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Agent Skill · 研究检索

ai-codebase-deep-modules(ai 代码库深度模块)

ai-codebase-deep-modules 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ai-codebase-deep-modules 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 43,660。

总安装 970周安装 40GitHub Stars 公开资料未说明下载 317核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ai-codebase-deep-modules(ai 代码库深度模块)
来源仓库:https://github.com/tristanmanchester/agent-skills
仓库路径:skills/ai-codebase-deep-modules
安装命令:
npx skills add https://github.com/tristanmanchester/agent-skills --skill ai-codebase-deep-modules
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/tristanmanchester/agent-skills --skill ai-codebase-deep-modules

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

ai-codebase-deep-modules 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。适用于代码库深度分析、模块依赖梳理或架构研究等开发场景。通过关键词和代码库路径,快速定位相关模块或功能点信息。

安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。可结合来源仓库、安装命令和原始 README 继续核验具体用法和功能边界。

来源仓库内路径:skills/ai-codebase-deep-modules

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/tristanmanchester/agent-skills --skill ai-code…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ai-codebase-deep-modules 怎么安装?

在终端执行 npx skills add https://github.com/tristanmanchester/agent-skills --skill ai-codebase-deep-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ai-codebase-deep-modules 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ai-codebase-deep-modules 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

ai-codebase-deep-modules 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

ai-codebase-deep-modules 用的人多吗?

公开数据是累计安装 970 次,近一周安装 40 次,下载 317 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ai-codebase-deep-modules 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ai-codebase-deep-modules

ai 代码库深度模块 · 本页

970—需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

AI Codebase Deep Modules

Turn “a web of shallow, cross-importing files” into a codebase that is easy for AI (and humans) to navigate, change, and test.

This skill is built around four ideas:

  1. The codebase matters more than the prompt. AI struggles when feedback is slow, structure is unclear, and dependencies are tangled.
  2. Match the filesystem to the mental model. Group code the way you *think* about it (features/domains/services), not as a grab-bag of utilities.
  3. Prefer deep modules. Lots of implementation behind a small, well-designed public interface.
  4. Treat deep modules as greyboxes. Lock behaviour with tests at the boundary; internal code becomes replaceable.

When to use this skill

Use this skill when the user wants any of the following:

  • Refactor an existing repo to be more navigable and safer for AI-assisted coding
  • Introduce/strengthen module boundaries, reduce coupling, or eliminate “spaghetti imports”
  • Restructure the repo by feature/domain (a “map you hold in your head” reflected on disk)
  • Define service/module interfaces, public APIs, and “only import from here” rules
  • Build fast feedback loops (tests, typecheck, lint) so AI can verify changes quickly
  • Plan a refactor with incremental steps, acceptance criteria, and tests

Do not use this skill for:

  • One-off debugging of an isolated error (use normal debugging / code review)
  • Purely stylistic refactors with no boundary or testing implications
  • Writing greenfield code where the user already has a clear modular architecture (unless they want a module template)

Inputs this skill expects (minimal)

If available, ask for or infer:

  • Language/runtime (TS/JS, Python, Go, Java/Kotlin, etc.)
  • How to run the fastest meaningful check (unit tests, typecheck, lint, build)
  • The top 3–7 “chunks” of product behaviour (domains/features/services)
  • Any hard constraints (monorepo tooling, existing packages, deployment boundaries)

If the user hasn’t provided this, do not stall. Make best-effort guesses by inspecting:

  • package.json, pyproject.toml, go.mod, pom.xml, build.gradle, Makefile, justfile
  • src/, app/, packages/, services/, modules/
  • existing test folders and CI configs

Workflow

Step 0 — Establish the feedback loop (non-negotiable)

Goal: ensure there is a fast “did it work?” loop before and during refactors.

  1. Identify the quickest command that provides signal:

- Typecheck: tsc -p tsconfig.json - Unit tests: npm test, pytest -q, go test./... - Lint: eslint., ruff check, golangci-lint run

  1. Prefer a single “verify” entrypoint:

- make verify, just verify, npm run verify, ./scripts/verify.sh

  1. If tests are missing, propose the smallest viable starting point:

- Smoke tests for core flows - Contract tests for the boundaries you’re about to introduce

  1. If the loop is slow, propose speed-ups *before* large refactors:

- Run only impacted packages - Split unit vs integration tests - Cache dependencies in CI

Deliverable: a short “Feedback loop” section with the exact commands and expected outputs.

Step 1 — Reconstruct the mental map of the codebase

Goal: identify the natural groupings that already exist in the product.

  1. List the product domains/features (aim for 3–10):

- e.g. auth, billing, thumbnail-editor, video-editor, cms-forms

  1. For each domain, identify:

- entrypoints (routes/controllers/handlers) - data boundaries (models/schemas) - external dependencies (APIs, DB, queues)

  1. Capture the current pain:

- “Where do people get lost?” - “What breaks when we change X?” - “Where are imports crossing domains?”

Deliverable: a Module Map (table) with: domain, responsibilities, key files, current coupling risks.

Step 2 — Design deep modules (few, chunky, stable interfaces)

Goal: reduce the number of things the agent must keep in working memory.

For each domain/module candidate:

  1. Define the public interface (small surface area):

- functions/classes/commands exposed - public types/data contracts - error/edge-case semantics

  1. Define what is explicitly internal:

- helper functions, adapters, DB queries, parsing, etc.

  1. Decide the dependency direction:

- Prefer: domain → shared primitives - Avoid: domain ↔ domain cross-imports

  1. Keep the interface boring and predictable:

- stable names - minimal parameters - explicit return types / result objects

Deliverable: an Interface Spec for each deep module:

  • Public API (signatures)
  • Invariants (pre/post conditions)
  • Examples (happy path + one edge case)

See: references/module-templates.md

Step 3 — Align the filesystem to the map (progressive disclosure)

Goal: make it obvious where to look.

Default rule: outside code imports only from a module’s public entrypoint.

Recommended structure (adapt per language):

  • src/<module>/

- index.* (public exports) - types.* (public types) - internal/ (implementation details; not imported from outside) - __tests__/ or tests/ (contract tests for the public API)

If the repo uses packages, prefer packages/<module>/ with explicit exports.

Deliverable: a “Move plan” listing:

  • directories to create
  • files to move
  • import paths to update
  • temporary compatibility shims (if needed)

Step 4 — Make modules greyboxes with boundary tests

Goal: you shouldn’t need to understand internals to trust behaviour.

  1. Write/identify contract tests for each module’s public API:

- behavioural checks - key error cases - side effects (DB writes, events emitted) via fakes/spies

  1. Keep tests close to the interface:

- treat internals as replaceable

  1. Only add internal unit tests where:

- performance-critical logic needs tight coverage - tricky algorithms deserve direct tests

Deliverable: test plan + initial contract test skeletons.

See: references/testing-and-feedback.md

Step 5 — Enforce boundaries (so the architecture stays true)

Goal: prevent the codebase from drifting back into a web.

Pick the lightest viable enforcement:

  • Conventions + code review (baseline)
  • Lint rules (TS/JS: no-restricted-imports, ESLint boundary plugins)
  • Architecture tests (assert “module A cannot import module B”)
  • Language-level boundaries (Go internal/, Rust pub(crate), Java modules)

Deliverable: an “Enforcement” section with the exact rules and where to configure them.

See: references/boundary-enforcement.md

Step 6 — Refactor incrementally (strangler pattern)

Goal: avoid giant-bang rewrites.

Suggested sequence:

  1. Create the new module folder and public interface (empty implementation).
  2. Add contract tests (they will fail).
  3. Add a thin adapter that wraps existing code (tests pass).
  4. Move internals gradually behind the interface:

- keep exports stable - delete old entrypoints only once usage is migrated

  1. Repeat module-by-module.

Deliverable: a stepwise refactor plan with checkpoints and rollback options.


Output format (what to produce)

When this skill is activated, produce a structured plan using this outline:

  1. Current state summary (1–2 paragraphs)
  2. Fast feedback loop (exact commands)
  3. Module Map (table)
  4. Proposed deep modules (list + responsibilities)
  5. Interface specs (per module)
  6. Filesystem changes (move plan)
  7. Boundary enforcement (rules + tooling)
  8. Testing strategy (contract tests first)
  9. Incremental migration steps (with checkpoints)

Optional: copy the template from assets/architecture-plan-template.md.


Examples

Example 1 — Broad request

User says: “Make our TypeScript monorepo more AI-friendly. It’s hard to find things and tests are slow.”

Actions:

  1. Identify verify loop (typecheck + unit tests) and how to run it per package.
  2. Produce a module map (3–7 modules).
  3. Propose deep modules with a clear public interface (index.ts, types.ts).
  4. Recommend boundary enforcement via ESLint no-restricted-imports.
  5. Add contract tests for each module.

Result: a concrete refactor plan and initial skeletons that can be executed incrementally.

Example 2 — Specific boundary problem

User says: “Auth imports billing and billing imports auth. We keep breaking things.”

Actions:

  1. Identify dependency cycle and why it exists (shared types? shared DB code?).
  2. Extract a deep module interface boundary:

- auth exports getCurrentUser(), requireAuth() - billing depends on those interfaces only (no deep imports)

  1. Move shared primitives into shared/ or platform/ module.
  2. Add an architecture rule to prevent the cycle returning.

Result: cycle removed, boundaries enforced, behaviour locked by tests.


Troubleshooting

Skill feels too “high level”

Use the template and references to get concrete:

Refactor is risky / unknown behaviour

Prioritise greybox contract tests first:

  • freeze behaviour at the public interface
  • only then move internals

Boundaries are hard to enforce in TS/JS

Start with lint rules and path conventions; add architecture tests if needed. See: references/boundary-enforcement.md

平台分布

Codex

34.49%
按下载量换算109

Claude

32%
按下载量换算101

Cursor

18.05%
按下载量换算57

Gemini CLI

9.3%
按下载量换算29

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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