🔍 Agentic Workflow Audit Report - 2025-10-10: Tool Availability Issues

[github-actions[bot]]

🔍 Agentic Workflow Audit Report - 2025-10-10

⚠️ Audit Status: INCOMPLETE

The automated agentic workflow audit was unable to complete due to critical tool availability issues.

Audit Summary

• Period: Last 24 hours (October 9-10, 2025)
• Runs Analyzed: 0 ❌
• Workflows Discovered: 48 total workflows in repository
• Agentic Workflows Identified: 13+
• Critical Issues: 2
• Status: Incomplete - Unable to fetch workflow run data

🚫 Critical Limitations Encountered

1. gh-aw MCP Server Unavailable

Severity: Critical
Impact: Cannot download workflow logs for analysis

The audit workflow requires the gh-aw MCP server to download workflow logs from the last 24 hours. The server is configured at `(redacted) but is not accessible during the audit workflow run.

Configuration found:

{
  "gh-aw": {
    "type": "http",
    "url": "(redacted)"
  }
}

Expected functionality: The logs tool from the gh-aw MCP server should allow downloading workflow logs with filters like:

• Time range (e.g., "-1d" for last 24 hours)
• Workflow name
• Engine type (claude, codex, copilot)
• Branch name

2. GitHub API Response Size Exceeds Limits

Severity: Critical
Impact: Cannot fetch workflow run details via GitHub MCP server

Attempted to use the GitHub MCP server's list_workflow_runs tool as a fallback, but responses exceed the 25,000 token limit even with minimal pagination (10 items per page).

Examples:

• Audit workflow (ID 195993955): 45,502 tokens for 10 runs
• Scout workflow (ID 181298242): 455,888 tokens for 100 runs
• CI Failure Doctor (ID 188421497): 140,895 tokens for 100 runs

This suggests workflow run objects contain extensive data that makes them unsuitable for bulk analysis.

🔧 Agentic Workflows Discovered

The audit identified the following agentic workflows in the repository:

1. Agentic Workflow Audit Agent (this workflow)
2. Scout - High activity, 455k+ tokens for 100 runs
3. CI Failure Doctor - 140k+ tokens for 100 runs
4. Dev - 459k+ tokens for 100 runs
5. Tidy
6. Technical Documentation Writer for GitHub Actions
7. Poem Bot - A Creative Agentic Workflow
8. Issue Classifier
9. Duplicate Code Detector
10. Changeset Generator
11. Issue Summary to Notion
12. CLI Version Checker
13. Issue Summarizer (GenAIScript)

Plus additional workflows for testing (Smoke Claude, Smoke Codex, Test Copilot, etc.)

📊 Missing Tools Analysis

Required Tool: gh-aw MCP Server

Tool Name: gh-aw MCP server with logs tool
Purpose: Download and analyze workflow logs from the last 24 hours
Current Status: Configured but not accessible
Workflows Affected: Agentic Workflow Audit Agent

Why this tool is needed:

• The audit agent needs to analyze actual workflow execution logs to identify:
  • Missing tools reported by workflows
  • Error patterns and failures
  • Performance metrics (tokens, costs, turns)
  • MCP server connectivity issues
  • Success/failure rates
• GitHub API provides workflow run metadata but not the detailed agent logs needed for comprehensive analysis

🎯 Recommendations

High Priority

1. Enable gh-aw MCP Server for Audit Workflow

   • Action: Configure the audit-workflows.lock.yml to start the gh-aw MCP server before running the audit
   • Benefit: Enables the core functionality of the audit agent
   • Implementation: The gh-aw binary appears to be built and available, but needs to be running as an HTTP server on localhost:8765 during audit execution

2. Implement Efficient Workflow Run Querying

   • Action: Create a lightweight API or tool that returns summarized workflow data
   • Options:
     • Use gh-aw logs tool (preferred)
     • Create a custom summary API endpoint
     • Store workflow summaries in a structured format during execution
   • Benefit: Enables bulk analysis of workflow runs without hitting token limits

Medium Priority

3. Create Audit-Friendly Log Storage

   • Action: Store workflow summaries in structured JSON format during execution
   • Benefit: Makes logs easily queryable and analyzable
   • Structure: Include key metrics (success, errors, missing tools, costs) in a standardized format

4. Implement Historical Trend Analysis

   • Action: Once logs are accessible, build trend analysis to track:
     • Error rates over time
     • Common failure patterns
     • Resource usage trends
     • Tool availability gaps
   • Benefit: Proactive identification of systemic issues

🗂️ Cache Memory Updated

The audit has created persistent cache memory at /tmp/gh-aw/cache-memory/:

cache-memory/
├── audits/
│   ├── index.json              ✅ Created
│   └── 2025-10-10.json         ✅ Created
└── patterns/
    └── missing-tools.json      ✅ Created

This cache will be used by future audit runs to track trends and historical context.

📋 Next Steps

• Enable gh-aw MCP server during audit workflow execution
• Verify logs tool functionality once MCP server is available
• Re-run audit to analyze last 24 hours of workflow activity
• Implement automated daily audit schedule
• Create alerting for critical issues found in audits

🔐 Security Notes

This audit workflow is designed to analyze workflow execution patterns and identify issues. It does not:

• Execute arbitrary code from logs
• Modify workflow configurations without review
• Access sensitive credentials or secrets

All findings are reported via GitHub Discussions for review and action by repository maintainers.

📈 Historical Context

This is the first audit run for this repository. No historical data is available for comparison. Future audits will track trends and improvements over time.

---

Audit Agent Version: 1.0
Execution Time: 2025-10-10T05:10:11.935Z
Run ID: 18397048120
Repository: githubnext/gh-aw
Branch: discussion-tests

AI generated by Agentic Workflow Audit Agent

[github-actions[bot]]

This discussion was automatically closed because it was created by an agentic workflow more than 1 month ago.