AI coding agent repository benchmark
Implement one bounded feature in an existing repository and pass its acceptance tests.
Cursor leads the editorial profile for codebase control; GitHub Copilot remains the mainstream IDE choice; Replit is strongest for browser-to-deployment flow; Lovable is fastest when the job begins as a visual product prototype.
The decision table.
Scores are calculated from the four visible profile dimensions below. Open each product review to inspect the underlying strengths and limitations.
Fixed protocol.
- 01Use the same repository snapshot and written acceptance criteria.
- 02Allow the agent to inspect only the files it requests.
- 03Run the same automated tests and one human code review.
- 04Record accepted code, review minutes, retries and regressions.
What counts as usable.
✓ All stated acceptance tests pass
✓ No unrelated file changes
✓ Security boundaries remain intact
✓ A human reviewer can explain the implementation
Open comparison library →This page is a transparent decision model built from HubAI editorial profile data. It does not claim controlled instrumented testing or guaranteed performance. Run the published protocol with representative work before purchasing.
Editorial disclosure →