AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple LLM support for better code understanding and developer onboarding.
ai-doc-gen is worth checking the docs before setup with strong trust signals. Check agent compatibility and use-case fit before adding it to your workflow.
npx skills add divar-ir/ai-doc-genRun the command in your terminal.
Confirm that the skill files were added to your agent workspace.
Check the README requirements before invoking the skill in your agent.
Repository setup guidance
Strong trust signals; still review the README and permissions before production use.
Last commit was about 96 days ago.
748 GitHub stars indicate community interest.
3 open issues signal maintenance load.
MIT license detected.
1 security/trust notes recorded.
Setup difficulty is 4/5.
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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`, `.curs
AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple LLM support for better code understanding and developer onboarding.
748
Stars
79
Forks
3
Issues
MIT
License
AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple LLM support for better code understanding and developer onboarding.
Developers
The setup section provides repository-level starting guidance, not a guarantee of an independently verified installation. Check the official README and release notes.
Use least-privilege GitLab access and avoid sending sensitive source code to untrusted model providers.
Similar or complementary options to evaluate include sourcey, mcpdoc, repowise.
Aug 20, 2026