Hey Product Hunt, I built Tautest after noticing a problem with AI coding agents: They can generate tests that pass, but those tests do not always protect real behavior. A simple example from the demo: age >= 65 becomes age > 65 The normal test suite passed, but the mutation survived because the exact boundary at 65 was not tested. Tautest uses StrykerJS under the hood and adds a PR-focused workflow around it: - mutation testing on changed source lines - surviving mutant reports - AI-ready fix prompts - GitHub sticky PR comments - CLI and GitHub Action support It does not call any LLM API itself. It just produces deterministic reports and prompts that can be used by Claude Code, Cursor, Codex, Copilot, or human reviewers. Tautest is open source and MIT licensed. I would love feedback from developers using AI coding agents, mutation testing, or CI-heavy workflows: - Would you run this locally or in PR checks? - Is the AI fix prompt workflow useful? - Should this stay focused on JS and TS, or expand later?

tautest

Mutation testing workflow for AI-written tests

Mutation testing workflow for AI-written tests