CloudAI-X

analyzing-projects

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181
# Install this skill:
npx skills add CloudAI-X/claude-workflow-v2 --skill "analyzing-projects"

Install specific skill from multi-skill repository

# Description

Analyzes codebases to understand structure, tech stack, patterns, and conventions. Use when onboarding to a new project, exploring unfamiliar code, or when asked "how does this work?" or "what's the architecture?"

# SKILL.md


name: analyzing-projects
description: Analyzes codebases to understand structure, tech stack, patterns, and conventions. Use when onboarding to a new project, exploring unfamiliar code, or when asked "how does this work?" or "what's the architecture?"


Analyzing Projects

Project Analysis Workflow

Copy this checklist and track progress:

Project Analysis Progress:
- [ ] Step 1: Quick overview (README, root files)
- [ ] Step 2: Detect tech stack
- [ ] Step 3: Map project structure
- [ ] Step 4: Identify key patterns
- [ ] Step 5: Find development workflow
- [ ] Step 6: Generate summary report

Step 1: Quick Overview

# Check for common project markers
ls -la
cat README.md 2>/dev/null | head -50

Step 2: Tech Stack Detection

Package Managers & Dependencies

  • package.json β†’ Node.js/JavaScript/TypeScript
  • requirements.txt / pyproject.toml / setup.py β†’ Python
  • go.mod β†’ Go
  • Cargo.toml β†’ Rust
  • pom.xml / build.gradle β†’ Java
  • Gemfile β†’ Ruby

Frameworks (from dependencies)

  • React, Vue, Angular, Next.js, Nuxt
  • Express, FastAPI, Django, Flask, Rails
  • Spring Boot, Gin, Echo

Infrastructure

  • Dockerfile, docker-compose.yml β†’ Containerized
  • kubernetes/, k8s/ β†’ Kubernetes
  • terraform/, .tf files β†’ IaC
  • serverless.yml β†’ Serverless Framework
  • .github/workflows/ β†’ GitHub Actions

Step 3: Project Structure Analysis

Present as a tree with annotations:

project/
β”œβ”€β”€ src/              # Source code
β”‚   β”œβ”€β”€ components/   # UI components (React/Vue)
β”‚   β”œβ”€β”€ services/     # Business logic
β”‚   β”œβ”€β”€ models/       # Data models
β”‚   └── utils/        # Shared utilities
β”œβ”€β”€ tests/            # Test files
β”œβ”€β”€ docs/             # Documentation
└── config/           # Configuration

Step 4: Key Patterns Identification

Look for and report:
- Architecture: Monolith, Microservices, Serverless, Monorepo
- API Style: REST, GraphQL, gRPC, tRPC
- State Management: Redux, Zustand, MobX, Context
- Database: SQL, NoSQL, ORM used
- Authentication: JWT, OAuth, Sessions
- Testing: Jest, Pytest, Go test, etc.

Step 5: Development Workflow

Check for:
- .eslintrc, .prettierrc β†’ Linting/Formatting
- .husky/ β†’ Git hooks
- Makefile β†’ Build commands
- scripts/ in package.json β†’ NPM scripts

Step 6: Output Format

Generate a summary using this template:

# Project: [Name]

## Overview
[1-2 sentence description]

## Tech Stack
| Category | Technology |
|----------|------------|
| Language | TypeScript |
| Framework | Next.js 14 |
| Database | PostgreSQL |
| ...      | ...        |

## Architecture
[Description with simple ASCII diagram if helpful]

## Key Directories
- `src/` - [purpose]
- `lib/` - [purpose]

## Entry Points
- Main: `src/index.ts`
- API: `src/api/`
- Tests: `npm test`

## Conventions
- [Naming conventions]
- [File organization patterns]
- [Code style preferences]

## Quick Commands
| Action | Command |
|--------|---------|
| Install | `npm install` |
| Dev | `npm run dev` |
| Test | `npm test` |
| Build | `npm run build` |

Analysis Validation

After completing analysis, verify:

Analysis Validation:
- [ ] All major directories explained
- [ ] Tech stack accurately identified
- [ ] Entry points documented
- [ ] Development commands verified working
- [ ] No assumptions made without evidence

If any items cannot be verified, note them as "needs clarification" in the report.

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.