# Event Manager Pipeline Report

- Generated: 2026-03-04T23:48:23.738196+00:00
- Session ID: `solar-raven-autumn`
- Overall status: **ok**
- Selected stages: meeting, salzburg, expo

## Stage results
- meeting: ok (1593.95s)
- salzburg: ok (140.61s)
- expo: ok (42.63s)

## What went well?
- Pipeline executed with stage-by-stage telemetry and persisted logs.
- Sequential orchestration stayed stable across all stages.
- Reporting artifact generated and indexed under `/reports`.

## What went wrong?
- Data-quality issues can still appear from upstream link anomalies and recurring edge cases.
- Stage duration drift may occur; no strict timeout/escalation policy yet.

## Lessons learned
- Keep both ingestion-side sanitization and UI-side normalization for resilience.
- Post-run reporting improves observability and speeds up debugging.
- Structured logs are critical for identifying regressions early.

## Did we achieve the goal?
- **Yes**: run completion target met for session `solar-raven-autumn`.

## How can we improve?
- Add per-stage timeout and explicit timeout status in logs.
- Add collision trend metrics (last 7 runs) to detect regressions.
- Auto-link malformed outbound URLs to a normalized URL helper in UI.
- Add optional Slack/Telegram compact status card after each daily run.
- Add automatic report generation at end of every pipeline run.

## Small improvement plan (bird's-eye view)
- **Reliability:** add per-stage timeout + retry policy (capped retries).
- **Data quality:** add collision trend checks (7-run rolling window).
- **Observability:** auto-generate report after every full run.
- **UX:** keep `/settings -> /reports` path prominent and stable.
- **Operations:** add compact Telegram run-card with key metrics.

## References
- Pipeline log: `/home/clawdbot/clawd/logs/event-manager-pipeline.jsonl`
- Meeting log: `/home/clawdbot/clawd/logs/meeting-vienna-info.jsonl`
- Salzburg log: `/home/clawdbot/clawd/logs/salzburgcongress.jsonl`
- Expo log: `/home/clawdbot/clawd/logs/expo-experts.jsonl`