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12.6Artifact Management
What to Capture
| Artifact | When | Size | Value |
|---|---|---|---|
| Screenshots (per step) | Always | ~100KB each | High — visual timeline |
| Screenshots (on failure) | On failure | ~100KB each | Critical — debugging |
| YAML snapshots (on failure) | On failure | ~1-20KB | High — agent can re-analyze semantically |
| Playwright traces (runner/healer sessions) | Always for agent runs | ~1-10MB | Critical — the audit trail: every action, before/after snapshots, console, and HAR network capture (included in traces since 1.60) |
| Console logs | Always | ~1-50KB | Medium — JavaScript errors |
| Test results JSON | Always | ~1-5KB | High — programmatic analysis |
The trace row is the important 2026 addition. If an AI agent drove a browser in your pipeline and you cannot answer "show me exactly what it did," you have an unaccountable system. Traces are the literal answer to that question — archive them for every agent-driven run, and feed them back to the agent (or the healer) when a run needs debugging.
Retention Policy
# GitHub Actions
- uses: actions/upload-artifact@v4
with:
name: test-results
path: results/
retention-days: 30 # Keep for 30 days; consider longer for traces if compliance asks