Agent skill

Codebase Onboarding

by affaan-m in affaan-m/ECC

分析一个陌生的代码库,并生成一个结构化的入门指南,包括架构图、关键入口点、规范和一个起始的CLAUDE.md文件。适用于加入新项目或首次在代码仓库中设置Claude Code时。

MITAuto-check passedDevelopment

Install Codebase Onboarding

skills CLI
$ npx skills add affaan-m/ECC --skill codebase-onboarding -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC codebase-onboarding --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/zh-CN/skills/codebase-onboarding .claude/skills/codebase-onboarding && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
codebase-onboarding
GitHub stars
275k
Used in
1 other repo
Token cost
~1.1k tokens
SKILL.md length
151 words
Files
1
Skills in repo
645
Repo updated
First seen
Licence
MIT

At a glance

分析一个陌生的代码库,并生成一个结构化的入门指南,包括架构图、关键入口点、规范和一个起始的CLAUDE.md文件。适用于加入新项目或首次在代码仓库中设置Claude Code时。

  • Works in 5 steps: 不要通读所有内容 —— 侦察阶段应使用 Glob 和… → 验证而非猜测 ——… → 尊重现有的 CLAUDE.md ——… → …
  • Tasks that involve Codebase onboarding
  • SKILL.md covers 使用时机, 工作原理, 最佳实践 and 应避免的反模式, plus 1 more section
  • Calls git

What it does

Codebase Onboarding is an agent skill from affaan-m/ECC. 分析一个陌生的代码库,并生成一个结构化的入门指南,包括架构图、关键入口点、规范和一个起始的CLAUDE.md文件。适用于加入新项目或首次在代码仓库中设置Claude Code时。

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Codebase onboarding and Agent instruction files. It works with Git. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • Tasks that involve Codebase onboarding
  • Tasks that involve Agent instruction files

Example prompts

  • “/codebase-onboarding”

Requirements

  • Node.js
  • Docker

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. 不要通读所有内容 —— 侦察阶段应使用 Glob 和 Grep,而非读取每个文件。仅在信号不明确时有选择性地读取。
  2. 验证而非猜测 —— 如果从配置文件中检测到某个框架,但实际代码使用了不同的东西,请以代码为准。
  3. 尊重现有的 CLAUDE.md —— 如果文件已存在,请增强它而不是替换它。明确标注哪些是新增内容,哪些是原有内容。
  4. 保持简洁 —— 入门指南应在 2 分钟内可快速浏览。细节应留在代码中,而非指南里。
  5. 标记未知项 —— 如果无法自信地检测到某个规范,请如实说明而非猜测。“无法确定测试运行器”比给出错误答案更好。

What it can do on your machine

Read from SKILL.md and the folder at commit ef648e0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Codebase Onboarding loads about 1.1k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 151 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~27
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit ef648e0, republished under its MIT licence (© affaan-m). 151 words, ~1,145 tokens.

Download SKILL.mdSave it as .claude/skills/codebase-onboarding/SKILL.md (or your agent's skills folder).
name
codebase-onboarding
description
分析一个陌生的代码库,并生成一个结构化的入门指南,包括架构图、关键入口点、规范和一个起始的CLAUDE.md文件。适用于加入新项目或首次在代码仓库中设置Claude Code时。
origin
ECC

代码库入门引导

系统性地分析一个不熟悉的代码库,并生成结构化的入门指南。专为加入新项目的开发者或首次在现有仓库中设置 Claude Code 的用户设计。

使用时机

  • 首次使用 Claude Code 打开项目时
  • 加入新团队或新仓库时
  • 用户询问“帮我理解这个代码库”
  • 用户要求为项目生成 CLAUDE.md 文件
  • 用户说“带我入门”或“带我浏览这个仓库”

工作原理

阶段 1:初步侦察

在不阅读每个文件的情况下,收集关于项目的原始信息。并行运行以下检查:

1. 包清单检测
   → package.json、go.mod、Cargo.toml、pyproject.toml、pom.xml、build.gradle、
     Gemfile、composer.json、mix.exs、pubspec.yaml

2. 框架指纹识别
   → next.config.*、nuxt.config.*、angular.json、vite.config.*、
     django 设置、flask 应用工厂、fastapi 主程序、rails 配置

3. 入口点识别
   → main.*、index.*、app.*、server.*、cmd/、src/main/

4. 目录结构快照
   → 目录树的前 2 层,忽略 node_modules、vendor、
     .git、dist、build、__pycache__、.next

5. 配置与工具检测
   → .eslintrc*、.prettierrc*、tsconfig.json、Makefile、Dockerfile、
     docker-compose*、.github/workflows/、.env.example、CI 配置

6. 测试结构检测
   → tests/、test/、__tests__/、*_test.go、*.spec.ts、*.test.js、
     pytest.ini、jest.config.*、vitest.config.*
阶段 2:架构映射

根据侦察数据,识别:

技术栈

  • 语言及版本限制
  • 框架及主要库
  • 数据库及 ORM
  • 构建工具和打包器
  • CI/CD 平台

架构模式

  • 单体、单体仓库、微服务,还是无服务器
  • 前端/后端分离,还是全栈
  • API 风格:REST、GraphQL、gRPC、tRPC

关键目录 将顶级目录映射到其用途:

<!-- Example for a React project — replace with detected directories -->
src/components/  → React UI 组件
src/api/         → API 路由处理程序
src/lib/         → 共享工具库
src/db/          → 数据库模型和迁移文件
tests/           → 测试套件
scripts/         → 构建和部署脚本

数据流 追踪一个请求从入口到响应的路径:

  • 请求从哪里进入?(路由器、处理器、控制器)
  • 如何进行验证?(中间件、模式、守卫)
  • 业务逻辑在哪里?(服务、模型、用例)
  • 如何访问数据库?(ORM、原始查询、存储库)
阶段 3:规范检测

识别代码库已遵循的模式:

命名规范

  • 文件命名:kebab-case、camelCase、PascalCase、snake_case
  • 组件/类命名模式
  • 测试文件命名:*.test.ts、*.spec.ts、*_test.go

代码模式

  • 错误处理风格:try/catch、Result 类型、错误码
  • 依赖注入还是直接导入
  • 状态管理方法
  • 异步模式:回调、Promise、async/await、通道

Git 规范

  • 根据最近分支推断分支命名
  • 根据最近提交推断提交信息风格
  • PR 工作流(压缩合并、合并、变基)
  • 如果仓库尚无提交记录或历史记录很浅(例如 git clone --depth 1),则跳过此部分并注明“Git 历史记录不可用或过浅,无法检测规范”
阶段 4:生成入门工件

生成两个输出:

输出 1:入门指南
markdown
# 新手上路指南:[项目名称]

## 概述
[2-3句话:说明本项目的作用及服务对象]

## 技术栈
<!-- Example for a Next.js project — replace with detected stack -->
| 层级 | 技术 | 版本 |
|-------|-----------|---------|
| 语言 | TypeScript | 5.x |
| 框架 | Next.js | 14.x |
| 数据库 | PostgreSQL | 16 |
| ORM | Prisma | 5.x |
| 测试 | Jest + Playwright | - |

## 架构
[组件连接方式的图表或描述]

## 关键入口点
<!-- Example for a Next.js project — replace with detected paths -->
- **API 路由**: `src/app/api/` — Next.js 路由处理器
- **UI 页面**: `src/app/(dashboard)/` — 经过身份验证的页面
- **数据库**: `prisma/schema.prisma` — 数据模型的单一事实来源
- **配置**: `next.config.ts` — 构建和运行时配置

## 目录结构
[顶级目录 → 用途映射]

## 请求生命周期
[追踪一个 API 请求从入口到响应的全过程]

## 约定
- [文件命名模式]
- [错误处理方法]
- [测试模式]
- [Git 工作流程]

## 常见任务
<!-- Example for a Node.js project — replace with detected commands -->
- **运行开发服务器**: `npm run dev`
- **运行测试**: `npm test`
- **运行代码检查工具**: `npm run lint`
- **数据库迁移**: `npx prisma migrate dev`
- **生产环境构建**: `npm run build`

## 查找位置
<!-- Example for a Next.js project — replace with detected paths -->
| 我想... | 查看... |
|--------------|-----------|
| 添加 API 端点 | `src/app/api/` |
| 添加 UI 页面 | `src/app/(dashboard)/` |
| 添加数据库表 | `prisma/schema.prisma` |
| 添加测试 | `tests/` (与源路径匹配) |
| 更改构建配置 | `next.config.ts` |
输出 2:初始 CLAUDE.md

根据检测到的规范,生成或更新项目特定的 CLAUDE.md。如果 CLAUDE.md 已存在,请先读取它并进行增强——保留现有的项目特定说明,并明确标注新增或更改的内容。

markdown
# 项目说明

## 技术栈
[检测到的技术栈摘要]

## 代码风格
- [检测到的命名规范]
- [检测到的应遵循的模式]

## 测试
- 运行测试:`[detected test command]`
- 测试模式:[检测到的测试文件约定]
- 覆盖率:[如果已配置,覆盖率命令]

## 构建与运行
- 开发:`[detected dev command]`
- 构建:`[detected build command]`
- 代码检查:`[detected lint command]`

## 项目结构
[关键目录 → 用途映射]

## 约定
- [可检测到的提交风格]
- [可检测到的 PR 工作流程]
- [错误处理模式]

最佳实践

  1. 不要通读所有内容 —— 侦察阶段应使用 Glob 和 Grep,而非读取每个文件。仅在信号不明确时有选择性地读取。
  2. 验证而非猜测 —— 如果从配置文件中检测到某个框架,但实际代码使用了不同的东西,请以代码为准。
  3. 尊重现有的 CLAUDE.md —— 如果文件已存在,请增强它而不是替换它。明确标注哪些是新增内容,哪些是原有内容。
  4. 保持简洁 —— 入门指南应在 2 分钟内可快速浏览。细节应留在代码中,而非指南里。
  5. 标记未知项 —— 如果无法自信地检测到某个规范,请如实说明而非猜测。“无法确定测试运行器”比给出错误答案更好。

应避免的反模式

  • 生成超过 100 行的 CLAUDE.md —— 保持其聚焦
  • 列出每个依赖项 —— 仅突出那些影响编码方式的依赖
  • 描述显而易见的目录名 —— src/ 不需要解释
  • 复制 README —— 入门指南应提供 README 所缺乏的结构性见解

示例

示例 1:首次进入新仓库

用户:“带我入门这个代码库” 操作:运行完整的 4 阶段工作流 → 生成入门指南 + 初始 CLAUDE.md 输出:入门指南直接打印到对话中,并在项目根目录写入一个 CLAUDE.md

示例 2:为现有项目生成 CLAUDE.md

用户:“为这个项目生成一个 CLAUDE.md” 操作:运行阶段 1-3,跳过入门指南,仅生成 CLAUDE.md 输出:包含检测到的规范的项目特定 CLAUDE.md

示例 3:增强现有的 CLAUDE.md

用户:“用当前项目规范更新 CLAUDE.md” 操作:读取现有 CLAUDE.md,运行阶段 1-3,合并新发现 输出:更新后的 CLAUDE.md,并明确标记了新增内容

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in docs/zh-CN/skills/codebase-onboarding of affaan-m/ECC.

Open the folder on GitHubat commit ef648e0

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Codebase Onboarding next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Codebase Onboarding compared with similar skills
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ReleaseYesterday-AI/paperclip-plugin-company-wizard184—~1.6kAutomated safety check: PassMIT
Mh InitHangYu8123/mini-harness199—~2.6kAutomated safety check: PassNone
Basemind Code ContextGoldziher/basemind106—~2.6kAutomated safety check: PassMIT

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Works with

Questions about Codebase Onboarding

What does Codebase Onboarding do?

分析一个陌生的代码库,并生成一个结构化的入门指南,包括架构图、关键入口点、规范和一个起始的CLAUDE.md文件。适用于加入新项目或首次在代码仓库中设置Claude Code时。. Codebase Onboarding is an agent skill from affaan-m/ECC.

When should I use Codebase Onboarding?

Codebase Onboarding fits situations like: tasks that involve Codebase onboarding; tasks that involve Agent instruction files.

How do I install Codebase Onboarding in Claude Code?

Run `npx skills add affaan-m/ECC --skill codebase-onboarding -a claude-code`. Or copy the skill folder (docs/zh-CN/skills/codebase-onboarding in affaan-m/ECC) into .claude/skills/codebase-onboarding in your project. Claude Code loads it when a task matches its description.

How do I install Codebase Onboarding in Codex?

Run `npx skills add affaan-m/ECC --skill codebase-onboarding -a codex`. Or copy the skill folder (docs/zh-CN/skills/codebase-onboarding in affaan-m/ECC) into .agents/skills/codebase-onboarding in your project. Codex loads it when a task matches its description.

Can I use Codebase Onboarding in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill codebase-onboarding -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/codebase-onboarding, .gemini/skills/codebase-onboarding, .github/skills/codebase-onboarding and .opencode/skills/codebase-onboarding in your project.

What does Codebase Onboarding need to run?

Going by SKILL.md and its folder, Codebase Onboarding needs the command-line tools its instructions call (git). Our summary lists: Node.js; Docker.

Does Codebase Onboarding access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Codebase Onboarding safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Codebase Onboarding use?

Codebase Onboarding is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Codebase Onboarding use?

About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Codebase Onboarding?

Skills that share tags, products or a category with Codebase Onboarding: Leon Coding Agent (leon-ai/leon, 18k stars), Adopt PR Branch Context (pydantic/pydantic-ai-harness, 948 stars), Release (Yesterday-AI/paperclip-plugin-company-wizard, 184 stars) and Mh Init (HangYu8123/mini-harness, 199 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Codebase Onboarding?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 275,023 GitHub stars. The repository holds 645 skills in this directory. The repository was last updated on October 5, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.