analyzing-projects

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?"

16 stars

Best use case

analyzing-projects is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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?"

Teams using analyzing-projects should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/analyzing-projects/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/backend/analyzing-projects/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/analyzing-projects/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How analyzing-projects Compares

Feature / Agentanalyzing-projectsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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?"

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

```bash
# 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` → Node.js/JavaScript/TypeScript
- `requirements.txt` / `pyproject.toml` / `setup.py` → Python
- `go.mod` → Go
- `Cargo.toml` → Rust
- `pom.xml` / `build.gradle` → Java
- `Gemfile` → Ruby

### Frameworks (from dependencies)
- React, Vue, Angular, Next.js, Nuxt
- Express, FastAPI, Django, Flask, Rails
- Spring Boot, Gin, Echo

### Infrastructure
- `Dockerfile`, `docker-compose.yml` → Containerized
- `kubernetes/`, `k8s/` → Kubernetes
- `terraform/`, `.tf` files → IaC
- `serverless.yml` → Serverless Framework
- `.github/workflows/` → GitHub Actions

## Step 3: Project Structure Analysis

Present as a tree with annotations:
```
project/
├── src/              # Source code
│   ├── components/   # UI components (React/Vue)
│   ├── services/     # Business logic
│   ├── models/       # Data models
│   └── utils/        # Shared utilities
├── tests/            # Test files
├── 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` → Linting/Formatting
- `.husky/` → Git hooks
- `Makefile` → Build commands
- `scripts/` in package.json → NPM scripts

## Step 6: Output Format

Generate a summary using this template:

```markdown
# 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.

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