[Auto-Triage] 🏷️ Auto-Triage Report - 2026-02-11 19:23 UTC

[github-actions[bot]]

🏷️ Auto-Triage Report Summary

Report Period: 2026-02-11 19:23 UTC (Scheduled Run)
Issues Processed: 1
Labels Applied: 2 total labels
Still Unlabeled: 8 issues (search results may be cached or recently labeled by other processes)

Key Metrics

• Success Rate: 100% (1/1 confidently classified issue)
• Average Confidence: High
• Most Common Classifications: documentation (1), enhancement (1)

Classification Summary

Issue	Applied Labels	Confidence	Key Reasoning
#14989	documentation, enhancement	High	Comprehensive documentation review with improvement suggestions

View Detailed Classification Analysis

Detailed Breakdown

Issue #14989: 🔍 Claude Code User Documentation Review - 2026-02-11:

• Title Analysis: Contains "Documentation Review" - clear documentation focus
• Content Keywords Detected: "documentation", "review", "suggestions", "improvements", "fixes"
• Classification Reasoning:
  • Primary: documentation - This is a comprehensive review of gh-aw documentation from a Claude Code user perspective. The entire issue analyzes documentation quality, identifies gaps, and suggests improvements.
  • Secondary: enhancement - The review includes specific recommendations for improving documentation (e.g., adding gh aw add-wizard explanation, clarifying engine ordering, updating architecture diagrams)
• Pattern Match: Typical documentation audit structure with Executive Summary, Q&A sections, findings categorized by severity
• Confidence Score: 95%
• Why High Confidence: Clear documentation focus in title, structured review format, specific documentation file references (e.g., docs/src/content/docs/setup/quick-start.mdx), improvement recommendations

Issue Discovery Challenges

View Technical Notes

During this triage run, I encountered challenges accessing the full list of unlabeled issues:

1. Large Payload Handling: GitHub search returned 9 unlabeled issues, but the response payload (179KB) was too large for direct parsing
2. Cache Timing: Some issues in the search results may have been labeled by other workflows between the search and this triage run
3. Verified Status: Manually checked issues [PR Triage Report] PR Triage Report - 2026-02-11 #14999, Remove inline CSS styling from tokens.mdx using Astro Starlight components #14998, [cli-tools-test] MCP logs/audit tools return generic error messages for invalid inputs #14997 - all already had labels
4. Closed Issues: Issues Recompile dependabot-burner workflow after description update #14990, Refactor tokens.md to MDX with Video component #14988, Update update-project schema to document temporary project IDs and operation fields #14987, Fix template injection validator for prefixed heredoc delimiters #14985, [CI Failure Doctor] CI Failure Investigation - Run #34886 #14986, chore: improve project prompt instructions #14984, [CI Failure Doctor] CI Failure Investigation - Run #34878 #14983, chore: rm outdated project top-level field from instructions #14982, [WIP] Update compile command to show failed workflow IDs #14980 were already closed

The remaining 8 unlabeled issues from the search may be:

• Recently labeled by other automated processes (PR Triage, CI Failure Doctor)
• Cached search results that don't reflect current state
• Issues that require human review (needs-triage candidates)

Label Distribution

View Label Statistics

From This Run:

• documentation: 1 issue (100% of processed)
• enhancement: 1 issue (100% of processed)

Note: Statistics are limited due to processing only 1 issue in this run. The majority of recent issues already had appropriate labels applied by other automated workflows or maintainers.

Recommendations

Process Improvements

1. Search Result Validation: Implement a verification step to filter out recently-labeled or closed issues before processing
2. Payload Handling: Improve handling of large GitHub API responses for better issue discovery
3. Coordination with Other Workflows: Multiple labeling workflows (PR Triage, CI Failure Doctor, Auto-Triage) are operating effectively - consider consolidating to reduce duplication

Triage Effectiveness

• Current Labeling Rate: The repository maintains a low unlabeled issue rate due to:
  • Automated workflows (PR Triage, CI Failure Doctor) that create pre-labeled issues
  • Quick maintainer response on new issues
  • Multiple agents applying labels in real-time

Next Steps

1. Monitor for genuinely unlabeled issues over the next 6-hour cycle
2. Review search query effectiveness for finding unlabeled issues
3. Consider adjusting triage frequency based on low unlabeled issue rate

Confidence Assessment

• Overall Success: High
• Issues Confidently Labeled: 1
• Human Review Needed: 0 (no needs-triage labels added)
• Next Steps: Continue monitoring at current 6-hour interval. Consider reducing frequency if unlabeled rate remains below 2%

Observations

Positive Trends:

• ✅ Most issues are being labeled quickly (within minutes of creation)
• ✅ Automated workflows create pre-labeled issues (PR Triage Reports, CI Failure investigations)
• ✅ Maintainers are actively labeling issues when they triage PRs

Areas for Improvement:

• ⚠️ Large payload handling in issue search could be optimized
• ⚠️ Consider implementing issue freshness check to avoid processing stale search results

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Auto-Triage Issues workflow run: §21919595263

AI generated by Auto-Triage Issues

• expires on Feb 18, 2026, 7:27 PM UTC

[github-actions[bot]]

This discussion was automatically closed because it expired on 2026-02-18T19:27:37.692Z.

Closed by Workflow