Public repos only · read-only

How ready is this codebase for an AI agent?

Reads the full merged-PR and commit history, scores how ready the codebase is for AI agents, and shows the engineering signals behind that score.

Agent Readiness · example

Level 3
L1
Foundational
88%
L2
Baseline
67%
L3
Agent-ready
57%
L4
Production-grade
25%
L5
Leading
0%

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Signals, not vanity metrics

Stars measure attention. These measure engineering — what kind of work lands, how fast it moves, how much of it survives, and how seriously it gets reviewed.

Work distribution

Reads every merged PR and classifies each commit as feature, bug fix, or maintenance — so you see where the team actually spends its time.

Code churn

Measures how much newly written code gets rewritten or reverted within weeks, a leading indicator of rushed or low-confidence changes.

Review velocity

Tracks cycle time, time to first approval, review rounds, and self-merge rate — the mechanics of how fast and safely changes land.

Review quality

Scores what fraction of review comments are substantive versus rubber-stamp, separating teams that really review from those that just approve.

Tracked repositories

Click a repo for the full breakdown