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[daily issues] Daily Issues Report - 2026-02-10ย #14748

@github-actions

Description

@github-actions

Summary

Over the last 30 days, issue volume remains high with steady throughput: 1,000 issues analyzed, with 54 open and 946 closed. The average time to close is under a day (0.90 days โ‰ˆ 21.7 hours), and the most active labels are automation-oriented, suggesting strong bot-driven activity alongside human triage.

The dominant themes are GitHub/workflow-related topics and task-mining discussions, with notable secondary clusters around smoke tests and workflow failures. Recent activity shows consistent daily openings/closures, peaking on February 6, 2026 (opened) and February 3, 2026 (closed).

๐Ÿ“Š Full Report Details

๐Ÿ“ˆ Issue Activity Trends

Issue Activity Trends

The peak opened day in the last 30 days was February 6, 2026 with 149 new issues, while the peak closed day was February 3, 2026 with 246 closures. The 7โ€‘day averages are roughly 79.6 opened/day and 80.7 closed/day, indicating stable throughput and a near-balanced backlog flow.

๐Ÿท๏ธ Issue Clusters by Theme

Issue Clusters

The top clusters center on GitHub/workflow topics and taskโ€‘mining discussions, followed by smoke tests and workflow failures. This distribution suggests routine operational activity plus periodic CI/runtime failures that merit monitoring.

Cluster Details

Cluster Theme Issue Count Sample Issues
1 Theme 3: github, workflow, gh 272 #14645, #14613, #14745
2 Theme 2: discussion task, task miner, miner 252 #14591, #14590, #14579
3 Theme 1: smoke, gh, copilot 146 #14729, #14717, #14712
4 Theme 7: workflow failure, failure, github 119 #14166, #14164, #14170
5 Theme 6: claude, smoke, testing 84 #14718, #14705, #14474
6 Theme 4: smoke, parent, group 56 #14706, #14734, #14688
7 Theme 5: ci, doctor, ci failure 53 #14397, #14686, #14653
8 Theme 8: deep report, deepreport intelligence, intelligence 18 #14678, #14675, #14677

๐Ÿ“Š Key Metrics

Volume Metrics

  • Total Issues Analyzed (issues_analyzed): 1000 (Scope: last 1000 issues)
  • Open Issues (open_issues): 54 (5.4%)
  • Closed Issues (closed_issues): 946 (94.6%)

Time-Based Metrics

  • Issues Opened (Last 7 Days) (issues_opened_7d): 648
  • Issues Opened (Last 30 Days) (issues_opened_30d): 1000
  • Average Time to Close: 0.90 days (~21.7 hours)

Triage Metrics

  • Issues Without Labels (issues_without_labels): 141
  • Issues Without Assignees (issues_without_assignees): 803
  • Stale Issues (30+ days) (stale_issues): 0

๐Ÿ† Top Labels

Label Issue Count
cookie 454
automation 414
code-quality 277
task-mining 257
agentic-workflows 125
documentation 118
refactoring 104
testing 90
smoke-copilot 78
enhancement 65

๐Ÿ‘ฅ Most Active Authors

Author Issues Created
@app/github-actions 965
@pelikhan 8
@Mossaka 5
@mnkiefer 3
@dsyme 3
@app/agentic-workflows-dev 3
@dindinrosaot853-tech 2
@dunalduck0 2
@devantler 2
@brunoborges 1

โš ๏ธ Issues Needing Attention

Stale Issues (No Activity 30+ Days)

  • None ๐ŸŽ‰

Unlabeled Issues

๐Ÿ“ Recommendations

  1. Triage unlabeled issues (141) by adding appropriate labels to improve routing and reporting accuracy.
  2. Assign owners to high-impact workflow failure and smoke-test clusters to reduce repeat CI interruptions.
  3. Review automation-heavy labels (cookie, automation, task-mining) to ensure bot-generated issues have the right escalation paths.

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

References: ยง21858500710


Note: This was intended to be a discussion, but discussions could not be created due to permissions issues. This issue was created as a fallback.

AI generated by Daily Issues Report Generator

  • expires on Feb 13, 2026, 9:13 AM UTC

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