I keep seeing AI-written PRs that look fine at first glance, but the risky parts are buried in the diff.
So I made Agent Diff Sentinel, a small open-source CLI that scans a git diff and points reviewers to the stuff worth checking first:
- auth, billing, security, database, CI, and dependency changes
- secret-looking added lines
- missing tests
- oversized generated-looking files
- TODO/FIXME/hack markers
It can output plain text, JSON, or Markdown, and it can fail CI on high-risk findings.
Repo: https://github.com/subhanA-UA/agent-diff-sentinel
Live page: https://subhana-ua.github.io/agent-diff-sentinel/
I’d love feedback from people using Codex, Cursor, Claude Code, or similar tools on real repos: what diff checks would you want before trusting an AI-assisted PR?
Top comments (1)
Good scope for a tool like this — diff triage rather than full review is where small utilities actually get adopted. From running AI-assisted PRs through review on real repos, the signals I'd want surfaced:
Question on the CI gate: where does the fail-on-high-risk threshold sit in practice? My worry with risk-scoring in CI is that once false positives train people to routinely skip the check, the gate quietly stops doing anything. Did you lean toward annotation-only by default with opt-in failure, or has failing builds on high-risk findings survived contact with real repos?