generating-docs
Generates README.md and DESIGN.md scaffolds by analyzing module structure. Use when creating documentation templates for new modules. Automatically triggered at module creation.
git clone --depth 1 https://github.com/telagod/code-abyss /tmp/generating-docs && cp -r /tmp/generating-docs/skills/generating-docs ~/.claude/skills/generating-docsSKILL.md
# 造典关卡 · 文档生成器
> 生成的是骨架，不是答案。**填决策理由是人的工作，工具不能代劳。**
## 何时使用
| 场景 | 跑 | 理由 |
|------|------|------|
| 新模块创建后第一时间 | ✅ | 趁记忆新鲜填决策 |
| [verifying-modules](../verifying-modules/SKILL.md) 报「缺 README/DESIGN」 | ✅ | 直接补救 |
| 重构后边界变化 | ⚠ | 看是否要重生成或手动改；**不要 `--force` 覆盖已有内容** |
| 已有完整文档 | ❌ | 不要破坏人工写的内容 |
## 生成内容
### README.md（自动可填部分）
| 字段 | 自动来源 | 待人补 |
|------|----------|--------|
| 模块名 | 目录名 | 是否有更好的展示名 |
| 描述 | 顶级 docstring（Python） | 「存在理由」必须人写 |
| 特性 | TODO（占位） | 列 3–5 个核心能力 |
| 依赖 | `requirements.txt` / `package.json` / `Cargo.toml` 等 | 是否有运行时假设 |
| 使用方法 | TODO（占位） | 5 分钟跑通示例 |
| API 概览 | 公开类/函数签名 | 调用顺序、生命周期 |
| 目录结构 | `tree` 输出 | — |
### DESIGN.md（骨架占位）
| 字段 | 自动 | 待人补（最重要） |
|------|------|------------------|
| 设计目标 / 非目标 | TODO | **核心决策驱动力** |
| 架构 | TODO | 含一张图最好 |
| 核心组件 | 公开类/函数列表 | 各组件的协作关系 |
| 决策表 | TODO | **方案对比 + 选择理由** |
| 技术选型 | 依赖列表 | 选 X 不选 Y 的理由 |
| 权衡 | TODO | 牺牲了什么 |
| 安全考量 | TODO | 信任边界、威胁模型 |
## 语言支持
| 语言 | 提取深度 |
|------|----------|
| Python | 类、函数、docstring、依赖（最完整） |
| Go / TypeScript / Rust | 目录结构 + 依赖 |
| 其他 | 基础目录结构 |
## 流程
```
doc_generator.js 生成骨架
↓
人工填 TODO（决策理由、使用示例、非目标）
↓
verify-module 校验完整性
↓
通过则提交
```
## 何时不要 `--force`
- **目标文件已有人工内容** —— `--force` 会无差别覆盖。先 diff 旧版，手动合并。
- **CI 环境** —— 生成应在开发机做，CI 只校验，不生成。
## 与其他 skill 联动
- 跑完后 → 必跑 [verifying-modules](../verifying-modules/SKILL.md)
- 大模块 → 拆分前先 [designing-architectures](../designing-architectures/SKILL.md) 想清楚边界
## 使用
```bash
node scripts/doc_generator.js <模块路径>
node scripts/doc_generator.js <模块路径> --force # 强制覆盖（慎用）
node scripts/doc_generator.js <模块路径> --json # CI 用
```
## 收口
工具给骨架，**TODO 不补完不算交付**。生成后 5 分钟内人工填决策；超过 1 天会忘原因，文档质量陡降。Analyzes code changes, detects documentation drift, and evaluates change impact scope. Use when reviewing diffs, checking doc sync, or running pre-commit analysis. Automatically triggered after design-level changes or refactoring.
Scans code for security vulnerabilities, detects dangerous patterns, and ensures security decisions are documented. Use when running security scans, auditing code, or checking for OWASP issues, injection risks, or sensitive data leaks. Automatically triggered on new modules, security-related changes, or post-refactor.
Processes Excel spreadsheet files (.xlsx, .xlsm, .csv). Creates workbooks, builds formulas, preserves formatting, analyzes tabular data, and validates financial models with zero-formula-error delivery. Use when working with spreadsheet files or tabular data analysis. Do NOT use for Word documents, PDFs, presentations, or database pipelines.
Frontend UI design system selector and implementation guide covering Glassmorphism, Liquid Glass (Apple-style), Neubrutalism, and Claymorphism. Use when building UI components, choosing a visual aesthetic, implementing design tokens, or auditing accessibility/contrast on themed surfaces. Provides per-style tokens, component patterns, dark mode, and a11y constraints.
安全架构与治理：威胁建模 (STRIDE/PASTA/LINDDUN)、零信任身份架构、IAM/SSO/MFA/PAM、合规框架 (SOC2/PCI/HIPAA/GDPR)、DLP、隐私工程、安全控制设计。Use when designing security architecture, threat modeling new systems, implementing zero-trust identity, designing IAM/SSO/PAM, building compliance evidence chains, or planning privacy-by-design.
DevOps knowledge reference covering Git workflows, testing strategies, DevSecOps, release pipeline orchestration (release.yml, multi-arch images, cosign integration), CI/CD pipelines, database management, observability, and performance optimization. Use when working with Git, CI/CD, release pipelines, ghcr image publishing, testing, monitoring, or infrastructure automation.
AI agent and LLM system engineering reference covering single-agent dev (ReAct, tool calling, plan-execute), multi-agent coordination (swarm, role decomposition, file locking), LLM security (prompt injection, jailbreak defense, output filtering), RAG architecture (chunking, hybrid retrieval, rerank), and prompt engineering / evaluation (RAGAS, LLM-as-Judge). Use when building AI agents, designing RAG pipelines, orchestrating multi-agent workflows, hardening LLM apps, or writing prompts.
Checks code quality metrics including complexity, duplication, naming conventions, and function length. Use when running quality gates, reviewing code smells, or checking lint rules. Automatically triggered on complex modules or post-refactor.