Start with the run timeline
The run resource is the source of truth for stage order, timestamps, terminal status, metered totals, dataset version, and recipe. A copilot workflow stores the same run ID so a reconnect can resume inspection.
/v1/distill/runs/{run_id}Inspect the run and its stages.
/v1/distill/runs/{run_id}/logsRead bounded logs. Filter by stage or cursor instead of replaying an unbounded stream.
Read normalized metrics
Use GET /v1/distill/runs/{run_id}/metrics for per-step series such as loss, reward mean and variance, KL, latency, and cost. Compare holdout baseline and final scores; training reward alone is not a deployment claim.
Quality
Holdout deltaDid unseen examples improve?Reliability
RegressionsWhich cohorts or rewards got worse?Efficiency
Cost & latencyDoes the student meet the original objective?Inspect the evaluation report
Reports combine summary metrics, verdict, regressions, and curated examples. The copilot may summarize evidence and link the report, but creating a public share link is human-only.
/v1/distill/reports/{report_id}Read the verdict and evaluation summary.
/v1/distill/reports/{report_id}/examplesPage through curated examples; retrieve one example for deeper review.
Decision checklist
- Holdout metrics meet the goal and uncertainty is acceptable.
- No high-severity regression is hidden by an average.
- Reward behavior still matches the intended product outcome.
- The published model ID belongs to this run and report.
- Serving fallback points to a known-good teacher.