Stars-894 !!better!! Today

| # | Objective | Success Metric | |---|-----------|----------------| | | Detect and localize high‑energy transients with < 10 ms timing accuracy. | ≥ 95 % of events > 10⁻⁸ erg cm⁻² localized within 5 arcmin. | | 2 | Provide real‑time alerts to the community via the Gamma‑Ray Coordinates Network (GCN). | ≤ 30 s latency from photon detection to GCN notice for ≥ 90 % of events. | | 3 | Produce a calibrated, publicly accessible high‑energy sky map every 6 h. | 100 % map completion, < 5 % systematic error. | | 4 | Demonstrate a scalable, high‑throughput telemetry architecture (> 2 Gbps). | Sustained downlink > 1.8 Gbps with < 2 % packet loss. | | 5 | Generate technology spin‑offs for commercial space‑weather services. | At least one commercial licensing agreement within 5 yr of operations. |

| Sprint | Tasks | |--------|-------| | (2 weeks) | - Create TagSuggestionDropdown React component - Set up debounced request flow - Draft API spec and add OpenAPI definitions | | Sprint 2 (2 weeks) | - Implement Node.js suggestion service (validation, taxonomy lookup) - Deploy placeholder NLP micro‑service (simple keyword extractor) | | Sprint 3 (2 weeks) | - Integrate fine‑tuned transformer model - Add snippet generation logic - Write unit & integration tests for backend | | Sprint 4 (2 weeks) | - Implement analytics endpoint & logging - Add accessibility improvements & keyboard shortcuts - Conduct performance testing & optimize latency | | Sprint 5 (1 week) | - Conduct UI/UX usability testing with 3 authors - Fix any discovered bugs - Prepare rollout documentation | | Sprint 6 (1 week) | - Feature flag rollout to 10 % of users (canary) - Monitor error rates & acceptance metrics - Full production enablement if no regressions | STARS-894