Token导航 LogoToken导航TokenDH.com
效率需要联网clawhub未标认证来源可访问clear审计提醒

ai-codebase-deep-modulesai 代码库深度模块

Agent Skill

ai-codebase-deep-modules 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

总安装

14,566

周安装

595

GitHub Stars

公开资料未说明

下载量

4,665
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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/ai-codebase-deep-modules
安装命令:
openclaw skills install 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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install ai-codebase-deep-modules

简介

通过将文件系统与域/功能边界对齐、使用 sm 创建深度(灰盒)模块,设计和重构软件代码库,使其对 AI 友好。

SKILL.md

name
ai-codebase-deep-modules
description
>-
compatibility
Works in skills-compatible coding assistants with repository file access. Optional scripts require Python 3.
metadata
author
generated-from-transcript
version
1.0.0

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

88.33%
按下载量换算4,121

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills