## Baselines

Baseline | Total runs | Pass rate | Last verdict | Last run at
--- | --- | --- | --- | ---
Loading…

## Recent runs

Timestamp | Baseline | Verdict | Judge model | Agent version | Details
--- | --- | --- | --- | --- | ---
Loading…

## How to record runs

Wire your CI pipeline to POST a JSON body to `/api/admin/evals/runs` after each LLM-as-judge run:

    POST /api/admin/evals/runs
    {
      "id": "ci-2026-05-15-1734",
      "baseline": "intent-support",
      "timestamp": "2026-05-15T17:34:00Z",
      "agentVersion": "atmosphere-4.0.46",
      "prompt": "...the judge prompt that was sent...",
      "judgeResponse": "{\"verdict\": true}",
      "verdict": true,
      "scores": {"relevance": 0.9, "groundedness": 0.95},
      "judgeModel": "gpt-4o-mini",
      "passed": true,
      "notes": "promoted to main"
    }

The endpoint requires `atmosphere.admin.http-write-enabled=true` plus an authenticated principal whose `ControlAuthorizer` grants `evals.write`. Every accepted submission is recorded in the control audit log so an operator can reconstruct who submitted what.