[daily issues] Daily Issues Report - 2026-09-29

[github-actions[bot]]

Summary

1000 issues analyzed — the window covers only 2026-09-23 to 2026-09-29, and 97% of the issues come from automation.

All 1000 issues were opened in the last 7 days. 179 are open (17.9%) and 821 are closed (82.1%). Average time to close is about 14h48m. app/github-actions authored 966 of them, so the data mostly reflects workflow-generated issues (WIP tracking, audits, debug and smoke reports).

Triage gaps: 198 issues have no labels and 973 have no assignees. No open issues are stale, because the whole dataset is under a week old.

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📈 Issue Activity Trends

The last 7 days opened 26, 168, 201, 135, 164, 162 and 144 issues per day. Closures track openings closely (3, 91, 160, 133, 169, 137, 128), so the backlog is stable. The first and last days are partial days.

🏷️ Issue Clusters by Theme

TF-IDF and K-means (k=8) show that automated workflow reports dominate. The largest group is a mix of generic dated reports, followed by "work in progress" tracking issues.

Cluster Details

Cluster	Theme (top terms)	Issue Count	Sample Issues
1	Dated workflow reports (github, aw, 2026, 09)	370	#64283, #64282, #64275
2	WIP tracking (work, work progress, created)	172	#64290, #64289, #64285
3	Debug/agent failures (debug, github, agent, aw)	153	#64286, #64284, #64257
4	Copilot models (model, copilot, models)	92	#64269, #64252, #64250
5	Smoke tests (aw, github, game, smoke)	70	#64264, #64263, #64262
6	Tool denial (strong, tool, denial)	66	#64278, #64235, #64211
7	Safe-output signals (task, outputs emitted)	52	#64287, #64280, #64230
8	AI credits (credits, ai credits, daily)	25	#64151, #64146, #64062

📊 Key Metrics

Volume Metrics

• Total Issues Analyzed (issues_analyzed): 1000 (Scope: last 1000 issues)
• Open Issues (open_issues): 179 (17.9%)
• Closed Issues (closed_issues): 821 (82.1%)

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: ~14h 48m

Triage Metrics

• Issues Without Labels (issues_without_labels): 198
• Issues Without Assignees (issues_without_assignees): 973
• Stale Issues (30+ days) (stale_issues): 0

🏆 Top Labels

Label	Issue Count
agentic-workflows	515
automation	155
cookie	112
cascade-suspected	104
code-quality	53
improvement	52
quick-win	49
task-mining	49
testing	43
squad:plan	38

👥 Most Active Authors

Author	Issues Created
@app/github-actions	966
@lpcox	4
@ekbritecore	3
@MattSkala	2
@blozano-tt	2
@niebloomj	2

⚠️ Issues Needing Attention

Stale Issues (No Activity 30+ Days)

• None. The dataset spans only 6 days.

Human-reported issues worth a look

• Copilot Responses tool continuations emit ctc_call IDs rejected by the endpoint #64282: Copilot Responses tool continuations emit ctc_call IDs rejected by the endpoint
• Non-JSON aw_context on manual workflow_dispatch crashes the agent job ("The template is not valid") #64249: Non-JSON aw_context on manual workflow_dispatch crashes the agent job

📝 Recommendations

1. Assign an owner to the 198 unlabeled issues, or auto-label them at creation.
2. Consider excluding or grouping automation-generated WIP and report issues so human-reported issues stay visible.
3. Investigate the 104 cascade-suspected issues for a shared root cause.
4. The 1000-issue cap now covers under a week, so long-term trends need a date-bounded query.

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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 · 18.1 AIC · ⌖ 7.44 AIC · ⊞ 13.6K · ◷

• expires on Oct 2, 2026, 6:42 AM UTC-08:00