codebase-onboarding
alirezarezvani/claude-skills
分析程式碼庫,並為工程師、技術主管及合約人員生成入職文件,具備快速蒐集資訊及產生可重複產出的能力。
...展開全部Codebase 入職指南
等級:POWERFUL
類別:工程
領域:文件 / 開發者體驗
概述
分析程式碼庫,並為工程師、技術負責人及合約人員生成入職文件。此技能專為快速蒐集事實資訊及產生可重複的入職文件而優化。
核心功能
- 根據儲存庫訊號進行架構與技術堆疊分析
- 為新貢獻者彙整關鍵檔案與設定清單
- 生成本地環境設定與常見任務指引
- 針對受眾需求量身打造的文件架構
- 除錯與貢獻檢查清單的骨架建置
何時適用
- 為新團隊成員或承包商進行入職培訓
- 在進行大規模重構後重建過時的專案文件
- 準備內部交接文件
- 為服務建立標準化的入職資料包
快速入門
# 1) 彙整程式碼庫相關資訊
python3 scripts/codebase_analyzer.py /path/to/repo
# 2) 匯出機器可讀的輸出檔
python3 scripts/codebase_analyzer.py /path/to/repo --json
# 3) 使用範本草擬入職文件
# 請參閱 references/onboarding-template.md
建議的工作流程
- 針對目標儲存庫執行
scripts/codebase_analyzer.py。 - 擷取關鍵指標:檔案數量、偵測到的程式語言、設定檔、頂層結構。
- 填寫
references/onboarding-template.md中的入職指南範本。 - 根據受眾調整輸出詳盡程度:
- 初階人員:環境設定 + 防護措施
- 資深工程師:架構 + 運維考量
- 合約工程師:範圍內的所有權 + 整合邊界
入職文件範本
詳細的範本及各章節範例請參閱:
references/onboarding-template.mdreferences/output-format-templates.md
常見陷阱
- 在未於乾淨環境中驗證設定指令的情況下撰寫文件
- 將架構深度解析內容混入以承包商為導向的文件中
- 省略疑難排解與驗證步驟
- 讓入門文件與當前儲存庫狀態脫節
最佳實務
- 確保設定說明可執行且有明確的時間限制。
- 針對關鍵架構決策,詳細記錄其「原因」。
- 在行為變更的同一個 Pull Request 中更新文件。
- 將入門文件視為持續更新的營運資產,而非一次性交付成果。
---
name: codebase-onboarding
description: Analyze a codebase and generate onboarding documentation for engineers, tech leads, and contractors, with fast fact-gathering and repeatable outputs.
---
# Codebase Onboarding
**Tier:** POWERFUL
**Category:** Engineering
**Domain:** Documentation / Developer Experience
---
## Overview
Analyze a codebase and generate onboarding documentation for engineers, tech leads, and contractors. This skill is optimized for fast fact-gathering and repeatable onboarding outputs.
## Core Capabilities
- Architecture and stack discovery from repository signals
- Key file and config inventory for new contributors
- Local setup and common-task guidance generation
- Audience-aware documentation framing
- Debugging and contribution checklist scaffolding
---
## When to Use
- Onboarding a new team member or contractor
- Rebuilding stale project docs after large refactors
- Preparing internal handoff documentation
- Creating a standardized onboarding packet for services
---
## Quick Start
```bash
# 1) Gather codebase facts
python3 scripts/codebase_analyzer.py /path/to/repo
# 2) Export machine-readable output
python3 scripts/codebase_analyzer.py /path/to/repo --json
# 3) Use the template to draft onboarding docs
# See references/onboarding-template.md
```
---
## Recommended Workflow
1. Run `scripts/codebase_analyzer.py` against the target repository.
2. Capture key signals: file counts, detected languages, config files, top-level structure.
3. Fill the onboarding template in `references/onboarding-template.md`.
4. Tailor output depth by audience:
- Junior: setup + guardrails
- Senior: architecture + operational concerns
- Contractor: scoped ownership + integration boundaries
---
## Onboarding Document Template
Detailed template and section examples live in:
- `references/onboarding-template.md`
- `references/output-format-templates.md`
---
## Common Pitfalls
- Writing docs without validating setup commands on a clean environment
- Mixing architecture deep-dives into contractor-oriented docs
- Omitting troubleshooting and verification steps
- Letting onboarding docs drift from current repo state
## Best Practices
1. Keep setup instructions executable and time-bounded.
2. Document the "why" for key architectural decisions.
3. Update docs in the same PR as behavior changes.
4. Treat onboarding docs as living operational assets, not one-time deliverables.





首頁
