Track the AI Code in your repositories

curl -sSL https://usegitai.com/install.sh | bash

powershell -NoProfile -ExecutionPolicy Bypass -Command "irm http://usegitai.com/install.ps1 | iex"

🎊 That's it! No per-repo setup. Once installed Git AI will work OOTB with any of these Supported Agents:

• AI Blame
• Cross-Agent Prompt Saving
• How Git AI Works
• CLI Reference
• Configuring Git AI for the enterprise

Once installed, all your Coding Agents will call Git AI in the background and mark the code they generate AI-authored.

After you commit, git-ai adds a git note to track which lines were AI-authored and scores each commit:

Aggregate git-ai data at the PR, developer, Repository and Organization levels:

• AI authorship breakdown for every Pull Request
• Measure % of code that is AI generated through the entire SDLC
• Compare accepted-rate for code written by each Agent + Model.
• AI-Code Halflife (how durable is the AI code)

Get early access by chatting with the maintainers

🤖 Track AI code in a Multi-Agent world. Because developers get to choose their tools, engineering teams need a vendor agnostic way to track AI impact in their repos.

🎯 Accurate attribution from Laptop → Pull Request → Merged. Claude Code, Cursor and Copilot cannot track code after generation—Git AI follows it through the entire workflow.

🔄 Support real-world git workflows by making sure AI-Authorship annotations survive a merge --squash, rebase, reset, cherry-pick etc.

🔗 Maintain link between prompts and code - there is valuable context and requirements in team prompts—preserve them alongside code.

🚀 Git-native + Fast - git-ai is built on git plumbing commands. Negligible impact even in large repos (<100ms). Tested in Chromium.

git-ai automatically sets up all supported agent hooks using the git-ai install-hooks command

| your agent here | | |

Building a Coding Agent? Add support for Git AI by following this guide