verifying-modules
Scans directory structure, detects missing documentation, and verifies code-doc synchronization. Use when checking module completeness, README presence, or DESIGN.md alignment. Automatically triggered after creating new modules.
git clone --depth 1 https://github.com/telagod/code-abyss /tmp/verifying-modules && cp -r /tmp/verifying-modules/skills/verifying-modules ~/.claude/skills/verifying-modulesSKILL.md
# 模块完整性校验关卡 > 文档不齐不算交付。模块是否能被外人独立理解,是「完成」的最低门槛。 ## 何时使用 | 场景 | 跑 | 理由 | |------|------|------| | 新建模块 | ✅ 必跑 | 阻断「无文档落地」 | | 模块重构(边界变化) | ✅ | 文档随边界更新 | | 接收他人模块 | ✅ | 检查可理解性 | | 提交前(涉及模块新增) | ✅ | 最后闸 | | 仅函数级修改 | ❌ | 走 [analyzing-changes](../analyzing-changes/SKILL.md) 即可 | ## 必备文件 | 文件 | 缺失后果 | 备注 | |------|----------|------| | `README.md` | 阻断交付 | 用户视角 | | `DESIGN.md` | 阻断交付 | 维护者视角 | | `tests/` | 警告 | 单文件模块或纯类型声明可豁免 | | `__init__.py` | 提示(仅 Python) | 视项目布局而定 | ## 文档要求 ### README(外部视角,回答「这是什么、怎么用」) - 模块名与定位 - 存在理由(解决什么问题,**不是**列功能清单) - 核心职责(一句话) - 依赖关系(上游:依赖什么;下游:被谁依赖) - 快速使用示例(5 分钟跑通) ### DESIGN(内部视角,回答「为什么这样设计」) - 设计目标(含非目标) - 方案选择与理由(对比 ≥2 选项) - 关键决策(含权衡) - 已知限制 - 变更历史(重大设计调整) ## 何时豁免 - **生成代码模块**(protobuf、OpenAPI client 等)→ 顶级 README 提一句即可,无需 DESIGN - **配置/数据模块**(fixtures、seed data)→ README 说明用途与字段含义即可 - **私有 utility**(`_internal/`、`internal/`)→ README 简化,DESIGN 可缺 ## 与其他 skill 联动 - 缺文档 → 用 [generating-docs](../generating-docs/SKILL.md) 生成骨架,再人工填决策 - 通过后 → 串 [analyzing-security](../analyzing-security/SKILL.md) 扫新增攻击面 - 大改后 → 串 [analyzing-changes](../analyzing-changes/SKILL.md) 看辐射面 ## 使用 ```bash node scripts/module_scanner.js <模块路径> node scripts/module_scanner.js <模块路径> -v # 详细 node scripts/module_scanner.js <模块路径> --json # CI 用 ``` ## 收口 阻断项必修。警告项可在 DESIGN 留「不写测试的理由」(如纯接口声明、纯常量)。**「以后补」不算理由。**
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.