[daily issues] Daily Issues Report - 2026-09-06

[github-actions[bot]]

Summary

1,000 issues analyzed — 164 open (16.4%), 836 closed (83.6%), all 1,000 opened in the last 30 days.

The repository's issue stream is dominated by automated agent output: 963 of 1,000 issues were filed by app/github-actions, and clustering reveals that most activity centers on agent workflow failures, daily/aw automation reports, and model-failure diagnostics rather than traditional human bug reports or feature requests. The average time to close is under 14 hours (0.58 days), reflecting a high-throughput automated triage pipeline rather than manual review cycles. 115 issues (11.5%) carry no labels and 924 (92.4%) have no assignee, consistent with a bot-driven issue lifecycle where labeling/assignment is optional or handled downstream. No issues are stale (30+ days without activity), indicating the automation keeps the queue moving.

Because nearly all issues originate from automated workflows, the "top authors" and "unlabeled" metrics should be read as automation health signals rather than community engagement signals — a small number of human authors (lpcox, dsyme, sigh71, v1v, others) appear only sporadically.

View Full Details

📈 Issue Activity Trends

All 1,000 fetched issues were created within the last 30 days (and indeed within the last 7), showing sustained heavy issue-creation volume from automated workflows. Opened and closed lines track closely together with a short lag, consistent with the sub-day average close time — issues are typically triaged and resolved almost as fast as they are filed.

🏷️ Issue Clusters by Theme

The largest cluster (326 issues) centers on agent/workflow failure reports, followed by daily "aw"/gh workflow automation summaries (209) and model-failure diagnostics (156). Work-in-progress trackers, smoke-test/PR sub-issues, "DeepReport" briefings, squad/game-planner issues, and code-scanning fixer reports round out the remaining themes.

Cluster Details

Cluster	Theme (top TF-IDF terms)	Issue Count	Sample Issues
1	failure, agent, workflow, details	326	#58991, #58982, #58964
2	aw, workflow, gh, daily	209	#58993, #58990, #58974
3	model, failure, workflow, agent	156	#58984, #58983, #58972
4	work, work progress, progress, created	109	#58995, #58994, #58985
5	smoke, pr, sub, aw	78	#58940, #58889, #58888
6	deep report, deep, id deep, report	66	#58986, #58948, #58947
7	squad, game, game planner, squad game	36	#58981, #58980, #58979
8	scanning fixer, fixer, code scanning, scanning	20	#58992, #58951, #58855

📊 Key Metrics

Volume Metrics

• Total Issues Analyzed (issues_analyzed): 1000 (Scope: Last 1000 issues)
• Open Issues (open_issues): 164 (16.4%)
• Closed Issues (closed_issues): 836 (83.6%)

Time-Based Metrics

• Issues Opened (Last 7 Days) (issues_opened_7d): 1000
• Issues Opened (Last 30 Days) (issues_opened_30d): 1000
• Average Time to Close: 0.58 days (~14 hours)

Triage Metrics

• Issues Without Labels (issues_without_labels): 115
• Issues Without Assignees (issues_without_assignees): 924
• Stale Issues (30+ days) (stale_issues): 0

🏆 Top Labels

Label	Issue Count
agentic-workflows	534
automation	204
cookie	114
cascade-suspected	109
improvement	69
code-quality	65
quick-win	62
task-mining	62
testing	60
squad:plan	41

👥 Most Active Authors

Author	Issues Created
app/github-actions	963
@lpcox	9
@dsyme	4
@sigh71	3
@v1v	3
@ilja	2
@kkruel8100	2
@xpepper	1
@jaroslawgajewski	1
@golivax	1

⚠️ Issues Needing Attention

Stale Issues (No Activity 30+ Days)

None found — all open issues have had activity within the last 30 days.

Unlabeled Issues

• [WIP] Daily Go Test Parallelizer: work in progress #58995: [WIP] Daily Go Test Parallelizer: work in progress
• [WIP] Dead Code Removal Agent: work in progress #58994: [WIP] Dead Code Removal Agent: work in progress
• [copilot-cli-research] Copilot CLI Deep Research - 2026-09-06 #58912: [copilot-cli-research] Copilot CLI Deep Research - 2026-09-06

📝 Recommendations

1. Reduce label gaps: 115 issues (11.5%) lack labels, including several [WIP] tracker issues — apply automated labeling rules for known workflow-generated title prefixes (e.g. [WIP], [daily issues]) to close this gap.
2. Consolidate high-volume clusters: the "agent/workflow failure" cluster (326 issues) and "model failure" cluster (156 issues) together represent nearly half of all issues — consider a dedicated triage workflow or auto-linking to reduce duplicate/near-duplicate failure reports.
3. Review assignee policy: with 92.4% of issues unassigned, confirm this is intentional for bot-filed automation issues rather than a sign that actionable items are going unowned.
4. Monitor throughput, not just backlog: because close time is sub-day and stale issues are at zero, the queue is healthy overall — future reports should watch for any uptick in avg_close_days or stale count as an early signal of automation regressions.

---

Report generated automatically by the Daily Issues Report workflow
Data source: Last 1000 issues from github/gh-aw

Generated by 📅 Daily Issues Report Generator · copilot · auto · 36.4 AIC · ⌖ 7.74 AIC · ⊞ 13.8K · ◷

• expires on Sep 9, 2026, 6:36 AM UTC-08:00