gds-document-project

Analyzes existing codebases to generate architecture, API, and development documentation.

1|Updated Sep 18, 2026
One-click install
npx skills add https://github.com/PastaSus/egg-defender --skill gds-document-project-pastasus
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gds-document-project
Source: https://github.com/PastaSus/egg-defender/tree/main/.agents/skills/gds-document-project
Command: npx skills add https://github.com/PastaSus/egg-defender --skill gds-document-project-pastasus

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Brownfield projects often lack up-to-date documentation, making it hard for developers and AI agents to understand the existing system before planning new features. This Skill scans an existing codebase and produces a complete, structured documentation set ready for brownfield PRD workflows. ## Core Features & Use Cases - Multi-Level Project Scanning: Choose quick (pattern-only), deep (critical directories), or exhaustive (all source files) scan levels, with automatic project type detection across 12 types (web, mobile, backend, CLI, library, game, and more). - Full Documentation Generation: Produces index.md, project-overview, architecture, source-tree-analysis, component-inventory, development-guide, api-contracts, data-models, and integration-architecture files, including per-part docs for monorepos and multi-part projects. - Deep-Dive Mode: Exhaustively reads every file in a chosen feature, folder, or API group to produce dependency graphs, data flow analysis, and implementation guidance. - Resumable State Tracking: Maintains a project-scan-report.json state file so interrupted scans can resume within 24 hours. - Use Case: Point the Skill at a legacy full-stack repository and receive a linked documentation set that an AI agent can use to plan new features without re-reading the entire codebase. ## Quick Start Ask the AI to document the project by saying "document project" and then choose a scan level when prompted.

Frequently Asked Questions about gds-document-project

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

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

Run the document-project workflow and point it at your project root. It detects the project type, lets you pick a scan level (quick, deep, or exhaustive), and writes a linked set of Markdown docs including architecture, source tree, and development guides.

What is the difference between quick, deep, and exhaustive scans?

Quick scan uses pattern matching on configs and manifests without reading source files. Deep scan reads files in critical directories for the detected project type. Exhaustive scan reads every source file, excluding node_modules, dist, and build folders.

Can it document monorepos or multi-part projects?

Yes. It detects multiple parts such as client and server folders, classifies each part separately, and generates per-part architecture, component, and development docs plus an integration-architecture file and project-parts.json metadata.

What happens if the documentation scan is interrupted?

The workflow writes a project-scan-report.json state file after each step. If you rerun within 24 hours, it offers to resume from the last completed step; older state files are archived and a fresh scan starts.

When should I use deep-dive mode instead of a full rescan?

Use deep-dive mode when you need exhaustive detail on one specific area, such as a feature module or API group. It reads every file in scope and produces dependency graphs, data flow analysis, and modification guidance rather than project-wide docs.