Open source · Early access

Do you know how much of your
codebase was written by an AI?

Most teams can't answer that. Not because they don't care — but because the tools don't exist yet.

getaigit correlates AI coding session logs with git history, surfacing AI attribution as a git blame overlay, per-file AI%, and CI report.

$ aigit blame src/api/routes.py

  4 a1b2c3d  [claude 100%] def get_user(user_id: int):
  5 a1b2c3d  [claude 100%]     return db.query(User).get(user_id)
  6 f9e8d7c               
  7 f9e8d7c                def delete_user(user_id: int):
  8 f9e8d7c                    db.query(User).filter_by(id=user_id).delete()

$ aigit stats

  src/api/routes.py     73% AI  ████████████░░░░
  src/core/engine.py    51% AI  ████████░░░░░░░░
  tests/test_api.py     68% AI  ███████████░░░░░

  Repo-wide: 61% AI-attributed
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How it works

01

Index sessions

Reads AI tool session logs and extracts code blocks automatically.

02

Match commits

Fuzzy-hashes blocks against git diff hunks across your entire history.

03

Surface insights

Blame overlay, per-file AI%, churn rate, and CI report on every PR.