Validation signals for AI-assisted development.
Fast AI output needs instrumentation. vibe-check turns git history into a reliability signal: what stuck, what churned, and when the session started spiraling.
It tells you whether an AI-assisted session produced durable progress or just confident motion.
// the 5 core metrics
Trust Pass Rate is the key metric: it measures whether the trust level matched the task risk.
// why this matters
AI reliability varies by task type. The vibe levels answer: when can you trust AI output, and when do you verify every line?
// the context budget
Gene Kim and Steve Yegge published the threshold research: past a fraction of the context window, the AI starts forgetting instructions and contradicting itself. vibe-check treats the budget as a first-class reliability signal.
Load just-in-time, watch utilization, and reset early instead of arguing with a degraded session. The full belief is at /method: context is a budget.
// the insight
Git history is the receipt. The commits tell the truth.
vibe-check analyzes your commit patterns to detect debug spirals before they consume your whole session. Stuck for 30 minutes on the same thing? That's a wipe. Reset, do some research, come back with a plan.
The pattern it catches: eighteen minutes into arguing with the model about a circular dependency, certain the next prompt will fix it. The alert is what tells you to step away, draw the schema on paper, and come back to fix it in one commit. Minute eighteen instead of hour two.
// status
Published to npm in 2025 and quiet since. The project did its job: the ideas moved upstream. Trust calibration and spiral detection grew into the validation gates that now run inside AgentOps.
I still run the discipline it encodes: calibrate trust to task risk, watch for the spiral, reset early. The standalone CLI is the archaeology; the practice lives on in the method.