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document-project

Analyze codebases to generate structured technical documentation for existing software projects.

4|2|Updated Apr 1, 2026
Search Tags:#architecture#software engineering#codebase analysis#ai context#project documentation#brownfield
One-click install
npx skills add https://github.com/anderson-0/mighty-powers --skill document-project-anderson-0
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: document-project
Source: https://github.com/anderson-0/mighty-powers/tree/main/skills/document-project
Command: npx skills add https://github.com/anderson-0/mighty-powers --skill document-project-anderson-0

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams understand and document existing codebases by creating structured project documentation for AI-assisted development, reducing the effort required to analyze brownfield systems.

Core Features & Use Cases

  • Project Analysis Workflow: Scans project structure, technology stacks, architecture patterns, APIs, data models, components, and development workflows.
  • Resumable Documentation Generation: Maintains workflow state, supports quick/deep/exhaustive scans, and generates organized documentation artifacts for future AI context.
  • Use Case: A developer inheriting a large application can use this Skill to create architecture docs, source tree analysis, and implementation guidance before planning new features.

Quick Start

Use the document-project skill to generate comprehensive documentation for this existing project and prepare it for AI-assisted development.

Frequently Asked Questions about document-project

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate architecture documentation for an existing codebase?▼

Generate architecture documentation for an existing codebase by scanning project structure, technology stacks, and APIs. This Skill produces structured technical documentation and organized artifacts for AI-assisted development.

What is the best way to prepare brownfield project documentation for AI context?▼

Preparing brownfield project documentation for AI context involves analyzing source trees and data models to create implementation guidance. It outputs maintainable project knowledge structured specifically for AI workflows.

Can I resume project scanning if my codebase analysis is interrupted?▼

Yes, you can resume codebase analysis because the workflow maintains its state. This supports quick, deep, and exhaustive scans without losing progress, ensuring complete artifact generation for large projects.

Does this approach work for discovering APIs and data models in large applications?▼

Yes, this approach works for discovering APIs and data models in large applications by performing source analysis. It scans the architecture patterns and development workflows to output comprehensive technical documentation.

What are the limitations when scanning complex software engineering projects?▼

Scanning complex software engineering projects requires workflow orchestration and validation tracking. While it handles brownfield systems well, users must manage scan depth settings to balance analysis thoroughness with processing time.

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