AI Agent Trace-to-Eval Harness

Builders can observe agent failures, but still lack a lightweight path from production trace to repeatable eval. A small CLI or GitHub Action can turn real failures into regression tests for MCP-connected agents.

Agent builders can observe failures, but lack a simple way to turn production traces into repeatable release-gating tests.

Founders and engineering teams shipping MCP-connected agents or agentic workflows into production.

Ship a CLI/GitHub Action that converts one agent trace into a replayable eval and fails releases when regressions appear.