github-issue-triage

You can automate GitHub issue triage by launching a separate background task for each issue, enabling real-time per-issue analysis and live progress updates as tasks run in parallel. A final comprehensive triage report is generated once all tasks finish.

Streaming analysis for GitHub issues processes every issue as its own independent background task, fetching all issues through exhaustive pagination. It reports results continuously as each task completes via background_output(), providing live progress feedback during processing.

Yes, you need the gh CLI installed and accessible in your Python environment to run the issue triage. The skill uses the gh CLI to fetch all repository issues with exhaustive pagination before launching parallel background tasks for analysis.

Yes, you can triage GitHub issues in near real time by monitoring live results as each background task completes. The skill provides continuous feedback during processing via background_output(), enabling faster bug identification and prioritization for busy repositories.

The best way to generate a comprehensive triage report is running per-issue background tasks in parallel and consolidating results. After all streaming tasks finish, the skill produces a final triage summary including categorization of issues and suggested maintainer actions.

Processing GitHub issues as parallel background tasks is designed for repositories with high issue volume. The skill applies deterministic task-per-issue execution, so repositories with very few issues may not benefit significantly from the streaming parallel approach.