搜索

PythonReactSEOPDF
GitHub Skill

codebase-analysis

Patterns and techniques for analyzing brownfield codebases. Use when onboarding to unfamiliar code, preparing for refactoring, conducting architecture reviews, or identifying technical debt.

aiskillstore☆ 124 仓库 Stars6 仓库 Forks

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

查看来源 ↗使用指南

技能说明

Codebase Analysis Skill

Systematically explore and understand existing codebases, including entry point discovery, dependency tracing, pattern detection, and technical debt identification.

Variables

Variable Default Description
ANALYSIS_DEPTH standard quick (5min), standard (30min), deep (1hr+)
OUTPUT_FORMAT markdown markdown, json, c4
INCLUDE_DEBT true Include technical debt assessment
INCLUDE_DIAGRAMS true Generate C4 diagrams

Instructions

MANDATORY - Follow the Workflow steps below in order. Do not skip steps.

  • Start with entry points, not random files
  • Trace dependencies before analyzing patterns
  • Document findings as you go

Red Flags - STOP and Reconsider

If you're about to:

  • Analyze random files without finding entry points first
  • Make architectural claims without tracing dependencies
  • Skip pattern detection before identifying anti-patterns
  • Report technical debt without severity classification

STOP -> Read the appropriate cookbook file -> Follow the workflow -> Then proceed

Workflow

  1. Quick Assessment: Project size, structure, config files
  2. CHECKPOINT: Identify entry points (read cookbook/entry-point-discovery.md)
  3. Trace dependencies from entry points
  4. Detect architectural patterns
  5. CHECKPOINT: Verify pattern detection before anti-pattern search
  6. Identify anti-patterns and technical debt
  7. Document findings with C4 diagrams (if INCLUDE_DIAGRAMS)

Cookbook

Entry Point Discovery
  • IF: Starting analysis of unfamiliar codebase
  • THEN: Read cookbook/entry-point-discovery.md
  • RESULT: List of main entry points by framework
Dependency Tracing
  • IF: Need to understand how modules connect
  • THEN: Read cookbook/dependency-tracing.md
  • RESULT: Import chains, dependency graph
Pattern Detection
  • IF: Need to identify architectural style
  • THEN: Read cookbook/pattern-detection.md
  • RESULT: Identified patterns (MVC, Layered, etc.)
Technical Debt Identification
  • IF: Assessing code quality and debt
  • THEN: Read cookbook/debt-identification.md
  • RESULT: Prioritized debt inventory

Quick Reference

Entry Points by Stack
Stack Look For
Node.js package.json main/bin, index.js, server.js
TypeScript tsconfig.json, src/index.ts
Python __main__.py, app.py, wsgi.py
Go main.go, cmd/*/main.go
React src/index.tsx, pages/_app.tsx

See reference/framework-patterns.md for complete list.

Common Patterns
Pattern Directory Signs
MVC models/, views/, controllers/
Layered presentation/, business/, data/
Hexagonal domain/, ports/, adapters/
Microservices services/*/, packages/*/

Output

Standard Report Format
# Codebase Analysis: [Project Name]

## Overview
- **Size**: X files, Y lines
- **Primary Language**: TypeScript
- **Framework**: Next.js
- **Architecture**: [Pattern]

## Entry Points
1. `src/pages/_app.tsx` - Application root
2. `src/api/` - API routes

## Key Dependencies
- [External deps list]

## Architecture Diagram
[C4 diagram if INCLUDE_DIAGRAMS]

## Technical Debt (if INCLUDE_DEBT)
| Issue | Severity | Location |
|-------|----------|----------|
| ... | High | ... |

使用示例

查看来源仓库中的使用示例与配置说明。

查看来源 ↗

来源历史

收录时间
2026-01-20
索引更新时间
2026-01-28
Branch
main

收录与同步日期属于本站记录。源码修改历史请查看来源仓库。

GitHub ↗

chat Comments (0)

chat_bubble_outline

No comments yet. Be the first to share your thoughts!