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1,000 issues analyzed — 142 open, 858 closed. This repository's issue tracker is dominated by automated agentic-workflow activity: 95.7% of issues were filed by app/github-actions, and every single issue in the sample was created within the last 30 days, reflecting the extremely high churn rate of automated agent runs (failure reports, smoke tests, WIP trackers, and deep-dive analyses).
The largest thematic clusters are workflow-failure reports (376 issues) and general agent-workflow activity (270 issues), together accounting for nearly two-thirds of all volume. Average time-to-close is under 14 hours, indicating most of these automated issues are triaged and closed quickly. Only 54 issues (5.4%) lack labels, but 723 issues (72.3%) have no assignee — expected given most are automation artifacts rather than human-owned work items.
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📈 Issue Activity Trends
Both opened and closed counts track closely together across the 30-day window, consistent with a high-volume automation pipeline that self-closes most items same-day. No sustained backlog growth is visible.
🏷️ Issue Clusters by Theme
"Failure, workflow, details" and "aw, workflow, gh" dominate, reflecting routine failure-investigator and workflow-execution reports. Smaller clusters ("deep report", "smoke copilot", "sous chef", "squad game") map to specific named agentic workflows running on schedules.
Consider auto-labeling WIP/tracker issues (e.g., automation, wip) at creation time to eliminate the 54 unlabeled issues, mostly transient "work in progress" trackers from scheduled workflows.
The near-100% same-week issue volume confirms this tracker functions primarily as an automation log; consider a shorter retention/auto-close policy for routine smoke-test and WIP issues to reduce noise for human triagers.
With 723 issues unassigned, verify that automated closure/triage workflows are reliably picking up these items rather than relying on human assignment.
Report generated automatically by the Daily Issues Report workflow Data source: Last 1000 issues from github/gh-aw
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Summary
1,000 issues analyzed — 142 open, 858 closed. This repository's issue tracker is dominated by automated agentic-workflow activity: 95.7% of issues were filed by
app/github-actions, and every single issue in the sample was created within the last 30 days, reflecting the extremely high churn rate of automated agent runs (failure reports, smoke tests, WIP trackers, and deep-dive analyses).The largest thematic clusters are workflow-failure reports (376 issues) and general agent-workflow activity (270 issues), together accounting for nearly two-thirds of all volume. Average time-to-close is under 14 hours, indicating most of these automated issues are triaged and closed quickly. Only 54 issues (5.4%) lack labels, but 723 issues (72.3%) have no assignee — expected given most are automation artifacts rather than human-owned work items.
View Full Details
📈 Issue Activity Trends
Both opened and closed counts track closely together across the 30-day window, consistent with a high-volume automation pipeline that self-closes most items same-day. No sustained backlog growth is visible.
🏷️ Issue Clusters by Theme
"Failure, workflow, details" and "aw, workflow, gh" dominate, reflecting routine failure-investigator and workflow-execution reports. Smaller clusters ("deep report", "smoke copilot", "sous chef", "squad game") map to specific named agentic workflows running on schedules.
Cluster Details
📊 Key Metrics
Volume Metrics
issues_analyzed): 1,000 (Scope: Last 1000 issues)open_issues): 142 (14.2%)closed_issues): 858 (85.8%)Time-Based Metrics
issues_opened_7d): 1,000issues_opened_30d): 1,000Triage Metrics
issues_without_labels): 54issues_without_assignees): 723stale_issues): 0🏆 Top Labels
👥 Most Active Authors
@app/github-actions@dsyme@lpcox@seesharprun@ricohomewood@theletterf@mnkiefer@sebastianbiallas@loganrosen@radiantspaceStale Issues (No Activity 30+ Days)
None found — all sampled issues have recent activity.
Unlabeled Issues
📝 Recommendations
automation,wip) at creation time to eliminate the 54 unlabeled issues, mostly transient "work in progress" trackers from scheduled workflows.Report generated automatically by the Daily Issues Report workflow
Data source: Last 1000 issues from github/gh-aw
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