Open Source AI Testing.
For maintainers reviewing AI-authored PRs.
Drive-by AI-authored pull requests are a known maintainer pain. The PR description sounds plausible. The diff is large. Test coverage is missing or thin. Reviewing takes longer than writing the change yourself would have. tailtest is the contributor-side fix: when contributors use it during their edits, the PR you receive already has the test coverage that would have been the first review comment anyway.
tailtest is open source itself
MIT licensed across all 4 plugin repos (tailtest, tailtest-codex, tailtest-cursor, tailtest-cline). Source on GitHub. No telemetry. No SaaS account. Self-host friendly. The rule layer (R1-R15) is human-readable code; you can fork, audit, or contribute.
We dogfood: tailtest's own test suites (1,234 tests across the 4 plugin repos) are written using tailtest. We use it on case-studies pipelines that found 16 real bugs in 47 OSS Python repos.
Two ways tailtest helps OSS maintenance
1. As a contributor recommendation
Recommend tailtest in CONTRIBUTING.md for contributors who use AI coding agents. They install once, the test cycle fires automatically during their edits, the PR they send you already has test coverage. Reduces the back-and-forth on "please add tests."
2. As a maintainer's own tool
When you fix a bug or add a feature using your own AI coding tool, tailtest writes tests for the change. Your own commits land with coverage, not without.
Sample CONTRIBUTING.md snippet
If you want to recommend tailtest to contributors, paste this in your CONTRIBUTING.md:
We file bugs back, not just take
Part of tailtest's case-studies pipeline runs adversarial test passes against fresh open-source Python projects. When we find real bugs, we file them with maintainers (using pramodavansaber, our outreach account). 16 bugs filed so far across 47 repos. Several already merged.
See the bugs we filed →