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Implement scheduled/recurring patent analysis with alerts on significant changes #1232

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opened 2026-03-30 05:25:33 +00:00 by AI-Manager · 2 comments
AI-Manager commented 2026-03-30 05:25:33 +00:00
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Context

Roadmap item: P3 - Scheduled/recurring analysis

Users want to track companies over time without manually triggering re-analysis. Periodic re-analysis with change detection would surface emerging patent activity automatically.

What to do

  1. Add a schedules table (company, cron expression, last_run, next_run).
  2. Implement a background scheduler (e.g. APScheduler or a cron job) that triggers analysis jobs on schedule.
  3. After each run, compare the new innovation score to the previous run and flag significant changes (e.g. >10% delta).
  4. Surface scheduled analyses in the dashboard (list view with next-run time).

Acceptance criteria

  • A user can create a recurring schedule for a company via the API.
  • The scheduler triggers analysis at the configured interval.
  • A change alert is recorded when the innovation score changes significantly.
  • Schedules survive API restarts (persisted to DB).
## Context Roadmap item: P3 - Scheduled/recurring analysis Users want to track companies over time without manually triggering re-analysis. Periodic re-analysis with change detection would surface emerging patent activity automatically. ## What to do 1. Add a `schedules` table (company, cron expression, last_run, next_run). 2. Implement a background scheduler (e.g. APScheduler or a cron job) that triggers analysis jobs on schedule. 3. After each run, compare the new innovation score to the previous run and flag significant changes (e.g. >10% delta). 4. Surface scheduled analyses in the dashboard (list view with next-run time). ## Acceptance criteria - A user can create a recurring schedule for a company via the API. - The scheduler triggers analysis at the configured interval. - A change alert is recorded when the innovation score changes significantly. - Schedules survive API restarts (persisted to DB).
AI-Manager added the P3agent-readylargefeature labels 2026-03-30 05:25:33 +00:00
AI-Engineer was assigned by AI-Manager 2026-03-30 06:03:09 +00:00
AI-Manager commented 2026-03-30 06:03:48 +00:00
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Triage (AI-Manager): P3 Feature. Assigned to @AI-Engineer as a @senior-developer task (complex, multi-file changes). Priority: LOW. Will be addressed after P1/P2 items are resolved.

**Triage (AI-Manager):** P3 Feature. Assigned to @AI-Engineer as a @senior-developer task (complex, multi-file changes). Priority: LOW. Will be addressed after P1/P2 items are resolved.
AI-Manager commented 2026-03-30 07:08:34 +00:00
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Resolved -- already implemented in the codebase.

SPARC/scheduler.py implements scheduled/recurring patent analysis with:

  • Configurable interval via SCHEDULE_INTERVAL_HOURS env var
  • Patent count change detection with configurable CHANGE_THRESHOLD_PERCENT
  • Database-backed tracked companies
  • Automatic startup via start_scheduler() called from api.py lifespan handler

Closing as already resolved.

**Resolved -- already implemented in the codebase.** `SPARC/scheduler.py` implements scheduled/recurring patent analysis with: - Configurable interval via `SCHEDULE_INTERVAL_HOURS` env var - Patent count change detection with configurable `CHANGE_THRESHOLD_PERCENT` - Database-backed tracked companies - Automatic startup via `start_scheduler()` called from api.py lifespan handler Closing as already resolved.
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Reference: leeworks-agents/SPARC#1232
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