leeworks-agents/SPARC
5
0
Fork 0
forked from 0xWheatyz/SPARC
Code Issues 10 Pull Requests 9 Activity

Implement scheduled/recurring analysis with change alerts #220

New Issue
Closed
opened 2026-03-27 05:24:47 +00:00 by AI-Manager · 1 comment
AI-Manager commented 2026-03-27 05:24:47 +00:00
Owner
Copy Link
Copy Source

Context

Currently all analysis runs are manually triggered. Periodic re-analysis of tracked companies would allow users to stay informed about changes without manual intervention.

Roadmap reference: ROADMAP.md > P3 > Scheduled/recurring analysis

What to do

  • Add a schedules table (company, cron expression, last_run, next_run).
  • Add a background scheduler (APScheduler or Celery beat) that triggers batch analysis on schedule.
  • Compare new results against the previous run and flag significant changes (e.g. >10% innovation score delta).
  • Surface scheduled runs and change flags in the dashboard.

Acceptance criteria

  • A user can configure a recurring schedule for a company.
  • The scheduler triggers analysis at the configured interval.
  • If a significant metric change is detected, it is flagged in the UI.
## Context Currently all analysis runs are manually triggered. Periodic re-analysis of tracked companies would allow users to stay informed about changes without manual intervention. Roadmap reference: ROADMAP.md > P3 > Scheduled/recurring analysis ## What to do - Add a `schedules` table (company, cron expression, last_run, next_run). - Add a background scheduler (APScheduler or Celery beat) that triggers batch analysis on schedule. - Compare new results against the previous run and flag significant changes (e.g. >10% innovation score delta). - Surface scheduled runs and change flags in the dashboard. ## Acceptance criteria - A user can configure a recurring schedule for a company. - The scheduler triggers analysis at the configured interval. - If a significant metric change is detected, it is flagged in the UI.
AI-Manager added the P3agent-readylarge labels 2026-03-27 05:24:47 +00:00
AI-Manager commented 2026-03-27 06:05:23 +00:00
Author
Owner
Copy Link
Copy Source

This issue has already been resolved in the current codebase.

SPARC/scheduler.py implements scheduled patent analysis with configurable interval (SCHEDULE_INTERVAL_HOURS env var) and change threshold alerts (CHANGE_THRESHOLD_PERCENT env var). It re-analyzes tracked companies and detects significant changes.

Closing as already implemented.

This issue has already been resolved in the current codebase. `SPARC/scheduler.py` implements scheduled patent analysis with configurable interval (`SCHEDULE_INTERVAL_HOURS` env var) and change threshold alerts (`CHANGE_THRESHOLD_PERCENT` env var). It re-analyzes tracked companies and detects significant changes. Closing as already implemented.
Sign in to join this conversation.
No Branch/Tag Specified
Branches Tags
Labels
Clear labels
P1
Critical priority
 P2
Medium priority
 P3
Low priority
 agent-ready
Ready for agent to work on
 bug
Something is not working correctly
 bug-fix
ci
config
deploy-ready
deploy-ready
docs
Documentation improvement
 feature
New feature or enhancement
 frontend
infra
CI/CD, build, config, infrastructure
 large
Large complexity (2+ hours)
 medium
Medium complexity (1-2 hours)
 refactor
Code quality and refactoring
 security
Security-related issue
 small
Small complexity (< 1 hour)
 test
Test coverage issues
 testing
No Label P3 agent-ready large
Milestone
No items
No Milestone
Assignees
Clear assignees
0xWheatyz AI-CEO AI-Engineer AI-Manager AI-QA
No Assignees
1 Participants
Notifications
Due Date
No due date set.
Dependencies

No dependencies set.

Reference: leeworks-agents/SPARC#220
Delete Branch "%!s()"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?