OpenClaw GitHub Stale Issue Cleanup: Automate Backlog Hygiene with Human Review
This case identifies inactive GitHub issues on a fixed cadence, generates closure candidates for maintainers, and keeps issue backlogs manageable without fully automated blind closing.
Tags
Target users
What it does
- Scans open GitHub issues on a schedule and flags inactivity beyond a defined threshold (for example, 30 days).
- Produces a candidate list for human maintainers instead of directly closing everything.
- Supports a warn-then-close flow so contributors have a response window before closure.
Skills You Need
Pain Point
Issue backlogs keep growing, but manual triage is irregular and expensive. Repositories often carry many inactive issues that hide high-priority work and slow down maintenance decisions.
Core value of this case
This case turns backlog cleanup into a repeatable operating routine. It reduces issue noise, preserves human control for final closure decisions, and keeps repository health visible over time.
Typical scenarios
- Weekly maintenance for medium/large open-source repositories.
- Team workflows where maintainers want cleanup suggestions, not automatic mass closure.
- Repositories with recurring “abandoned issue” accumulation.
How to setup
- Define inactivity policy (for example, stale after 30 days, close 14 days after stale warning).
- Run a scheduled workflow that applies the stale label and warning comment.
- Route stale candidates to a maintainer review step before final close.
Related Links
FAQ
Should stale issues be closed automatically?
Not always. A review gate is safer for repositories with active but slow-moving discussions.
What threshold is a practical starting point?
A common baseline is 30 days to mark stale and 14 extra days before closure.
How do we avoid closing valuable long-term issues?
Use labels or exemption rules for roadmap, security, or design-tracking issues before stale automation runs.