Workflow Health Dashboard - December 25, 2024

[github-actions]

Overview

Analysis Date: December 25, 2024
Workflow Health Manager Run: #20497822471

Summary Statistics

• Total Workflows: 124
• Compilation Status: ✅ 100% (124/124 have .lock.yml files)
• Missing Lock Files: 0
• Workflow Categories: 5 main categories identified

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✅ Compilation Health: EXCELLENT

All 124 executable workflows in .github/workflows/ have successfully compiled .lock.yml files. No compilation issues detected.

Note: Workflows in .github/workflows/shared/ are intentionally excluded as they are reusable imports, not standalone executables.

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📊 Workflow Categories

Meta-Orchestrators (4 workflows)

These high-level workflows coordinate and manage other workflows:

1. metrics-collector.md - Infrastructure agent collecting daily performance metrics
2. campaign-manager.md - Manages campaigns and analyzes performance
3. agent-performance-analyzer.md - Analyzes AI agent quality and effectiveness
4. workflow-health-manager.md - Monitors workflow ecosystem health (this workflow)

Daily Scheduled Workflows (16 workflows)

Regular maintenance and monitoring tasks:

• daily-assign-issue-to-user.md
• daily-choice-test.md
• daily-code-metrics.md
• daily-copilot-token-report.md
• daily-doc-updater.md
• daily-fact.md
• daily-file-diet.md
• daily-firewall-report.md
• daily-issues-report.md
• daily-malicious-code-scan.md
• daily-multi-device-docs-tester.md
• daily-news.md
• daily-performance-summary.md
• daily-repo-chronicle.md
• daily-team-status.md
• daily-workflow-updater.md

Smoke Test Workflows (10 workflows)

Testing different engine and configuration combinations:

• smoke-claude.md
• smoke-codex-firewall.md
• smoke-codex.md
• smoke-copilot-no-firewall.md
• smoke-copilot-playwright.md
• smoke-copilot-safe-inputs.md
• smoke-copilot.md
• smoke-detector.md
• smoke-srt-custom-config.md
• smoke-srt.md

Campaign Workflows (1 workflow)

• go-file-size-reduction-project64.campaign.g.md

Event-Triggered & Specialized Workflows (93 workflows)

Various workflows triggered by pull requests, issues, workflow_run events, and other GitHub events.

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🔍 Analysis Limitations

Current Run Constraints

GitHub API Access: ⚠️ Not Available

• The gh CLI is not authenticated in this workflow run
• Cannot query recent workflow run history
• Cannot fetch success/failure rates from GitHub Actions API
• Cannot access detailed error logs or timing data

**Metrics (redacted) ⚠️ Not Available

• Expected metrics at /tmp/gh-aw/repo-memory-default/memory/meta-orchestrators/metrics/latest.json
• Metrics directory appears empty (may not be populated yet)
• Historical daily metrics not accessible

Impact:

• This analysis is compilation-focused only
• Cannot assess runtime health, failure rates, or execution patterns
• Cannot identify failing workflows or error trends
• Cannot calculate reliability scores or MTBF

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🎯 Recommendations

1. Enable Metrics Collection (P1)

The metrics-collector workflow should run daily and populate:

• /tmp/gh-aw/repo-memory-default/memory/meta-orchestrators/metrics/latest.json
• /tmp/gh-aw/repo-memory-default/memory/meta-orchestrators/metrics/daily/YYYY-MM-DD.json

Action Required: Verify metrics-collector workflow is scheduled and running successfully.

2. GitHub API Access Configuration (P2)

For comprehensive health monitoring, this workflow needs:

• GitHub Actions read permissions (✅ already configured)
• Either:
  • Authenticated gh CLI access, OR
  • GitHub MCP tool with actions toolset (✅ already configured)

Current Configuration:

tools:
  github:
    mode: remote
    toolsets: [default, actions]

Note: The workflow has the right configuration but may need to use MCP tools instead of gh CLI for querying workflow runs.

3. Enhanced Monitoring Capabilities (P3)

Once metrics and API access are available, this workflow can provide:

• Workflow success/failure rates over time
• Identification of consistently failing workflows
• Error pattern analysis across the ecosystem
• Resource utilization tracking
• Automated issue creation for degraded workflows
• Trend analysis and predictive health scoring

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📈 Next Steps

1. Verify metrics-collector: Confirm it's running and populating metrics data
2. Test MCP GitHub tools: Use GitHub MCP server to query workflow runs
3. Build historical baseline: Accumulate 7-30 days of metrics for trend analysis
4. Implement health scoring: Calculate reliability scores once run data is available
5. Automate issue creation: Create issues for P0/P1 workflows when problems detected

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🏆 Current Status: HEALTHY (Compilation)

Compilation Health: 100% ✅

• Zero workflows missing lock files
• Zero compilation errors detected
• All workflows ready for execution

Runtime Health: Unknown ⚠️

• Pending metrics data availability
• Pending GitHub API access validation
• Will be assessed in future runs

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Workflow Health Manager | Meta-Orchestrator
Run ID: 20497822471 | Generated: 2024-12-25T02:53:48Z
Next scheduled check: Daily at ~00:00 UTC

AI generated by Workflow Health Manager - Meta-Orchestrator