Project Analyzer

This skill helps you systematically analyze and understand codebases by following a structured approach to gather key information about the project.

When to Use This Skill

Activate this skill when:

• User asks "what does this project do?"
• User requests "analyze this codebase" or "explain this repo"
• User wants to understand project structure or architecture
• You need to provide a comprehensive overview of an unfamiliar codebase
• User asks about the technologies or stack used in a project

Analysis Process

Follow these steps systematically:

1. Project Overview

• Read README.md, README.txt, or similar documentation files
• Check package.json, pyproject.toml, Cargo.toml, go.mod, or equivalent manifest files
• Look for LICENSE file to understand licensing
• Review .git/config or check remote URLs to understand the repository source

2. Technology Stack Detection

Identify the primary languages and frameworks by checking for:

• package.json → Node.js/JavaScript/TypeScript project
• requirements.txt, pyproject.toml, setup.py → Python project
• Cargo.toml → Rust project
• go.mod → Go project
• pom.xml, build.gradle → Java project
• Gemfile → Ruby project
• .csproj, .sln → .NET/C# project
• composer.json → PHP project

3. Project Structure Analysis

• Use Glob to identify key directories (src/, lib/, tests/, docs/, etc.)
• Look for configuration files (.env.example, config/, .github/, etc.)
• Identify entry points (main.py, index.js, main.go, app.py, etc.)
• Check for build/tooling files (Makefile, Dockerfile, CI/CD configs)

4. Code Architecture

• Identify main modules/packages using directory structure
• Look for architectural patterns (MVC, microservices, monolith, etc.)
• Check for API definitions (openapi.yaml, schema.graphql, route files)
• Review database schemas or models if present

5. Dependencies & Integrations

• List major dependencies from manifest files
• Identify external services (databases, APIs, cloud services)
• Note testing frameworks and tooling
• Check for containerization (Docker, Kubernetes)

Output Format

Present your analysis in this structure:

# Project Analysis: [Project Name]

## Overview
[Brief description of what the project does]

## Technology Stack
- **Language(s)**: [Primary languages]
- **Framework(s)**: [Main frameworks]
- **Runtime/Platform**: [Node.js, Python 3.x, etc.]

## Project Structure
[Key directories and their purposes]

## Architecture
[High-level architecture description]

## Key Features
[Main functionality and capabilities]

## Dependencies
[Notable dependencies and integrations]

## Entry Points
[Main files to start understanding the code]

## Development Setup
[How to build/run the project based on available documentation]

Best Practices

• Start with documentation: Always read existing docs first
• Use the right tools: Prefer Glob for file searches, Read for reading files
• Be thorough but concise: Cover all important aspects without overwhelming detail
• Provide context: Explain why certain patterns or technologies are used
• Highlight entry points: Help users know where to start reading code
• Note gaps: If documentation is missing or unclear, mention it

Examples

Example 1: Web Application

User: "What does this project do?"
Assistant: [Activates project-analyzer skill]
[Reads README.md, package.json]
[Analyzes src/ structure]
[Provides comprehensive analysis]

Example 2: Library/Package

User: "Explain this codebase to me"
Assistant: [Activates project-analyzer skill]
[Checks for setup.py or Cargo.toml]
[Reviews lib/ and tests/]
[Explains library purpose and API]

Example 3: Microservices

User: "Analyze this repository"
Assistant: [Activates project-analyzer skill]
[Identifies multiple service directories]
[Checks docker-compose.yml]
[Explains microservice architecture]

Anti-Patterns to Avoid

• Don't make assumptions without checking files
• Don't skip reading the README if it exists
• Don't provide generic descriptions without specific details
• Don't analyze every single file (focus on key files)
• Don't ignore configuration and tooling files