You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
1000 issues analyzed — 165 open (16.5%), 835 closed (83.5%).
The window is short: all 1000 issues were created between 2026-09-30 and 2026-10-05, so the 1000-issue cap covers only ~5 days. Volume is extremely high and almost entirely automated (959 issues by app/github-actions). Issues close fast: average 14h18m, median 12h39m.
Triage gaps: 139 issues have no labels and 912 have no assignee. No open issue is stale (the whole window is under 30 days old).
View Full Details
📈 Issue Activity Trends
Activity covers only the last ~5 days of the 30-day axis, so the chart is a short burst rather than a long trend. Closures track openings closely, consistent with a fast automated issue lifecycle.
🏷️ Issue Clusters by Theme
Themes are dominated by automated reports (audits, WIP placeholders, squad plans) alongside model/provider and safe-outputs errors.
reacted with thumbs up emoji reacted with thumbs down emoji reacted with laugh emoji reacted with hooray emoji reacted with confused emoji reacted with heart emoji reacted with rocket emoji reacted with eyes emoji
Uh oh!
There was an error while loading. Please reload this page.
Summary
1000 issues analyzed — 165 open (16.5%), 835 closed (83.5%).
The window is short: all 1000 issues were created between 2026-09-30 and 2026-10-05, so the 1000-issue cap covers only ~5 days. Volume is extremely high and almost entirely automated (959 issues by
app/github-actions). Issues close fast: average 14h18m, median 12h39m.Triage gaps: 139 issues have no labels and 912 have no assignee. No open issue is stale (the whole window is under 30 days old).
View Full Details
📈 Issue Activity Trends
Activity covers only the last ~5 days of the 30-day axis, so the chart is a short burst rather than a long trend. Closures track openings closely, consistent with a fast automated issue lifecycle.
🏷️ Issue Clusters by Theme
Themes are dominated by automated reports (audits, WIP placeholders, squad plans) alongside model/provider and safe-outputs errors.
Cluster Details
📊 Key Metrics
Volume Metrics
issues_analyzed): 1000 (Scope: Last 1000 issues)open_issues): 165 (16.5%)closed_issues): 835 (83.5%)Time-Based Metrics
issues_opened_7d): 1000issues_opened_30d): 1000Triage Metrics
issues_without_labels): 139issues_without_assignees): 912stale_issues): 0🏆 Top Labels
👥 Most Active Authors
@app/github-actions@niebloomj@pelikhan@jaroslawgajewski@lpcoxStale Issues (No Activity 30+ Days)
Unlabeled Issues
📝 Recommendations
cascade-suspectedissues and the 116 WIP placeholder issues to curb automated issue volume.Report generated automatically by the Daily Issues Report workflow
Data source: Last 1000 issues from github/gh-aw
All reactions