🏥 Safe Output Health Report - January 15, 2026

[github-actions[bot]]

Executive Summary

Health Status: ⚠️ Moderate - Recurring Issues Detected

The safe output health monitoring system analyzed 10 workflow runs from the last 24 hours. While the safe output validation is working correctly, we identified 2 recurring error patterns that indicate underlying workflow configuration and agent prompt issues requiring attention.

• Period: Last 24 hours (January 15, 2026)
• Runs Analyzed: 10
• Workflows Active: 6 (Smoke Claude, Smoke Codex, Smoke Copilot, Changeset Generator, Code Scanning Fixer, Issue Monster)
• Safe Output Jobs Executed: 19 operations across 9 runs
• Safe Output Jobs Failed: 4 (21.1% failure rate)
• Error Clusters Identified: 2 (both recurring from previous audits)

Safe Output Job Statistics

Job Type	Total Executions	Failures	Success Rate
add_comment	8	3	62.5%
add_labels	2	0	100%
missing_tool	3	0	100%
update_pull_request	2	1	50%
TOTAL	19	4	78.9%

🚨 Critical Finding: Recurring Error Patterns

Both error clusters identified today are recurring issues from previous audits (January 12-13), indicating that root causes have not yet been addressed:

Cluster 1: Update Pull Request with Empty Fields ⚠️

• Pattern ID: update-pull-request-empty-fields
• First Seen: 2026-01-12 | Last Seen: 2026-01-15 (TODAY)
• Occurrences: 2 total (1 today)
• Status: 🔴 RECURRING - Not resolved from previous audit

Cluster 2: Add Comment Context Mismatch in Schedule ⚠️

• Pattern ID: add-comment-context-mismatch-schedule
• First Seen: 2026-01-13 | Last Seen: 2026-01-15 (TODAY)
• Occurrences: 6 total (3 today)
• Status: 🔴 RECURRING - Not resolved from previous audit

Error Clusters

Cluster 1: Update Pull Request with Empty Fields 📝

Count: 1 occurrence
Severity: Low
Status: Working as intended (validation), but indicates agent prompt issue

Affected Workflow:

• Changeset Generator (run #841)
  • Agent: Codex (gpt-5-mini)
  • Event: pull_request on PR Add host.docker.internal to Codex default domains for MCP gateway access #9999
  • Conclusion: success (overall workflow succeeded despite validation failure)

Error Message:

##[warning]No update fields provided or all fields are disabled
##[error]✗ Message 1 (update_pull_request) failed: No update fields provided or all fields are disabled

Root Cause: The Changeset Generator workflow agent produced a safe output message to update a pull request, but the message contained no body or title fields to actually update. The safe output handler correctly validated this and rejected the empty update request.

Impact: Pull request was not updated (correct behavior). This is proper validation working as designed, but it indicates the agent is generating unnecessary/empty output.

Why This Is Concerning: This exact error pattern was seen on 2026-01-12 for the same workflow, suggesting a systematic issue in the Changeset Generator's agent prompt that consistently produces empty update messages.

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Cluster 2: Add Comment Context Mismatch in Scheduled Workflows 📅

Count: 3 occurrences (all in one workflow run)
Severity: Medium
Status: Working as intended (validation), but indicates workflow configuration issue

Affected Workflow:

• Issue Monster (run #1258)
  • Agent: GitHub Copilot CLI
  • Event: schedule (cron job)
  • Conclusion: success (overall workflow succeeded, 0/6 safe output messages succeeded, 3/6 failed, 3/6 skipped)

Error Message:

##[warning]Target is "triggering" but not running in issue or pull request context, skipping add_comment
##[error]✗ Message 4 (add_comment) failed: Target is "triggering" but not running in issue or pull request context, skipping add_comment

Root Cause: The Issue Monster workflow runs on a schedule and attempts to add comments using target='triggering'. However, in a scheduled context (cron job), there is no "triggering" issue or pull request to comment on. The safe output handler correctly validates this context mismatch and rejects the comments.

Impact: 3 comments were not posted (correct behavior). The agent generated 6 safe output messages, but only 3 were applicable to the scheduled context. This is proper validation, but indicates the agent doesn't understand the execution context.

Why This Is Concerning: This exact error pattern was seen on 2026-01-13 for the same workflow, suggesting a systematic configuration issue where the Issue Monster workflow and/or its agent prompt is not properly configured for scheduled execution.

Root Cause Analysis

Validation Errors (Both Clusters)

Good News: The safe output validation system is working perfectly - it's catching invalid operations and preventing incorrect API calls.

Bad News: Both error patterns are recurring from previous days, indicating that the underlying issues have not been addressed:

1. Changeset Generator consistently produces empty update_pull_request messages
2. Issue Monster consistently attempts to use target='triggering' in scheduled context where it doesn't make sense

Why These Are Recurring

These patterns suggest configuration drift or insufficient feedback loops:

• Agent prompts may not have been updated after initial error detection
• Workflow configurations haven't been adjusted to match agent behavior
• No automated alerts or tracking for recurring validation failures

Recommendations

🔴 Critical Issues (Immediate Action Required)

1. Fix Changeset Generator Empty Update Messages

• Priority: Medium
• Root Cause: Agent prompt generates update_pull_request with no content
• Recommended Action:
  • Review Changeset Generator agent prompt to ensure it only generates update_pull_request when there's actual content to update
  • Add agent-side logic to check if body/title exist before creating the message
  • Consider removing update_pull_request functionality if not needed
• Affected: Changeset Generator workflow
• Tracking: Recurring since 2026-01-12

2. Fix Issue Monster Scheduled Context Handling

• Priority: High
• Root Cause: Workflow uses target='triggering' for add_comment in schedule context
• Recommended Action:
  • Update Issue Monster workflow configuration to use explicit issue numbers instead of 'triggering' target
  • Modify agent prompt to understand scheduled execution context and generate explicit target issue numbers
  • Consider using assign_to_agent or creating new issues instead of commenting on non-existent triggering context
• Affected: Issue Monster workflow
• Tracking: Recurring since 2026-01-13

📊 Process Improvements

1. Implement Recurring Error Detection

• Current State: Errors are logged but not tracked for recurrence
• Proposed: Add automated detection of error patterns that repeat across multiple days
• Benefits: Early warning system for systematic issues that need configuration changes

2. Add Workflow Health Metrics

• Current State: Per-run success tracking only
• Proposed: Track per-workflow success rates over time, alert on declining trends
• Benefits: Identify workflows that consistently produce validation errors

3. Create Agent Prompt Testing Framework

• Current State: Agent prompts updated manually without validation
• Proposed: Test agent prompts against common scenarios before deployment
• Benefits: Catch context mismatches and empty messages before they reach production

4. Enhance Safe Output Documentation

• Current State: Basic documentation of safe output capabilities
• Proposed: Add context-aware examples (schedule vs pull_request vs issue_comment events)
• Benefits: Workflow authors understand which safe outputs work in which contexts

Historical Context

Trend Analysis

Date	Success Rate	Failed Ops	Status
Jan 15	78.9%	4	⚠️ Moderate (recurring issues)
Jan 14	94.1%	1	✅ Good
Jan 13	50.0%	7	🔴 Poor
Jan 11	100%*	2	⚠️ Bug found (fixed in PR #9666)
Jan 07	73.7%	5	⚠️ Moderate
Jan 06	100%	1	✅ Excellent

* Jan 11 had a false success reporting bug that was fixed

Recurring Issues Tracking

• update-pull-request-empty-fields: Seen on Jan 12, Jan 15 (2 occurrences)
• add-comment-context-mismatch-schedule: Seen on Jan 13, Jan 15 (6 occurrences)
• close-discussion-category-mismatch: Seen on Jan 14 only (1 occurrence)

Key Observations

1. Validation is working correctly - All errors are proper validation catching invalid operations
2. Recurring patterns indicate systemic issues - Same workflows producing same errors multiple days in a row
3. Success rate volatility - Ranges from 50% to 100%, with today at 78.9%
4. No API or infrastructure errors - All errors are validation/configuration related

Work Item Plans

Work Item 1: Fix Changeset Generator Empty Updates

• Type: Configuration / Prompt Enhancement
• Priority: Medium
• Description: Changeset Generator consistently produces empty update_pull_request messages that fail validation (seen Jan 12, Jan 15)
• Acceptance Criteria:
  • Changeset Generator only creates update_pull_request messages when there's actual content
  • Zero validation failures for "No update fields provided" in next 7 days
  • Agent prompt documentation updated with best practices
• Technical Approach:
  1. Review Changeset Generator workflow prompt
  2. Add conditional logic to only generate update_pull_request if body or title exists
  3. Test with sample PRs to verify no empty messages
  4. Deploy and monitor for 7 days
• Estimated Effort: Small (2-4 hours)
• Dependencies: Access to workflow configuration files

Work Item 2: Fix Issue Monster Schedule Context

• Type: Configuration / Workflow Enhancement
• Priority: High
• Description: Issue Monster workflow fails 50% of add_comment operations in scheduled context by using target='triggering' (seen Jan 13, Jan 15)
• Acceptance Criteria:
  • Issue Monster scheduled runs have 0% add_comment validation failures
  • Agent understands scheduled vs triggered context and generates appropriate targets
  • Safe output success rate for Issue Monster reaches 90%+
• Technical Approach:
  1. Update Issue Monster workflow configuration to pass execution context to agent
  2. Modify agent prompt to generate explicit issue numbers in scheduled context
  3. Consider alternative approach: use create_issue instead of add_comment for schedule
  4. Test scheduled and triggered executions separately
  5. Deploy and monitor for 7 days
• Estimated Effort: Medium (4-8 hours)
• Dependencies: Understanding of Issue Monster workflow logic

Work Item 3: Implement Recurring Error Alerting

• Type: Enhancement / Monitoring
• Priority: Medium
• Description: Add automated detection and alerting for error patterns that recur across multiple days
• Acceptance Criteria:
  • System detects when same error pattern appears 3+ days
  • Automated alert (discussion/issue) created for recurring patterns
  • Alert includes workflow name, error pattern, and recommended fixes
• Technical Approach:
  1. Extend safe output health monitor to track error history
  2. Add pattern matching logic to identify recurring issues
  3. Create automated discussion/issue when threshold reached
  4. Include links to affected runs and historical context
• Estimated Effort: Medium (6-10 hours)
• Dependencies: None

Work Item 4: Create Context-Aware Safe Output Documentation

• Type: Documentation
• Priority: Low
• Description: Enhance safe output documentation with context-specific examples and limitations
• Acceptance Criteria:
  • Documentation includes context matrix (which safe outputs work in which event types)
  • Examples provided for schedule, pull_request, issue_comment, and discussion events
  • Common pitfalls section added (like target='triggering' in schedule)
• Technical Approach:
  1. Audit all safe output handlers for context requirements
  2. Create context compatibility matrix
  3. Write examples for each event type + safe output combination
  4. Add troubleshooting section for common validation errors
• Estimated Effort: Small (3-5 hours)
• Dependencies: Access to safe output handler code

Metrics and KPIs

• Overall Safe Output Success Rate: 78.9% (down from 94.1% yesterday)
• Most Reliable Job Type: add_labels and missing_tool (100% success rate)
• Most Problematic Job Type: add_comment (62.5% success rate, dragged down by context mismatches)
• Workflows with Perfect Safe Output Health:
  • Smoke Claude (2/2 runs: 100%)
  • Smoke Codex (2/2 runs: 100%)
  • Smoke Copilot (2/2 runs: 100%)
  • Code Scanning Fixer (1/1 runs: N/A - no safe outputs)
• Workflows Needing Attention:
  • Issue Monster (0% safe output success in scheduled run)
  • Changeset Generator (50% safe output success, empty update messages)

Next Steps

• URGENT: Review Issue Monster workflow configuration and fix scheduled context handling
• Review Changeset Generator agent prompt to eliminate empty update messages
• Implement recurring error detection and alerting system
• Create context-aware safe output documentation
• Monitor both workflows over next 7 days to verify fixes are effective
• Consider implementing agent prompt testing framework for future workflows

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About This Report

This report was automatically generated by the Safe Output Health Monitor, which audits all agentic workflow runs daily to identify patterns, errors, and opportunities for improvement in the safe output job execution system.

Data Sources:

• Workflow logs from 10 runs (January 15, 2026)
• Historical audit data (6 previous audits)
• Error pattern database (6 known patterns)

Cache Location: /tmp/gh-aw/cache-memory/safe-output-health/2026-01-15.json

References:

• §21049165919 - Issue Monster with add_comment failures
• §21048252402 - Changeset Generator with empty update_pull_request
• §21049334837 - Smoke Claude with perfect safe output health

AI generated by Safe Output Health Monitor