v0.20.4 refine antigravity research skills
This commit is contained in:
Deep Research System
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# AGENTS.md — 生物医药 Deep Research 系统规则
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# AGENTS.md — Deep Research Cross-Tool Rules
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> 本文件为跨平台项目级指令文件。Codex、OpenCode、Claude Code、Antigravity、Gemini CLI 均应以本文件为运行规则。
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> 所有平台 adapter / skill / command 必须遵循本文件定义的研究方法论、信源标准与输出规范。
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This file is the shared, cross-tool instruction layer for Codex, OpenCode, Claude Code, Gemini CLI, and Antigravity.
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---
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Keep this file short. Do not put Antigravity roles, detailed workflows, or long skill manuals here.
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## 1. 项目使命
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## Project
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本项目通过**Python core + skills + 可选多模型角色**协作，以**麦肯锡、德勤等顶尖机构的研究方法**，对生物医药领域（研发、工艺、管理、投资）的指定主题进行深度研究，输出专业级报告（PDF + DOCX）。
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Deep Research produces professional biomedical research reports for R&D, CMC/GMP, management, market, and investment topics.
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本项目**不涉及业务代码开发**，所有"代码"都是为**研究流水线**服务（如 Python runtime、ReportLab/Quarto 模板、下载脚本、信源 API 调用）。
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This repository is not an application codebase. Its code supports the research pipeline: Python runtime, search utilities, evidence schemas, citation checks, and PDF/DOCX rendering.
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### 1.1 v0.20 架构原则
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## Instruction Layers
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- `scripts/dr.py` 与 `scripts/runtime/*` 是核心编排真源；OpenCode、Codex、Claude Code、Antigravity、Gemini CLI 只是表层入口。
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- 模型选择以 `configs/models.yaml` 为准，由 Python runtime 解析 role/task 映射。
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- Skills 以 `.agents/skills` 为 canonical registry；adapter skill 目录由 `uv run python scripts/dr.py skills sync` 同步。
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- 默认工作链路为中文主写作；英文只保留在检索关键词、原文摘录、source title、DOI/URL 与来源笔记中。
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- Cross-tool baseline: `AGENTS.md`
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- Gemini / Antigravity override: `GEMINI.md`
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- Antigravity roles: `.agents/agents.md`
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- Antigravity strong rules: `.agents/rules/`
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- Reusable skills: `.agents/skills/`
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- Antigravity workflows: `.agents/workflows/`
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- Implementation plan and changelog: `PLAN.md`
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## 2. 研究方法论（所有 agent 必须遵循）
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If instructions conflict, use the more specific layer. For Antigravity, `GEMINI.md` and `.agents/rules/` override this file.
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### 2.1 麦肯锡核心原则
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## Operating Modes
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1. **研究方法适配场景**：MECE 是常用方法之一，但 GMP/CMC/管理咨询/研发立项等场景必须选择匹配框架
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2. **SCQA 叙事**（Situation → Complication → Question → Answer）：每章节开头用此结构引入
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3. **金字塔原理**：结论先行，论据支撑，纵向深入，横向 MECE
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4. **"每个标题即一个观点"**：标题不能是"概述""现状"这类模糊词，必须包含判断
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5. **So What? 自检**：每写完一段问自己"所以呢？"，若无则删
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Python-core mode:
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### 2.2 证据铁律
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- Use `scripts/dr.py`, `scripts/runtime/**`, `configs/models.yaml`, and `.agents/skills`.
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- Platform agents should call the Python CLI rather than reimplement worker orchestration.
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- Model routing is resolved by the Python runtime.
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- **每条结论至少 2 个独立 Tier 1-2 信源**佐证（见 §4 信源分级）
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- 达不到则**必须在正文注明**"该观点仅有 X 个来源支持，待进一步验证"
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- **反方证据优先**：每个 chapter 的研究必须主动搜索证伪性论点，不能只找支持证据
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- **数据可追溯**：所有数字、百分比、日期必须有来源 ID（如 `[src_042]`）
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Antigravity native mode:
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### 2.3 字数配额（硬要求）
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- Use `.agents/agents.md`, `.agents/rules/`, `.agents/skills/`, and `.agents/workflows/`.
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- Antigravity uses its own model quota for research execution.
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- Python scripts are auxiliary for scaffolding, local material processing, deterministic checks, citation/report rendering, and status.
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- Do not run Python model-worker commands such as `dr.py run`, `research --execute-packets`, or `research --assemble-chapters` unless the user explicitly approves external API/ZenMux usage.
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| 报告类型 | 最小字数 | 建议章节数 |
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| 综述类 | 10,000 字 | 8-10 章 |
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| 研究类 | 30,000 字 | 10-12 章 |
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| 投资报告 | 20,000 字 | 10-12 章 |
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| 管理/工艺类 | 15,000-25,000 字 | 9-11 章 |
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**字数分配原则**：
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- 每章字数差距不超过 ±30%（避免头重脚轻）
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- 每 section 最少 800 字（不够则合并）
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- 结论章不少于全文 10%
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### 2.4 报告不能只谈结论
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- 每个观点后必须紧跟**数据/事实/案例**佐证
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- 禁止空洞形容词（"巨大""快速""显著"）不带数据
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- 趋势判断必须给**量化依据**（年复合增长率、市场规模、成功率等）
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---
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## 3. Phase 工作流（4 阶段）
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### Phase 1：框架规划
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- **驱动命令**：`uv run python scripts/dr.py init <topic>` → `uv run python scripts/dr.py frame <slug>`（`/dr-init`、`/dr-frame` 只是薄封装）
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- **主导入口**：Python core 生成项目骨架与 framework；dr-plan 可作为表层访谈增强
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- **产出**：`phase1/material_brief.md` + `phase1/framework.md` + `phase1/research_brief.md/json`
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- **暂停点**：用户确认材料解读、研究方法、任务切分、检索策略和章节框架
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- **硬规则**：clarification 不只是问范围；必须固化报告用途、基调、成功标准、任务拆分、每个任务轴的 prompt/skills/search route，让低成本 worker 也能独立执行
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### Phase 2：深度研究
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- **驱动命令**：`uv run python scripts/dr.py research <slug> --workers 6`
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- **主导入口**：Python core 生成 task cards 并控制并发
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- **产出**：`phase2/task_cards.json` + `packets/*.json` + `sources.jsonl` + `chapter_briefs/*.json` + `compressed_findings/*.json` + `drafts/chXX.md`
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- **不暂停**：全自动跑完
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- **防碎片化规则**：并发 worker 只写 evidence packet；`--build-briefs` 必须先收束为 chapter brief 和 compressed finding；章节正文必须从 compressed finding 写，不得把 packet 按顺序拼贴成报告
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### Phase 3：总编审校
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- **驱动命令**：`uv run python scripts/dr.py review <slug>`（`/dr-review` 只是薄封装）
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- **主导入口**：Python core deterministic review；dr-chief-editor/Gemini 可作为后续深度审校增强
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- **产出**：`projects/<slug>/phase3/critique.md`
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- **暂停点**：用户决策（修正 / 回炉 phase2 / 整体重来）
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### Phase 4：成稿
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- **驱动命令**：`uv run python scripts/dr.py finalize <slug>`
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- **主导入口**：Python core 中文原生成稿；OpenCode/Codex/Claude Code 只调用 CLI
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- **默认链路**：final_zh.md → glossary/check(optional) → polish(optional) → citation_check → build_report
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- **兼容链路**：仅显式 `--legacy-translate` 时使用 final_en.md → translate → polish
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- **产出**：`phase4/final_zh.md` + `phase4/final_zh_polished.md`（可选）+ `phase4/*.pdf` + `phase4/*.docx`
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---
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## 4. 信源分级（Tier 系统）
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### Tier 1 — 一级信源（优先使用，评分权重 × 1.2）
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- **一手学术文献**：PubMed、Cochrane、顶刊原文（NEJM / Lancet / Nature / Science / Cell / JAMA）
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- **监管机构公告**：FDA、EMA、NMPA、PMDA 官网及 openFDA
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- **临床试验注册**：ClinicalTrials.gov、ChiCTR
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- **专利原文**：USPTO、EPO、CNIPA、Google Patents
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- **上市公司披露**：SEC 10-K/10-Q、招股书、交易所年报
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### Tier 2 — 二级信源（可用，标准权重）
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- **权威咨询报告**：麦肯锡、BCG、德勤、IQVIA、EvaluatePharma、弗若斯特沙利文
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- **学术综述**：系统综述（Systematic Review）、Meta 分析
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- **行业协会**：PhRMA、BIO、中国医药工业协会
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- **专业数据库**：Wind、东方财富、同花顺（金融侧）
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- **专业媒体**：BioSpace、Endpoints News、FiercePharma、医药魔方、Insight 数据库
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### Tier 3 — 三级信源（辅助，不得作为唯一支撑）
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- **预印本**：bioRxiv、medRxiv（需标注"未经同行评审"）
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- **券商研报**：中金、中信、高盛生物医药团队（需注意利益冲突）
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- **会议摘要**：AACR、ASCO、ASH 会议摘要（数据可能未完整发表）
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- **企业白皮书**（注明来源，降权使用）
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### Tier 4 — 四级信源（仅做发现入口）
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- Tavily / Brave / Exa 通用搜索返回的**普通网页**
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- 一般新闻报道
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- Wikipedia（**只做术语理解入口，结论不得引用**）
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### 黑名单（禁用）
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- 纯新闻聚合站（百家号、头条号、部分自媒体公众号）
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- 未署名作者的行业博客
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- 被 Retraction Watch 标记为撤稿的论文
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- 明显软文/PR 稿（如"某某 CEO 表示..."而无实质数据）
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- 超过 5 年的综述（除机制类研究可放宽）
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### 信源评分（0-10）
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每个进入 `sources.jsonl` 的信源必须打分，维度：
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- 权威性（期刊 IF、机构排名）0-3
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- 时效性（≤3 年满分，每老 1 年 -0.5） 0-2
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- 一手性（一手 > 综述 > 二次解读） 0-2
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- 可验证性（有 DOI / URL / 原始数据） 0-2
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- 利益冲突（厂商自发 -1） 0-1
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**硬规则**：评分 < 5 的信源不得作为结论唯一支撑。
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---
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## 5. Python Role / Task 模型
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平台 agent 文件只保留兼容和展示意义；真实角色、任务类型、模型、温度、并发上限以 Python runtime 为准。
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查看当前模型配置：
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## Core Commands
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```bash
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uv run python scripts/dr.py models --profile medium
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uv run python scripts/dr.py models --profile medium --json
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uv run python scripts/dr.py methods list
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uv run python scripts/dr.py init "研究主题" --slug <slug> --method <method>
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uv run python scripts/dr.py frame <slug>
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uv run python scripts/dr.py research <slug> --workers 6 --execute-packets
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uv run python scripts/dr.py review <slug>
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uv run python scripts/dr.py finalize <slug>
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uv run python scripts/deploy_adapters.py antigravity --target /path/to/workspace --dry-run
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```
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核心任务类型：
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## Research Integrity
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| Task type | 默认角色 | 用途 |
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| `source_discovery` | `dr_searcher` | 轻量信源发现 |
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| `evidence_packet` | `dr_analyst` | task card → evidence packet |
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| `chapter_assembly` | `dr_analyst` | chapter brief → 中文章节 |
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| `counter_verification` | `dr_verifier` | 反方证据与交叉模型验证 |
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| `phase3_review` | `dr_chief_editor` | 总编审校 |
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| `final_editorial` | `dr_editor_in_chief` | 中文终稿统稿 |
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| `report_render` | `dr_reporter` | PDF/DOCX 渲染 |
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- No fabricated data, URLs, DOIs, clinical results, regulatory status, patents, or market figures.
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- No factual claim without a source ID or a clearly marked "to verify" status.
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- No claim that a search or verification was performed unless there is a real tool receipt or search log.
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- Search snippets, AI summaries, and model memory are discovery leads, not final evidence.
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- Every major conclusion needs at least two independent Tier 1-2 sources. If not available, downgrade and mark uncertainty.
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- Counter-evidence is mandatory. Do not collect only supporting evidence.
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- Wikipedia is allowed for orientation only and must not support final conclusions.
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- Use Chinese for formal report writing. English may remain in search keywords, titles, DOI/URL, original excerpts, and raw notes.
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默认策略：
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## Method Selection
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- Codex/GPT 系列适合代码、schema、回归、review。
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- Claude/Opus/Sonnet 适合长文结构、中文表达、访谈增强。
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- Gemini 适合长上下文审校、多模态材料、替代框架评估。
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- ZenMux 混合模型仍由 `configs/models.yaml` 统一管理，平台当前会话模型不得覆盖 Python role/task 映射。
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Do not default to McKinsey/MECE for every topic.
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## 6. Platform Adapter 调用方式
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Choose the research method and tools based on the user's scenario. Use `.agents/skills/method-selection/SKILL.md` for Antigravity native work and `configs/research_methods.yaml` for Python-core mode.
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详见 `docs/platform-adapters.md`。摘要如下：
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## Source Quality
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| Platform | 项目指令/命令位置 | 推荐调用 |
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| OpenCode | `.opencode/commands/*.md` | `/dr-run <slug-or-topic>` |
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| Codex | `AGENTS.md` + `$CODEX_HOME` adapter（由 `scripts/deploy_adapters.py codex` 部署） | `uv run python scripts/dr.py ...` 或 `codex exec "$(uv run python scripts/dr.py prompt dr-run '<topic>')"` |
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| Claude Code | `.claude/skills/*/SKILL.md` | `/dr-run <slug-or-topic>` |
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| Gemini CLI | `GEMINI.md` + `.gemini/commands/dr/*.toml` | `/dr:run <slug-or-topic>` |
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| Antigravity | `.agents/agents.md` + `.agents/rules` + `.agents/skills` + `.agents/workflows` | 角色定义在 agents，强约束在 rules，技能在 skills，流程在 workflows |
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Detailed scoring belongs in `.agents/skills/source-quality/SKILL.md`.
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跨平台硬规则：
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Baseline tiers:
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- 除 Antigravity native 模式外，平台只做 surface adapter，不承载核心调度。
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- Antigravity 的角色定义放在 `.agents/agents.md`；不要把角色、技能和流程继续堆进本文件。
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- 不在平台 prompt 中手工并发写章节。
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- 不把平台 subagent 当默认并发机制。
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- 真实并发由 `scripts/runtime/workers.py` 的 worker pool 执行。
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- 真实模型选择由 `configs/models.yaml` 和 `scripts/runtime/roles.py` 执行。
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- 信息检索默认走 `scripts/search.py` / `SearchClient` / `search-gateway` skill；不得把 Tavily MCP、browser MCP 或平台 web search 作为默认路径，除非用户明确授权。
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- 搜索路由必须按任务类型选择：`evidence`=Exa highlights 受控证据发现，`fda/scholar/patents/news`=专用信源路径，`general`=宽泛发现和兜底；Tavily Research 只能作为阶段性 scan/enrichment/rework 输入，不能直接替代 evidence packet 或章节正文。
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- Tier 1: original academic papers, systematic reviews where appropriate, regulator documents, clinical trial registries, patents, company filings.
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- Tier 2: authoritative consulting/industry reports, industry associations, reputable professional media and databases.
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- Tier 3: preprints, conference abstracts, brokerage research, company white papers. Use with caution.
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- Tier 4: general web pages, ordinary news, Wikipedia. Discovery only.
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---
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## Safety
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## 7. 目录约定
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- Keep API keys only in `secrets.env`; never hardcode or commit secrets.
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- Do not read or expose secrets unless the user explicitly asks.
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- Do not overwrite user settings or existing workspace rule/skill/workflow files unless the user asks for `--force`.
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- Do not run destructive git commands such as `git reset --hard`, `git clean`, or broad file deletion without explicit approval.
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- Do not write outside the current workspace unless the user explicitly approves.
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- 每个研究主题放在 `projects/<topic-slug>/`，slug 用小写+连字符，如 `glp1-r-agonist-market-2026`
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- 所有中间产物（drafts、evidence、sources.jsonl）均为 Markdown 或 JSONL，便于 diff 与版本控制
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- `archive/` 存放已完成或废弃的研究，不再主动维护
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## Change Management
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---
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## 8. 安全与权限
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- API 密钥**只存** `secrets.env`（已入 gitignore），禁止硬编码到任何 agent/skill/command
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- 字体文件（~140MB）不入 git，通过 `download-fonts.sh` 获取
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- `bash` 权限默认 `ask`，仅允许 `python *` / `pandoc *` / `ls *` / `cat *` / `curl *` 自动执行
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---
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|
||||
## 9. 如何判断是否走了 Python Core
|
||||
|
||||
不要用“平台是否 spawn subagent”作为成功标准。Python-core 模式的验证锚点是 Python runtime 产物：
|
||||
|
||||
1. `uv run python scripts/dr.py status <slug>` 能看到 phase 状态。
|
||||
2. Phase 2 存在 `phase2/task_cards.json`。
|
||||
3. Phase 1 存在 `phase1/research_brief.md` 和 `phase1/research_brief.json`。
|
||||
4. `--execute-packets` 后存在 `phase2/packets/*.json` 和必要时的 `phase2/packet_errors/*.json`。
|
||||
5. `--build-briefs` 后存在 `phase2/chapter_briefs/*.json` 与 `phase2/compressed_findings/*.json`。
|
||||
6. `--assemble-chapters` 后存在 `phase2/drafts/chXX.md` 和必要时的 `phase2/chapter_errors/*.json`。
|
||||
7. `scripts/v020_regression.py` 输出 `v0.20 regression PASS`。
|
||||
|
||||
Antigravity native 模式的验收锚点由 `.agents/workflows/deep-research-native.md` 定义。
|
||||
|
||||
---
|
||||
|
||||
## 10. 禁止事项（negative instructions）
|
||||
|
||||
所有 agent 均禁止：
|
||||
|
||||
1. ❌ 引用 Wikipedia 作为结论支撑（仅做术语理解）
|
||||
2. ❌ 在缺乏 2 个独立信源时仍给出绝对化结论
|
||||
3. ❌ 使用"据报道""有专家认为"等未指明来源的表述
|
||||
4. ❌ 编造或虚构数据、URL、DOI
|
||||
5. ❌ 声称"已搜索/已验证/官网显示"但没有工具回执和检索记录
|
||||
6. ❌ 用搜索摘要、AI summary、snippet 冒充原文证据
|
||||
7. ❌ 写空洞的套话（"随着科技的发展""在大数据时代"）
|
||||
8. ❌ 忽略反方观点，只收集支持证据
|
||||
9. ❌ 对输出字数"打折"（综述 <10000 字、研究 <30000 字必须返工）
|
||||
10. ❌ 在正文中使用未在术语表中定义的专业缩写（首次出现需全称+缩写）
|
||||
|
||||
---
|
||||
|
||||
## 11. 变更管理
|
||||
|
||||
- 本文件与 `PLAN.md` 是**双核**：PLAN.md 管实施进度与架构，AGENTS.md 管运行时规则
|
||||
- 修改本文件需同步更新 PLAN.md 的"变更记录"段
|
||||
- 所有 agent/skill 新增或重大调整必须在 PLAN.md §8 清单中标记完成状态
|
||||
- Treat `AGENTS.md`, `GEMINI.md`, `.agents/**`, and `PLAN.md` as production configuration.
|
||||
- Keep root rules short. Move roles to `.agents/agents.md`, constraints to `.agents/rules`, capabilities to `.agents/skills`, and phase sequencing to `.agents/workflows`.
|
||||
- When changing runtime rules or adapter behavior, update `PLAN.md` changelog.
|
||||
|
||||
Reference in New Issue
Block a user