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AI Doc Gen

AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple…

Install

$/plugin marketplace add divar-ir/ai-doc-gen

Install command taken from the project's README or registry entry. Always review code before running it.

AI Documentation Generator

An AI-powered code documentation generator that automatically analyzes repositories and creates comprehensive documentation using large language models. The system employs a multi-agent architecture: five specialized analysis agents run concurrently to map a codebase's structure, dependencies, data flow, request flow, and APIs, and generation agents turn those analyses into a polished README.md and AI assistant configuration files (CLAUDE.md, AGENTS.md, .cursor/rules/). A GitLab cronjob mode discovers active projects and opens merge requests with fresh analysis automatically.

📝 Blog Posts

Read the full story behind this project:

Table of Contents

Features

  • Multi-Agent Analysis: Five specialized AI agents for code structure, data flow, dependency, request flow, and API analysis, writing reusable analysis documents to .ai/docs/
  • Automated Documentation: Generates comprehensive README files with configurable sections
  • AI Assistant Configuration: Generates CLAUDE.md, AGENTS.md, and .cursor/rules/*.mdc files for AI coding assistants
  • Claude Code Plugin & Skills: Ships as an installable Claude Code plugin with analyze-codebase, generate-readme, and generate-ai-rules skills (.claude-plugin/, skills/)
  • GitLab Integration: Cronjob mode discovers recently active GitLab projects, runs analysis, and opens merge requests
  • Concurrent Processing: Parallel agent execution with a configurable worker pool (ANALYZER_MAX_WORKERS, 0 = auto-detect CPU count)
  • Flexible Configuration: Layered configuration — Pydantic defaults, .ai/config.yaml, then CLI flags
  • Multiple LLM Support: Works with any OpenAI-compatible API (OpenAI, Anthropic-compatible gateways, OpenRouter, local models, etc.), with per-agent model/endpoint settings
  • Resilience: Agent-level retries plus an HTTP retry client with exponential backoff and Retry-After support (handles 429s)
  • Observability: OpenTelemetry tracing via logfire with optional Langfuse integration

Installation

Using Skills (Claude Code)

This repository doubles as a Claude Code plugin — the easiest way to use it, no API keys or Python setup required. Install it from within Claude Code:

/plugin marketplace add divar-ir/ai-doc-gen
/plugin install ai-doc-gen@divar

This adds three skills that Claude Code invokes directly:

  • analyze-codebase — multi-agent analysis producing .ai/docs/ documents
  • generate-readme — README generation from analysis or direct exploration
  • generate-ai-rules — CLAUDE.md, AGENTS.md, and Cursor rules generation

Prerequisites

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