Vibe Coding Testing.
For when AI built it and nobody wrote tests.
Your AI assistant shipped 5,000 lines of working code. None of it has tests. You can't read every line. CI is green because there's nothing to run. Then production breaks and you're back in the editor asking the AI what changed. tailtest fixes the loop: the same AI that wrote the code now writes the tests, runs them, and tells you what's broken before you ship.
The vibe-coding test gap
Three numbers worth knowing if you ship vibe-coded apps:
You don't need to be a "real engineer" to build software in 2026. But you do need a way to verify what was built. tailtest is that layer, built for people whose primary tool is an AI coding assistant.
How it fits your workflow
You probably use Claude Code, Cursor, Codex CLI, or Cline (or some combination). tailtest is a plugin you install once into whichever of those is your daily driver. From that point on:
- You build features the way you already build them. Talk to the AI in natural language.
- Every time the AI edits a file, tailtest queues that file for testing.
- The same AI writes the test, runs it, and reports what failed.
- If everything passes, you see one line: "tailtest: 12 scenarios -- all passed." You keep building.
- If something fails, the AI fixes it (usually) before showing you. If it can't, you see the failing scenarios with what went wrong.
You don't write tests. You don't run tests. You don't configure runners. tailtest detects what test framework your project uses (or doesn't use yet) and either uses it or stands up a sensible default.
What about security?
Adversarial mode (turn on with one line of config) biases scenarios toward breakage paths: boundary inputs, format injection, type confusion, race conditions, time/locale edges, partial failure handling, resource exhaustion, off-by-one logic. These are the categories that catch the most common vibe-coding bugs.
A dedicated security testing layer is on the platform roadmap for Q4 2026: OWASP-aligned scans, secrets in code detection, auth/authz edge cases. Roadmap details here. Until that ships, adversarial mode catches a meaningful subset of security-adjacent issues -- particularly input validation and resource handling.
Get started in one command
Pick whichever AI tool you actually use:
Proof: we use this against ourselves
We ran tailtest's adversarial mode against 47 open-source Python repositories. It found 16 real bugs that maintainers confirmed and fixed. Same tool that runs against your vibe-coded app. Same R1-R15 rule layer. Same 8 adversarial categories.
See the 16 findings →Free, open source, no telemetry, no SaaS account. MIT licensed forever.