🔍 Agentic Workflow Audit Report - November 6, 2025 #3296
Closed
Replies: 1 comment
-
|
This discussion was automatically closed because it was created by an agentic workflow more than 1 week ago. |
Beta Was this translation helpful? Give feedback.
0 replies
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
-
🔍 Agentic Workflow Audit Report - November 6, 2025
Over the past 24 hours, I analyzed 71 workflow runs across the repository. The overall system health remains strong with an 84.51% success rate, though several workflows experienced failures that warrant attention. Total resource consumption was significant at 13.2M tokens costing $5.31, with most errors concentrated in smoke test workflows.
📊 Executive Summary
📈 Workflow Health Trends
Success/Failure Patterns
The trend chart shows workflow execution patterns over the last 4 days (Nov 3-6). The success rate has remained relatively stable in the 80-90% range, with November 5th showing the highest activity (27 runs total) and the best success rate. The failed runs are distributed across different days, indicating no systematic degradation in workflow reliability.
Token Usage & Costs
Resource consumption peaked on November 5th with 4.5M tokens ($1.94), driven by increased workflow activity. November 6th (today) shows reduced activity with 2.3M tokens ($1.09) as we're still early in the 24-hour collection window. The average daily cost is approximately $1.33, which translates to roughly $40/month if this pattern continues.
Detailed Audit Findings
🚨 Failed Workflow Runs
Breakdown by Workflow
Analysis: Most failures (10 out of 71 runs) appear to be isolated incidents rather than systemic issues. The Changeset Generator workflow failed twice, suggesting it may need attention. Several failures occurred in smoke test workflows, which are designed to test edge cases and may experience higher failure rates by design.
Top Workflows by Error Count
Common Error Patterns
1. JSON Parsing Errors (High Frequency)
Unexpected token 'E', "Error appl"... is not valid JSONcommon-generic-error2. Permission Denied Errors (Low Frequency)
copilot-permission-denied📊 Workflow Activity Analysis
Most Active Workflows (Last 24 Hours)
Based on successful runs:
Workflows with 100% Success Rate
Multiple workflows maintained perfect success rates including:
🔧 Tool Usage Statistics
No missing tools were reported during the audit period, indicating that all workflows had access to the tools they needed. Additionally, no MCP server failures were detected, showing good infrastructure stability.
💰 Cost Analysis
The cost is reasonable given the number of workflows and complexity of operations. The high token usage is primarily driven by:
🎯 Recommendations
High Priority
Investigate Changeset Generator Failures: This workflow failed twice in the last 24 hours. Review the logs for §19087350762 and §19117962937 to identify the root cause.
Review JSON Parsing Logic: The high frequency of JSON parsing errors suggests a systemic issue with how some workflows handle API responses or log data. Consider adding try-catch blocks and better error messages.
Medium Priority
Monitor Smoke Test Error Rates: While smoke tests are expected to encounter errors, the 163 errors in Smoke Claude warrant review to ensure they're legitimate test failures and not actual bugs.
Optimize Token Usage: Consider reviewing workflows with unusually high token consumption to identify optimization opportunities.
Low Priority
Document Error Patterns: Create a knowledge base of common error patterns and their resolutions for faster debugging.
Set Up Alerts: Consider implementing alerts for workflows that fail more than once in a 24-hour period.
📅 Historical Context
This is the first audit in the new automated audit system. Future audits will include trend analysis comparing against previous periods to identify:
✅ Positive Findings
🔄 Next Steps
Audit Metadata:
References:
Beta Was this translation helpful? Give feedback.
All reactions