Project Analysis

Overview

Perform comprehensive project analysis across three dimensions: Features, Architecture, and Implementation. Provide actionable insights with specific file paths and line references.

Core principle: Read and understand, never modify. Always provide concrete code references.

Announce at start: "I'm analyzing this project's features, architecture, and implementation."

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Critical Constraints

• READ-ONLY - Do not edit or create any files
• NO CODE GENERATION - Only reference existing code
• ALWAYS CITE SOURCES - Include file:line references for all code mentions
• SAVE REPORT - Save analysis to docs/analysis/YYYY-MM-DD-<project-name>.md

Analysis Process

Phase 1: Feature Discovery

Goal: Identify what the project does.

Steps:

1. Parse arguments to determine analysis scope:
   • No args: Analyze entire project
   • Directory path: Focus analysis on that directory
   • --features / --architecture / --implementation: Run only the specified phase(s)
2. Find entry points:
   • Check config files for entry hints: package.json (main/bin/scripts), Cargo.toml ([[bin]]), setup.py/pyproject.toml (entry_points/scripts), go.mod, Makefile, etc.
   • Look for common entry files: main.*, index.*, app.*, cli.*, server.*
   • Identify CLI commands, API route definitions, exported modules
3. Identify feature modules and their responsibilities
4. List public APIs and interfaces
5. Document configuration options

Phase 2: Architecture Analysis

Goal: Understand how the project is organized.

Steps:

1. Identify tech stack (language, runtime, framework, build tools)
2. Analyze key third-party dependencies and their purposes (focus on 5-15 most significant; group by category if many)
3. Map source directory structure with file purposes
4. Identify core components and their relationships
5. Trace data flow (input → processing → output)
6. Identify design patterns used and whether they are applied consistently

Phase 3: Implementation Deep Dive

Goal: Understand how key features are implemented.

Steps:

1. Trace code paths for core features
2. Document key algorithms and logic
3. Identify important classes/functions and their roles
4. Find extension points and customization options

Output Format

# Project Analysis: [Project Name]

## Overview

[One paragraph describing what the project does]

## Features

| Feature | Description | Entry Point |
|---------|-------------|-------------|
| [name] | [what it does] | [file:line] |

## Architecture

### Tech Stack

| Category | Technology |
|----------|------------|
| Language | [e.g., Python 3.12, Go 1.22, TypeScript 5.x] |
| Runtime | [e.g., Node.js 20, CPython, JVM 21] |
| Framework | [e.g., Express, Django, Gin] |
| Build Tool | [e.g., Vite, setuptools, cargo] |

### Dependencies (Key)

List direct dependencies critical to understanding the project. Group by category if many.

| Package | Version | Purpose |
|---------|---------|---------|
| [name] | [version] | [what it does] |

### Source Structure

<!-- Adapt tree to actual project structure and language -->
project/
├── src/                # Source code
│   ├── core/           # Core business logic
│   ├── utils/          # Utility functions
│   └── main.*          # Main entry point
├── tests/              # Test files
└── [config files]      # Project configuration

**Key Files:**

| Path | Purpose |
|------|---------|
| [path to main entry] | Main entry, exports public API |
| [path to core module] | Core business logic |

### Core Components

| Component | Location | Responsibility |
|-----------|----------|----------------|
| [name] | [file:line] | [what it does] |

### Data Flow

[Input] → [Processing Stage 1] → [Processing Stage 2] → [Output]

### Design Patterns

| Pattern | Location | Purpose |
|---------|----------|---------|
| [pattern name] | [file:line] | [why it's used] |

## Implementation Details

### [Feature Name]

- **Entry:** `file:line`
- **Code Path:** file1:10 → file2:25 → file3:100
- **Key Logic:** [explanation of algorithm/approach]
- **Extension Points:** [how to customize/extend]

Edge Cases

Usage Examples

Guidelines

• Start with the broadest view, then drill into details — don't get lost in implementation before understanding architecture
• Prioritize accuracy over completeness — say "unclear" rather than guess
• Adapt depth to project size: small projects get full analysis, large projects focus on core modules
• When multiple patterns coexist (e.g., both MVC and event-driven), note the inconsistency
• Identify not just what patterns are used, but whether they're applied correctly
• Don't list every file — focus on architecturally significant files
• If the project has documentation, cross-reference your findings against it
• Use tables for structured data, tree diagrams for directories, flow notation (→) for data flow

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