests/test_readme_badges.py was red on staging.
- AGENTS.md: Part A (environment truth, delivery, worktrees, record
  placement, bug workflow, growth freeze, frontend red lines, privacy,
  pre-work check, test tiers) and Part B (reading-rigor constraints).
  GitHub issue-tracker/triage boilerplate removed: GitHub is a read-only
  mirror. All strings locked by tests/ are preserved.
- CLAUDE.md added: roles, three working modes, task-brief sections,
  acceptance criteria, session discipline; imports AGENTS.md.
- 50 tracked TASK-*/PROGRESS-* files and 3 never-committed briefs move to
  docs/tasks/ with an index; REPO_LAYOUT.md merged into README.

Docs-only change (no gated path touched).

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0193vBv6w5MV2cifdTUu9H5P
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Jesse_Chen
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# Jyotish 计算引擎与解读流水线(引擎层文档)
> 本文从 2026-09-03 之前的根 README 拆出,描述 Python 引擎(`scripts/`、`references/`、`SKILL.md`)的定位、流水线、技法覆盖与诚实边界。产品层(网页、部署、协作流程)见根目录 `README.md`。正文保留原文,"Project Status"一节反映 v6.9.14 时期的状态,仅作历史参考。
## What Is This
This is a **Vedic (Jyotish) astrology analysis system** designed for deep, auditable full-chart readings. It is NOT a simple ephemeris calculator — it is a multi-stage interpretive pipeline that:
1. **Computes** divisional charts (D1/D9/D10/...) via Swiss Ephemeris
2. **Routes** 89 capability entries as a backend evidence pool (Dashas, Yogas, Shadbala, Ashtakavarga, Transits...)
3. **Routes** the analysis through strict workflow paths depending on question type (career / relationship / wealth / timing)
4. **Audits** every technique used — declaring what was called, what is complete/covered, and which limitations affect confidence
5. **Degrades gracefully** — limitations are labeled, not silently over-promising
### Key Differentiators (vs. PyJHora / VedAstro / Maitreya)
| Feature | This Project | PyJHora | VedAstro | Maitreya |
|---------|-------------|----------|----------|----------|
| Full-reading pipeline (one command) | ✅ | ❌ | ❌ | ❌ |
| Strict workflow router (per-question-type) | ✅ | ❌ | ❌ | ❌ |
| Technique Audit Table (confidence labeling) | ✅ | ❌ | ❌ | ❌ |
| Capability degradation (limits are explicit) | ✅ | ❌ | ❌ | ❌ |
| MEVG external verification gates | ✅ | ❌ | ❌ | ❌ |
| 89 capability entries routed as a backend evidence pool | ✅ | ✅ (50+) | ✅ (200+) | ✅ |
| Traditional algorithm benchmarked | ✅ mixed depth | ✅ | ✅ | ✅ |
| Docker / MCP Server | ✅ | ❌ | ✅ | ❌ |
| English docs / PyPI package | ✅ in progress | ✅ | ✅ | ✅ |
---
### Prerequisites
- Python 3.11+
- Swiss Ephemeris (`pyswisseph` or `ephem`)
- Optional: `pypdf`, `pdfplumber` (for PDF chart input)
### Install
```bash
# Clone the repository
git clone https://github.com/732642856/yinduzhanxing.git
cd yinduzhanxing
# Install Python dependencies
pip install -r requirements.txt
# Verify installation
python3 scripts/audit_capabilities.py --mode validate
# Expected: valid=true, problem_count=0
```
### Minimal Full Reading (5 minutes)
```bash
python3 scripts/jyotish_engine.py full-reading \
--year 1990 --month 6 --day 15 \
--hour 10 --minute 30 \
--lat 28.6139 --lon 77.2090 --tz 5.5 \
--age 36 \
--transit-date 2026-06-04
```
**Output:** ~45 computed modules, zero errors, complete structured reading with technique audit table.
### Sample Output (abbreviated)
```
═══ FULL READING ═══
Birth Data: 1990-06-15 10:30 (+5.5) 28.61°N 77.21°E
Lagna: Gemini Sun: Taurus Moon: Leo
── Static Analysis ──
[✓] D1 Rashi Chart
[✓] D9 Navamsa
[✓] D10 Dasamsa
[✓] Vimshottari Dasha (120 years)
[✓] Ashtakavarga (8-point system)
[✓] Shadbala (covered — absolute Rupa totals, component invariants verified)
[✓] Yogas & Doshas
[✓] Argala (planetary interventions)
[✓] Nakshatra Advanced (Chandra Bala / Tara Bala)
── Dynamic Timing ──
[✓] Vimshottari Dasha breakdown
[✓] Dasha Sandhi detection
[✓] Transit (true positions)
[✓] Double Transit analysis
[✓] Narayana Dasha
[✓] Solar Return / Varshaphala
[✓] Nakshatra Dasha (Ashtottari)
── Technique Audit Table ──
✓ Vimshottari Dasha covered high confidence
✓ Ashtakavarga covered high confidence
✓ Shadbala covered absolute Rupa output; total_virupas component invariant passed
✓ Chara Dasha covered KN Rao benchmark 95.83% overall match
✓ KP Sub-Lord covered SubLord/SubSubLord + ABCD significator workflow
```
## Core Workflow
### Three Input Paths
| Path | Input | Behavior |
|------|-------|----------|
| **A: Precise birth data** | Date + time + coordinates | Full `full-reading` engine |
| **B: PDF / text chart** | Scanned chart or description | Extract → Quality Gate → route to A |
| **C: Uncertain birth time** | "Don't know my birth time" | Interactive birth time rectification |
### Eight-Stage Pipeline
```
Stage -1: Question-type routing (career / relationship / wealth / timing)
Stage 0: Input routing (A / B / C)
Stage 1: (B only) PDF extraction + Quality Gate
Stage 2: Intent recognition → target house routing
Stage 3: Static analysis (10 steps)
Stage 4: Dynamic timing (7 steps)
Stage 5: Timing output (5-layer verification)
Stage 6: Remedial measures (optional)
Stage 7: Modern language packaging
Stage 8: Technique Audit Table (mandatory)
```
**Strict Workflow Router** (`references/strict-workflow-router.md`):
- Career questions → `career-timing-strict`
- Relationship questions → `relationship-timing-strict`
- Wealth questions → `wealth-timing-strict`
- Event timing → `event-timing-strict`
- Historical verification → `event-verification-strict`
The AI does NOT require the user to name techniques (e.g., "Chara Dasha"). It auto-selects based on question type.
---
## Technique Coverage
Current registry count: **89 capability entries** (79 covered, 10 complete, 0 partial, 0 missing).
These entries are a **backend evidence pool**, not a flat list of 89 user-facing
prediction sources. Ordinary users see topic-level conclusions and evidence
summaries. The question-domain router selects a small primary chain, then uses
supporting indicators only to raise/lower confidence. Audit-only and alias
entries cannot affect astrological conclusions.
The table below lists representative high-value entries. Treat
`references/technique_registry.json` as the source of truth for the full
machine-readable registry.
| Technique | Status | Notes |
|-----------|--------|-------|
| D1 Rashi Chart | ✅ covered | Swiss Eph base |
| D9 Navamsa | ✅ covered | |
| D10 Dasamsa | ✅ covered | |
| Vimshottari Dasha | ✅ covered | |
| Dasha Sandhi | ✅ covered | |
| Ashtakavarga | ✅ covered | BPHS/PVR calibrated |
| Argala | ✅ covered | |
| Vargottama | ✅ covered | |
| Pushkara | ✅ covered | |
| A10 / Karma Pada | ✅ covered | |
| UL / Upapada | ✅ covered | |
| Transit (true positions) | ✅ covered | |
| Double Transit | ✅ covered | |
| Nakshatra Advanced | ✅ covered | Tara Bala / Chandra Bala / Sub-Lord workflow |
| Narayana Dasha | ✅ covered | CLI and full-reading integration |
| Solar Return / Varshaphala | ✅ covered | Tajika annual-chart workflow |
| **Shadbala** | ✅ covered | **absolute Rupa component-sum output; internal invariants pass; external absolute-value oracle expansion remains open** |
| **Chara Dasha** | ✅ covered | **KN Rao benchmark: sign 100%, duration 91.67%, overall 95.83%** |
| KP Sub-Lord | ✅ covered | SubLord/SubSubLord + ABCD significator workflow |
| Bhava Chalit | ✅ covered | Sripati/Porphyry/Equal/Whole Sign/Placidus/Koch |
| Sudarshana Chakra | ✅ covered | Asc/Moon/Sun reference charts + convergence scoring |
| Tajika Yogas | ✅ complete | Annual-chart yoga set |
| Raj Yoga | ✅ covered | Rule-based detection |
| Dhana Yoga | ✅ covered | Rule-based detection |
| Pancha Mahapurusha | ✅ covered | Complete detection |
| Neecha Bhanga | ✅ complete | Debilitation cancellation workflow |
| Sade Sati | ✅ covered | Saturn pressure timing |
| Tithi Lord | ✅ complete | Lunar-day ruler workflow |
| Pancha Pakshi | ✅ complete | Five-bird system |
| Rashi Tulya Navamsa | ✅ covered | D1/D9 mapping |
| Trimshamsa D30 | ✅ covered | D30 varga support |
| Marriage Counting | ✅ complete | Bhrigu Pada marriage-counting method |
| Prashna Integration | ✅ complete | Prashna workflow integrated |
| Bhrigu Pada Dasha | ✅ complete | Pada progression workflow |
| Muhurta | ✅ covered | Panchanga / auspicious timing workflow |
**Legend:**
-`covered` — implemented and benchmarked against authoritative sources
-`complete` — implemented with integrated workflow and validation hooks
-`covered` — implemented and available in the engine, sometimes with explicit confidence caps
- 🔶 `partial` — reserved for implemented-but-insufficiently-integrated techniques; current registry count is 0
-`missing` — not currently present in the registry; current registry count is 0
---
## Why This Exists (Competitive Context)
### The Landscape
| Project | Type | Strength | Weakness |
|---------|------|----------|-----------|
| **PyJHora** | Calculation library | Strongest traditional algorithm coverage (50+ Dashas, 284 Yogas) | No interpretive pipeline; user must interpret results themselves |
| **VedAstro** | API / Web platform | 200+ endpoints, Docker, MCP Server, MIT license | Interpretive audit & confidence labeling weaker |
| **Maitreya** | Desktop software | Mature cross-platform GUI | Jyotish depth not as deep as specialized projects |
| **jyotisha** | Panchanga / calendar | Excellent Panchanga accuracy | Not a full reading system |
| **This project** | AI-native analysis system | Full pipeline + audit + degradation | Pure calculation accuracy still being benchmarked |
### Our Position
> **PyJHora is the calculator. VedAstro is the API platform. Maitreya is the desktop software. This project is the "AI-native Jyotish research analyst."**
We are NOT trying to out-calculate PyJHora (it has years of lead). Our value is in:
1. Organizing calculations into a **reproducible interpretive workflow**
2. **Auditing** every technique used and declaring confidence
3. **Degrading gracefully** — confidence caps and limitations are labeled, not silently over-promising
4. Being **AI-native** — designed for integration with LLM-based analysis
---
## Honest Assessment
We believe in transparency about limitations. This is NOT a "99% accurate" system, and anyone claiming that about Jyotish is over-selling.
### Current Accuracy Estimates (self-evaluated)
| Dimension | Score | Notes |
|-----------|-------|-------|
| Astronomical foundation (Swiss Eph) | 8.5/10 | Depends on ayanamsa, node mode, house system |
| Traditional algorithm accuracy | 8.4/10 | Chara Dasha benchmark passed; Shadbala absolute Rupa invariants now pass; Dasha oracle expansion remains open |
| Technique coverage breadth | 9.1/10 | 65 registered techniques; broad and increasingly benchmarked |
| Reading detail depth | 9.6/10 | Possibly best among open-source projects |
| Prediction workflow rigor | 8.8/10 | Strict routing + audit table |
| Verification system | 8.2/10 | Has registry, benchmark, degradation; some verification still internal |
| Engineering maturity | 7.6/10 | Docker, PyPI config and CI exist; release artifacts still need cleanup |
| Open-source influence | 5.5/10 | Currently more of a "private high-density toolkit" |
### What Confidence Caps Mean (Important)
Even when a technique is labeled `covered`, it may carry a confidence or validation boundary:
- It CAN produce output
- Some components may still need broader external oracle expansion against PyJHora / JHora / canonical texts
- It should be interpreted together with cross-technique evidence
- It must NOT be the sole basis for high-confidence predictions when its limitation says so
Examples:
- `Shadbala` (covered): absolute Rupa totals are reported directly from six component sums; internal component invariants pass and `total_rupas = total_virupas / 60`, while external absolute-value oracle expansion remains open.
- `Chara Dasha` (covered): KN Rao benchmark passes at 95.83% overall; remaining differences are documented around Aquarius/Scorpio co-lord strength arbitration.
---
## Project Status
**Current version:** `v6.9.14`
### Recently Completed
- `v6.9.14` — Sudarshana Chakra complete + 475 pytest cases + 65-technique registry audit PASS.
- `v6.9.13` — Bhava Chalit complete + transit trigger output normalization + Nakshatra test calibration.
- `v6.9.12` — Shadbala precision upgrade + Ashtakoot 36-point compatibility + expanded subcommands.
- `v6.9.6` — Field mapping fixes (degree→degree_in_sign + toFixed null safety); PyPI publishing config.
- `v6.9.5` — birth_info null safety + API field mapping fixes.
- `v6.9.4` — AI interpretation integration; current browser build disables direct model API keys and routes AI through server-side `/api/chat` or a backend proxy.
- `v6.9.3` — 35 Dasha systems, 405+ Yoga rules, KP complete system, Prashna, 16-factor synastry, Remedies, Sahams 36, Sudarshana, PMC, Tajika.
- `v6.1.12` — Chara Dasha KN Rao Method rewrite, PyJHora benchmark 95.83% PASS.
- `v6.1.10` — Darakaraka deep reader wired into `full-reading.modules.jaimini.darakaraka`; thematic reports now consume real DK and Rashi Tulya Navamsa evidence.
- `v6.1.9` — Public/sanitized benchmark suite, competitive research, coverage roadmap and PDF validation methodology added.
- `v6.1.8` — Yoga validation reached F1=95.22% (FP=36, FN=63); thematic reports consume real `full-reading.modules` evidence.
- `v6.1.6` — Five-system Dasha convergence wired into full-reading (Vimshottari + Chara + Yogini + Ashtottari + Kalachakra).
- `v6.0.11` — Shadbala 1200/1200 internal invariants pass; later upgraded to absolute Rupa component-sum output.
### Actively Working On (P0)
1. **Release hygiene** — run the release profile, keep product-critical files tracked, rebuild wheel/sdist, and align GitHub tags with source version
2. **README / package metadata sync** — keep public docs, registry counts and distribution artifacts consistent
3. **Dasha oracle expansion** — add external cases for Vimshottari start/end boundaries and configurable year-length/ayanamsa comparisons
4. **Benchmark expansion** — add more oracle cases for Shadbala, KP and annual-chart modules
5. **Frontend verification** — keep the Next.js API contracts aligned with the Python engine output
### Next (P1)
- Production image publishing and smoke-test docs
- English documentation examples and API tutorials
- Multi-Ayanamsa UX polish and benchmark examples(计算层已可验证切换;网页设置展示和更多外部样本仍需补齐)
---
## Engine-level development checks
### Running the Test Suite
```bash
# Syntax check all scripts
python3 -m py_compile scripts/*.py
# Capability audit (must pass with 0 problems, 0 warnings)
python3 scripts/audit_capabilities.py --mode validate
# Next.js unit tests, lint, and production build
npm test --prefix frontend
npm run lint --prefix frontend
npm run build --prefix frontend
# Full-reading regression test (use FICTIONAL data only)
python3 scripts/jyotish_engine.py full-reading \
--year 1990 --month 6 --day 15 \
--hour 10 --minute 30 \
--lat 39.9042 --lon 116.4074 --tz 8 \
--age 36 \
--transit-date 2026-06-04
```
### Important Rules
1. **NEVER** put real user birth data into skill files, tests, CHANGELOG, or public repos
2. Use only: (a) public AA-rated celebrity data, (b) explicitly fictional smoke tests, (c) current-session data (never persisted)
3. Always run `git status --short --branch` before starting work
4. Always run `py_compile` + `audit_capabilities.py` + full-reading regression after modifications
5. Do NOT remove a confidence or validation boundary without external benchmark evidence
6. Do NOT refactor arbitrarily; make minimal verifiable changes
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# VedAstro Gateway、用户级入口与 Codex 插件
> 本文从根 README 拆出(2026-09-03),内容原样保留:VedAstro 官方/自建/本地回退三种模式的配置、中国大陆 Gateway 部署边界、`scripts/vedastro_user_entrypoint.py` 用户级入口,以及把本仓装成 Codex 本地插件的步骤。
### VedAstro:聊天产品推荐配置
项目当前固定使用官方 Python SDK `vedastro==1.23.25`。首次安装依赖时必须安装到项目虚拟环境,并用同一个解释器启动后端,避免子进程落到系统 Python 后出现 `No module named vedastro`
```bash
.venv/bin/pip install -r requirements.txt
.venv/bin/python scripts/jyotish_api_server.py --host 127.0.0.1 --port 5200
```
在仓库根目录创建本机私有配置文件 `.env.local`。聊天场景推荐先使用下面的快速官方证据模式:
```dotenv
VEDASTRO_API_ENDPOINT=https://api.vedastro.org/api
VEDASTRO_ENABLE_NETWORK=1
VEDASTRO_TIMEOUT_SECONDS=20
VEDASTRO_GATEWAY_REQUIRE_OFFICIAL_RAW_RESPONSE=1
# 聊天快速模式:保留 Dasha / Chara Dasha / Shadbala / Ashtakavarga
# 不执行 10 行星 + 12 宫位的逐项 fan-out。
VEDASTRO_FULL_SNAPSHOT_FANOUT_ENABLED=0
# 免费公共模式下 SearchEvents 范围扫描耗时长且容易限流,
# 聊天请求中默认关闭,避免同步阻塞流式回复。
VEDASTRO_RANGE_SCAN_NETWORK_ENABLED=0
VEDASTRO_CACHE_TTL_SECONDS=604800
VEDASTRO_OFFICIAL_FULL_SNAPSHOT_CACHE_TTL_SECONDS=604800
VEDASTRO_GATEWAY_QUEUE_ENABLED=1
VEDASTRO_FREE_TIER_QUEUE=1
VEDASTRO_FAIL_OPEN_LOCAL=1
VEDASTRO_FULL_CATALOG_SAMPLE_LIMIT=0
# 没有 key 时可先使用官方公共/免费模式;不要把 key 放到前端。
# VEDASTRO_API_KEY=your_vedastro_key
```
该文件已被 `.gitignore` 忽略;`scripts/jyotish_api_server.py``scripts/vedastro_service_adapter.py``scripts/run_quality_gate.py` 会自动加载它。VedAstro 子进程默认复用启动后端的 `sys.executable`;如需指定独立解释器,可设置 `VEDASTRO_PYTHON_BIN=/absolute/path/to/python`
快速模式仍会取得 VedAstro 官方原始响应,并让 Gateway 在存在 `official_raw_response` 时闭合为 `official_verified`;D1/D9 等基础盘继续由本地 Swiss Ephemeris 负责。它只关闭高延迟 fan-out 与 `SearchEvents` 范围扫描,不等于关闭 VedAstro。
获得稳定 API key,或把 Gateway 指向自建 VedAstro 服务后,可开启完整模式:
```dotenv
VEDASTRO_API_KEY=your_vedastro_key
VEDASTRO_FULL_SNAPSHOT_FANOUT_ENABLED=1
VEDASTRO_RANGE_SCAN_NETWORK_ENABLED=1
```
完整模式会增加外部请求数量和首包等待时间,更适合后台任务、预计算或非实时专业解盘,不建议直接放在聊天首轮的同步关键路径。运行 `.venv/bin/python scripts/diagnose_vedastro_mode.py` 可检查当前模式;通过 `/api/vedastro_gateway/status` 查看 Gateway 的实际配置和 readiness。
AI/vibe coding 推荐入口:Cline 接本仓 MCPAider 负责低成本小改,Dyad 只做前端原型。运行 `python3 scripts/print_cline_mcp_config.py` 生成 Cline MCP 配置;详情见 `docs/vibe_coding_setup.md`
### 中国大陆用户:VedAstro Gateway 模式
普通中国大陆用户不需要、也不应该让浏览器直连 VedAstro。推荐部署方式是:网页只访问你自己的本地或云端后端;后端通过 `VedAstro Gateway` 统一管理 self-host、official upstream、TTL/cache、free-tier queue 和 local fallback。
最短配置:
```bash
cp .env.cn.example .env.local
.venv/bin/python scripts/jyotish_api_server.py --host 127.0.0.1 --port 5200
npm ci --prefix frontend
npm run dev --prefix frontend
```
网页侧使用:
- `Trust Center -> Web Professional Reading v1`
- `/api/vedastro_gateway/status` 查看当前后端策略
- `/api/vedastro_gateway/run` 生成 VedAstro-compatible evidence packet
- `/api/professional_reading` 生成网页专业解盘包
关键边界:
- 不要让浏览器直连 VedAstro,也不要把 `VEDASTRO_API_KEY` 放进前端。
- `VEDASTRO_CACHE_TTL_SECONDS``VEDASTRO_OFFICIAL_FULL_SNAPSHOT_CACHE_TTL_SECONDS` 用于缓存官方或自建服务结果。
- `VEDASTRO_GATEWAY_QUEUE_ENABLED=1` / `VEDASTRO_FREE_TIER_QUEUE=1` 用于把昂贵或被限流的外部请求排队。
- 如果 VedAstro 官方或自建服务不可达,`VEDASTRO_FAIL_OPEN_LOCAL=1` 会保持本地 Jyotish 引擎继续输出,并在 Technique Audit Table 里降级标注。
- Gateway 不会默认声称跑完 641 项;它只把 capability catalog、dynamic selection、cache/queue/fallback 状态作为证据边界交给 strict workflow。
### Codex 用户级 VedAstro + strict workflow 入口
如果用户在 Codex 窗口从云端 Git 仓库拉取本项目,推荐先走这一条稳定入口,而不是手动拼多个底层脚本:
```bash
python3 scripts/vedastro_user_entrypoint.py \
--year YYYY --month MM --day DD --hour HH --minute mm \
--lat LAT --lon LON --tz TZ \
--question "事业机会什么时候出现" \
--themes career,marriage,wealth \
--reference-date 2026-07-02 \
--format markdown
```
机器读取或交给后续 agent 处理时使用 JSON
```bash
python3 scripts/vedastro_user_entrypoint.py \
--year YYYY --month MM --day DD --hour HH --minute mm \
--lat LAT --lon LON --tz TZ \
--question "事业机会什么时候出现" \
--themes career,health,education,property,children,migration,prashna \
--reference-date 2026-07-02 \
--format json
```
这个入口会自动做四件事:
1. 读取 `.env.local` 并诊断当前是 `official_extended` 还是 `fast_local_fallback`
2. 启动 `official_full_capability_catalog`,给 VedAstro 官方能力目录生成 `domain / execution_policy / adjudicator_use / confidence_role / blocked_reason`
3.`--themes` 做动态选择,避免把健康、教育、房产、子女、迁移、Prashna 等非三大主题塞进 `general`
4. 触发 strict workflow 合同摘要,输出 primary route、可用 route、cache/TTL/free-tier queue 策略和 honesty boundary。
边界必须保留:这个入口**不会把 641 项全部当作已执行**。它先做官方能力目录分类和主题选择;能自动执行的进入证据层,需要第二人资料、用户文本、校时画像或官方网络预算的方法会保持 `needs_user_context``needs_user_text``needs_rectification_profile``blocked`
#### 作为 Codex 本地插件安装
本仓现在带了最小插件包装:`.codex-plugin/plugin.json`。它复用现有 `skills/` 与根目录 `mcp_server.py`,适合你把当前仓直接装进 Codex 本机环境。
1. 先把本仓登记到个人 marketplace
```bash
python3 <home>/.codex/skills/.system/plugin-creator/scripts/create_basic_plugin.py \
jyotish-vedic-astrology \
--path ~/.codex/plugins \
--marketplace-path ~/.agents/plugins/marketplace.json \
--marketplace-name personal \
--with-marketplace
```
上面是 Codex 官方脚本的标准 marketplace 流。如果你要让 **当前仓本身** 被安装,关键不是用 scaffold 目录跑能力,而是让 `~/.agents/plugins/marketplace.json` 里的 `jyotish-vedic-astrology` 条目最终指向当前仓路径。
最少要确认这一条存在:
```json
{
"name": "jyotish-vedic-astrology",
"source": {
"source": "local",
"path": "<repo>"
}
}
```
2. 若本机还没把 personal marketplace 接进 Codex
```bash
codex plugin marketplace add ~/.agents/plugins/marketplace.json
```
3. 安装插件:
```bash
codex plugin add jyotish-vedic-astrology@personal
```
4. 检查是否已被识别:
```bash
codex plugin list
```
5. 开一个**新线程**再测试。Codex 只会在新线程里重新拾取新装的 skills / MCP。
#### 本地更新 / 重装
当你改了 `.codex-plugin/plugin.json``skills/``mcp_server.py`
```bash
python3 <home>/.codex/skills/.system/plugin-creator/scripts/update_plugin_cachebuster.py \
<repo>
codex plugin add jyotish-vedic-astrology@personal
```
然后重新开新线程验证。
推荐的 official extended `.env.local` 示例:
```bash
VEDASTRO_API_ENDPOINT=https://api.vedastro.org/api
VEDASTRO_ENABLE_NETWORK=1
VEDASTRO_TIMEOUT_SECONDS=20
VEDASTRO_CACHE_TTL_SECONDS=600
VEDASTRO_OFFICIAL_FULL_SNAPSHOT_CACHE_TTL_SECONDS=600
VEDASTRO_FREE_TIER_QUEUE=1
# 可选
# VEDASTRO_API_KEY=sk_live_xxx
```
先运行:
```bash
python3 scripts/diagnose_vedastro_mode.py
```
若仍显示 `fast_local_fallback`,用户级入口仍可运行,但解盘必须把 VedAstro official 证据写成 blocked/降级,不能声称 official extended 已闭环。