🔍 Agentic Workflow Audit Report - October 19, 2025

[dsyme]

🔍 Agentic Workflow Audit Report - October 19, 2025

Audit Summary

• Period: Last 24 hours (Oct 18, 2025 00:00 UTC - Oct 19, 2025 00:36 UTC)
• Runs Analyzed: 13 workflow runs
• Workflows Active: 5 unique workflows
• Success Rate: 76.9% (10 successful, 3 failed)
• Total Duration: 54.6 minutes
• Total Cost: $0.38
• Total Tokens: 436,228
• Issues Found: 2 critical, 1 high severity

---

🚨 Critical Issues

1. Issue Classifier Workflow Failures ⚠️ CRITICAL

Status: 🔴 Active - 2 consecutive failures

Affected Runs:

• Run #18621246285 - Failed at 2025-10-18 21:31:57Z
• Run #18620849104 - Failed at 2025-10-18 20:53:50Z

Problem:
The Issue Classifier workflow (Claude engine) is failing completely. The agent job completes with failure status before generating any agent logs, indicating the workflow is failing during activation or initialization.

Impact:

• All new issues are not being classified
• 0% success rate for this workflow in the last 24 hours
• Workflow has been broken for at least 3 hours

Recommended Action:

1. Investigate Issue Classifier workflow configuration in .github/workflows/issue-classifier.yml
2. Check activation steps and agent initialization
3. Review recent changes to the workflow or engine configuration
4. Test workflow manually with workflow_dispatch to reproduce

Priority: 🔴 URGENT - This affects all new issue processing

---

2. Drain3 MCP Server Errors 🐛 HIGH

Status: 🟠 Active - 5 failures across multiple runs

Affected Runs:

• Run #18619633056 - Failed
• Run #18620619494 - Succeeded with errors
• Run #18621256245 - Succeeded with errors
• Run #18621510852 - Succeeded with errors
• Run #18622074727 - Succeeded with errors

Problem:

'dict' object has no attribute 'mask_with'

The drain3 MCP server is experiencing attribute errors during index_file tool operations. This appears to be a bug in the new drain3 server integration being developed on the copilot/add-drain3-shared-workflow branch.

Impact:

• Drain3 MCP server tool calls fail
• Workflows continue but lose drain3 functionality
• All 5 failures occurred in Dev workflows testing drain3 integration

Recommended Action:

1. Review drain3 MCP server implementation for mask_with attribute usage
2. Check if dict objects need to be converted to proper objects with attributes
3. Add error handling for missing attributes
4. Add integration tests for drain3 MCP server

Priority: 🟠 HIGH - Blocks drain3 integration work

---

📊 Performance Metrics

Overall Statistics

Metric	Value	Change vs Oct 18
Total Runs	13	⬇️ -31.6% (was 19)
Success Rate	76.9%	⬇️ -12.6pp (was 89.5%)
Total Cost	$0.38	⬇️ -84.7% (was $2.49)
Total Tokens	436,228	⬇️ -86.4% (was 3.2M)
Avg Duration	4.2 min	Similar

By Engine

Engine	Runs	Success Rate	Avg Cost
Copilot	10	80%	$0.00
Claude	2	50%	$0.19
Codex	1	100%	$0.00

By Workflow

Workflow	Runs	Success	Failed	Success Rate
Dev	8	7	1	87.5%
Issue Classifier	2	0	2	0% 🔴
Changeset Generator	1	1	0	100% ✅
Duplicate Code Detector	1	1	0	100% ✅
Tidy	1	1	0	100% ✅

Cost Analysis

Highest Cost Run:

• Run: #18619603157
• Workflow: Changeset Generator
• Cost: $0.38
• Tokens: 436,228
• Turns: 25
• Duration: 2.6 minutes
• Status: ✅ Success

Longest Running:

• Run: #18620774112
• Workflow: Duplicate Code Detector
• Duration: 8.5 minutes
• Turns: 39
• Status: ✅ Success

---

🔧 MCP Server Health

Active MCP Servers

Server	Status	Calls	Issues
github	✅ Healthy	384	None
safe_outputs	✅ Healthy	18	None
drain3	🔴 Failing	5+	mask_with attribute error

MCP Server Failures

New Failures: drain3 MCP server (5 failures)

• First seen: 2025-10-18
• Error: 'dict' object has no attribute 'mask_with'
• Tool: index_file
• Status: Active/Unresolved

Previous Failures: github MCP server (1 failure on Oct 14)

• Status: No recurrence, appears resolved

---

⚠️ Recurring Warnings

Permission Denied Warnings

• Count: 141 occurrences
• Message: "Permission denied and could not request permission from user"
• Severity: Low (known issue)
• Impact: None - workflows continue successfully
• Status: Known issue, doesn't block execution
• Note: This is expected in non-interactive workflow contexts

---

📈 Historical Comparison

Trend Analysis (vs Oct 18)

Improvements ✅:

• Lower costs and token usage (more efficient)
• Token limit issues from Oct 18 not seen today

Regressions ⚠️:

• Success rate dropped 12.6 percentage points
• New critical issue: Issue Classifier failures
• New MCP failure: drain3 server errors
• Activity level decreased

Issue Status

Resolved:

• ✅ Token limit exceeded on search results (not seen today)

New:

• 🔴 Issue Classifier workflow failures (critical)
• 🟠 Drain3 MCP server errors (high)

Ongoing:

• 🟡 Permission denied warnings (low, expected)

---

✅ Missing Tools Analysis

Good News: Zero missing tool requests detected!

No workflows requested tools that were unavailable. All MCP servers provided expected tools successfully (even though drain3 tools are failing due to bugs, they are present).

---

📋 Recommendations

Immediate Actions (Next 24 Hours)

1. 🔴 URGENT: Investigate and fix Issue Classifier workflow failures

   • Check workflow configuration
   • Review activation steps
   • Test manually with workflow_dispatch
   • Priority: Critical

2. 🟠 HIGH: Fix drain3 MCP server mask_with attribute error

   • Review dict to object conversion
   • Add proper error handling
   • Add integration tests
   • Priority: High

3. 🟡 MEDIUM: Monitor workflow health after fixes

   • Watch Issue Classifier for continued issues
   • Verify drain3 fix resolves all errors
   • Check for new error patterns

Long-term Improvements

1. Add pre-flight checks to Issue Classifier to catch initialization failures early
2. Implement comprehensive MCP server health monitoring
3. Add automated alerts for workflow failure spikes
4. Consider improving error detection to reduce false positives from log parsing

---

🎯 Next Audit

The next audit will run in 24 hours (2025-10-20 00:00 UTC) and will focus on:

• ✅ Verifying Issue Classifier fixes
• ✅ Confirming drain3 MCP server stability
• 📊 Comparing success rates and costs
• 🔍 Detecting any new error patterns

---

📁 Audit Data

Full audit data and historical patterns are stored in:

• /tmp/gh-aw/cache-memory/audits/2025-10-19.json
• /tmp/gh-aw/cache-memory/patterns/errors.json
• /tmp/gh-aw/cache-memory/patterns/mcp-failures.json

---

Audit completed at: 2025-10-19 00:36 UTC
Audit agent: Agentic Workflow Audit Agent
Data source: gh-aw MCP server logs (last 24 hours)

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.