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Period: Last 24 hours (2026-01-28) Runs Analyzed: 9 workflow runs Workflows Active: 2 unique workflows Safe Output Jobs Executed: 6 Safe Output Jobs Failed: 0 Success Rate: 83.3% (5/6 successful) Error Clusters Identified: 1 (handled gracefully with fallback)
Overall Health Status: ✅ HEALTHY - All safe output jobs completed successfully. One job encountered a GitHub API permission error but successfully used fallback mechanism to create an issue instead of a PR.
Safe Output Job Statistics
Job Type
Total Executions
Failures
Success Rate
Overall
6
0
100%
noop
5
0
100%
create_pull_request
1
0
100%*
add_comment
1
0
100%
* One create_pull_request job used fallback mechanism (created issue instead of PR due to permission constraints)
Handler Usage Distribution
The following safe output handlers were loaded and available across runs:
Handler
Times Loaded
Times Used
add_comment
6
1
noop
6
5
missing_tool
6
0
missing_data
6
0
create_pull_request
1
1
Analysis: Most workflows (5/6) completed with noop messages, indicating agents found no issues requiring action. This is expected behavior for monitoring workflows like Security Guard.
Error Clusters
Cluster 1: GitHub Workflow Permission Error
Count: 1 occurrence
Affected Jobs: create_pull_request
Affected Workflows: Q (Workflow Optimizer)
Severity: Medium (gracefully handled)
Sample Error:
error: failed to push some refs to 'https://github.com/githubnext/gh-aw.git'
! [remote rejected] q/fix-pr-triage-label-proliferation-c5ecf218a92d04ca ->
q/fix-pr-triage-label-proliferation-c5ecf218a92d04ca
(refusing to allow a GitHub App to create or update workflow `.github/workflows/pr-triage-agent.md`
without `workflows` permission)
Root Cause: The GitHub App token used by the workflow lacks the workflows permission required to push changes to files in .github/workflows/ directory. This is a GitHub security feature to prevent unauthorized workflow modifications.
Impact: Pull requests that modify workflow files cannot be created directly via the safe output handler. However, the system gracefully handled this by creating a fallback issue #12385 with the patch attached.
Current Mitigation: The create_pull_request handler automatically detects git push failures and creates a fallback issue containing the patch content. This allows manual PR creation while maintaining transparency about the attempted changes.
Root Cause Analysis
Permission-Related Issues
Issue: GitHub App lacks workflows permission Why it matters: Workflows that attempt to optimize or modify other workflows (like the Q agent) cannot create PRs directly. Current state: Working as designed with fallback mechanism. Should we fix it?: This is a design decision:
Option A (Current): Keep restricted permissions, use fallback issues for workflow changes
✅ More secure (prevents malicious workflow modifications)
✅ Fallback mechanism works well
❌ Requires manual PR creation
Option B: Grant workflows permission to GitHub App
✅ Enables automated PR creation for workflow changes
❌ Security risk (app could modify workflows)
❌ Requires permission escalation
Recommendation: Keep current approach. The fallback mechanism works well and maintains security boundaries.
Workflow Breakdown
1. Security Guard Agent 🛡️
Runs: 6
Safe Output Jobs: 5
Success Rate: 100%
Message Types: All noop (no security concerns found)
Performance: Excellent - consistently completes with no issues
2. Q (Workflow Optimizer)
Runs: 1
Safe Output Jobs: 1
Success Rate: 100% (with fallback)
Message Types: create_pull_request, add_comment
Performance: Good - successfully created fallback issue and added comment despite permission constraints
3. Issue Monster
Runs: 2
Safe Output Jobs: 0
Notes: These runs did not trigger safe output jobs (likely exited early or produced no output)
Recommendations
No Critical Issues Identified
All safe output jobs are functioning correctly. No bugs or critical issues require immediate attention.
Enhancement Opportunities
1. Improve Workflow Metadata Tracking
Priority: Low Issue: The analysis showed workflow_id as "unknown" for all runs because the aw_info.json file doesn't include the correct workflow_id field.
Current State:
{
"workflow_name": "Security Guard Agent 🛡️",
"workflow_id": "unknown"// Should be "security-guard"
}
Proposed Fix: Update the agent output artifact generation to include the correct GH_AW_WORKFLOW_ID in aw_info.json.
Benefits:
Better trend tracking per workflow
More accurate reporting
Easier debugging
Effort: Small Impact: Low (cosmetic improvement for reporting)
2. Document Fallback Mechanism Behavior
Priority: Low Issue: The fallback mechanism (creating issues instead of PRs) works well but may surprise users.
Proposed Action: Add documentation explaining:
When fallbacks occur (permission errors, API failures)
What information is preserved (patch, PR body, metadata)
How to manually create PR from fallback issue
Benefits:
Better user understanding
Reduced confusion about "failed" PR creations
Clearer expectations
Effort: Small (documentation only) Impact: Low (user experience improvement)
3. Add Safe Output Health Dashboard
Priority: Low Issue: Currently no centralized view of safe output health over time.
Proposed Enhancement: Create a dashboard workflow that:
Tracks success rates over time
Identifies trending issues
Shows handler usage patterns
Highlights degradation in performance
Benefits:
Proactive issue detection
Historical trend analysis
Better visibility into system health
Effort: Medium Impact: Medium (operational improvement)
Note: This audit report serves as a prototype for such a dashboard.
Historical Context
First Audit: This is the first safe output health audit, establishing baseline metrics.
✅ None required - All safe output jobs are functioning correctly
Future Enhancements
Consider documenting the fallback mechanism behavior for workflow permission errors
Track whether workflow_id metadata issue recurs in future audits
Monitor if fallback mechanism is used frequently (may indicate permission configuration issue)
Monitoring
Continue daily safe output health audits
Watch for trends in error rates or new error patterns
Track handler usage patterns to identify underutilized or problematic handlers
Audit Methodology
This audit analyzed:
9 workflow runs from the last 24 hours
6 safe output job executions
All job logs, error messages, and completion statuses
Message type distribution and handler usage patterns
Analysis approach:
Downloaded workflow logs using gh-aw MCP server
Parsed safe output job logs for errors, warnings, and statistics
Clustered errors by type and root cause
Verified fallback mechanisms and mitigation strategies
Stored findings in cache memory for trend analysis
Data storage: Analysis results saved to /tmp/gh-aw/cache-memory/safe-output-health/ for historical tracking.
Conclusion
System Health: ✅ EXCELLENT
The safe output handler system is performing well with a 100% completion rate. The one error encountered (GitHub workflow permission) was gracefully handled by the fallback mechanism, demonstrating robust error handling. No bugs or critical issues were identified.
All monitored workflows (Security Guard, Q) are functioning as expected. The high prevalence of noop messages indicates agents are appropriately selective about when to create outputs, reducing noise and focusing on actionable issues.
Key Takeaway: The safe output system is stable, reliable, and well-designed with effective fallback mechanisms for known failure scenarios.
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Executive Summary
Period: Last 24 hours (2026-01-28)
Runs Analyzed: 9 workflow runs
Workflows Active: 2 unique workflows
Safe Output Jobs Executed: 6
Safe Output Jobs Failed: 0
Success Rate: 83.3% (5/6 successful)
Error Clusters Identified: 1 (handled gracefully with fallback)
Overall Health Status: ✅ HEALTHY - All safe output jobs completed successfully. One job encountered a GitHub API permission error but successfully used fallback mechanism to create an issue instead of a PR.
Safe Output Job Statistics
* One
create_pull_requestjob used fallback mechanism (created issue instead of PR due to permission constraints)Handler Usage Distribution
The following safe output handlers were loaded and available across runs:
Analysis: Most workflows (5/6) completed with
noopmessages, indicating agents found no issues requiring action. This is expected behavior for monitoring workflows like Security Guard.Error Clusters
Cluster 1: GitHub Workflow Permission Error
Root Cause: The GitHub App token used by the workflow lacks the
workflowspermission required to push changes to files in.github/workflows/directory. This is a GitHub security feature to prevent unauthorized workflow modifications.Impact: Pull requests that modify workflow files cannot be created directly via the safe output handler. However, the system gracefully handled this by creating a fallback issue #12385 with the patch attached.
Current Mitigation: The
create_pull_requesthandler automatically detects git push failures and creates a fallback issue containing the patch content. This allows manual PR creation while maintaining transparency about the attempted changes.Root Cause Analysis
Permission-Related Issues
Issue: GitHub App lacks
workflowspermissionWhy it matters: Workflows that attempt to optimize or modify other workflows (like the Q agent) cannot create PRs directly.
Current state: Working as designed with fallback mechanism.
Should we fix it?: This is a design decision:
Option A (Current): Keep restricted permissions, use fallback issues for workflow changes
Option B: Grant
workflowspermission to GitHub AppRecommendation: Keep current approach. The fallback mechanism works well and maintains security boundaries.
Workflow Breakdown
1. Security Guard Agent 🛡️
noop(no security concerns found)2. Q (Workflow Optimizer)
create_pull_request,add_comment3. Issue Monster
Recommendations
No Critical Issues Identified
All safe output jobs are functioning correctly. No bugs or critical issues require immediate attention.
Enhancement Opportunities
1. Improve Workflow Metadata Tracking
Priority: Low
Issue: The analysis showed
workflow_idas "unknown" for all runs because theaw_info.jsonfile doesn't include the correctworkflow_idfield.Current State:
{ "workflow_name": "Security Guard Agent 🛡️", "workflow_id": "unknown" // Should be "security-guard" }Proposed Fix: Update the agent output artifact generation to include the correct
GH_AW_WORKFLOW_IDinaw_info.json.Benefits:
Effort: Small
Impact: Low (cosmetic improvement for reporting)
2. Document Fallback Mechanism Behavior
Priority: Low
Issue: The fallback mechanism (creating issues instead of PRs) works well but may surprise users.
Proposed Action: Add documentation explaining:
Benefits:
Effort: Small (documentation only)
Impact: Low (user experience improvement)
3. Add Safe Output Health Dashboard
Priority: Low
Issue: Currently no centralized view of safe output health over time.
Proposed Enhancement: Create a dashboard workflow that:
Benefits:
Effort: Medium
Impact: Medium (operational improvement)
Note: This audit report serves as a prototype for such a dashboard.
Historical Context
First Audit: This is the first safe output health audit, establishing baseline metrics.
Baseline Metrics Established:
noop(83%)Trends: N/A (insufficient historical data)
Metrics and KPIs
noop(5/7 messages)Detailed Run Analysis
View Individual Run Details
Successful Runs (5)
Run §21458347359 - Security Guard Agent 🛡️
Run §21458367072 - Security Guard Agent 🛡️
Run §21458590059 - Security Guard Agent 🛡️
Run §21459054297 - Security Guard Agent 🛡️
Run §21459104816 - Security Guard Agent 🛡️
Runs with Warnings (1)
Runs without Safe Output Jobs (3)
Run §21458312357 - Security Guard Agent 🛡️
Run §21458618467 - Issue Monster
Run §21459233260 - Unknown
Next Steps
Immediate Actions
Future Enhancements
workflow_idmetadata issue recurs in future auditsMonitoring
Audit Methodology
This audit analyzed:
Analysis approach:
Data storage: Analysis results saved to
/tmp/gh-aw/cache-memory/safe-output-health/for historical tracking.Conclusion
System Health: ✅ EXCELLENT
The safe output handler system is performing well with a 100% completion rate. The one error encountered (GitHub workflow permission) was gracefully handled by the fallback mechanism, demonstrating robust error handling. No bugs or critical issues were identified.
All monitored workflows (Security Guard, Q) are functioning as expected. The high prevalence of
noopmessages indicates agents are appropriately selective about when to create outputs, reducing noise and focusing on actionable issues.Key Takeaway: The safe output system is stable, reliable, and well-designed with effective fallback mechanisms for known failure scenarios.
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