Agentmetry dogfood exposes four recorder bugs

Agentmetry found five bugs while auditing live coding-agent activity, and four were in its own recorder: a five-day, 1,880-event backlog exposed silent capture stoppage, event loss during replay, corrupted timestamps, and false-positive detections. The project’s dogfood report says the fixes now sit behind a 20-case benchmark with 14 expected detections, zero misses, and zero false positives; the Apache-licensed repository exposes the corpus and engine. For teams deploying the guardrails described in OpenAI’s agent-security acquisition thesis, the lesson is blunt: validate the telemetry path and benign corpus, not merely the attack rules, before treating an audit trail as evidence.