🔍 Agentic Workflow Audit Report - November 11, 2025

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🔍 Agentic Workflow Audit Report - November 11, 2025

This report provides a comprehensive analysis of agentic workflow performance over the past 24 hours, with trend analysis spanning 30 days of historical data.

Executive Summary

Over the past 24 hours, the system processed 10 workflow runs with a 60% success rate. While the firewall performed flawlessly with 100% legitimate traffic, several critical issues require immediate attention: MCP timeout errors causing complete workflow failures, and MCP server spawn failures affecting reliability. The 30-day trend analysis reveals generally healthy patterns with an average 87% success rate on active days, though token consumption remains high at over 1 million tokens per run on average.

Key Highlights:

• ✅ Firewall: 100% allow rate - all 21 requests legitimate
• ✅ Missing Tools: Zero requests - excellent configuration
• ⚠️ Success Rate: 60% (24h) - below 80% target
• ⚠️ Critical Issues: 2 MCP server failures, 16 errors in one workflow
• 💰 Cost Control: $0.52 total (24h), but one run used 408K tokens

📈 Workflow Health Trends

Success/Failure Patterns

The trend chart reveals recent activity spanning November 6-11, with 101 total workflow runs. Success rates have been variable, with November 10 showing elevated failure rates (70.59% success) correlating with high volume (51 runs). The most recent day (Nov 11) shows recovery with 100% success, though based on limited sample size. The orange dashed line indicates the 80% success rate target - recent performance has been hovering near or below this threshold, indicating room for improvement.

Token Usage & Costs

Token consumption shows significant day-to-day variation, with peaks exceeding 12 million tokens on November 9 (costing ~$9). Daily costs range from $1-$9, with the 7-day moving average showing gradual decline toward more efficient usage. However, the average of 1M+ tokens per run remains unusually high and warrants investigation. The correlation between high token usage and workflow failures suggests optimization opportunities.

Full Audit Details - Last 24 Hours

Audit Period Statistics

Time Range: November 10-11, 2025 (24 hours)

Overall Performance Metrics

Metric	Value
Total Runs	10
Successful	6 (60%)
Failed	3 (30%)
In Progress	1 (10%)
Total Duration	40.9 minutes
Average Duration	4.1 minutes per run
Total Errors	49
Total Warnings	27
Avg Errors/Run	4.9
Avg Warnings/Run	2.7

Cost Analysis

Metric	Value
Total Token Usage	408,061 tokens
Total Cost	$0.52
Runs with Token Data	1 of 10 (10%)
Highest Single Run Cost	$0.52 (Smoke Claude #152)
Tokens in Highest Run	408,061 tokens

Note: Token tracking appears incomplete - only 1 of 10 runs reported token usage. This may indicate failed runs before AI execution or missing instrumentation.

Agent Distribution

Agent	Runs	Success	Failed	In Progress
Claude	3	2	0	1
Copilot	5	4	1	0
Codex	1	1	0	0
Unknown	1	0	1	0

Insight: Codex achieved perfect performance (0 errors), while the unknown agent configuration resulted in failure.

🚨 Critical Issues

Issue #1: MCP Timeout Errors - Weekly Workflow Analysis

Severity: 🔴 CRITICAL
Workflow: Weekly Workflow Analysis
Run ID: §19226397498
Status: FAILURE
Impact: Complete workflow failure with 16 errors

Error Pattern:

Error: MCP request exceeded timeout of 60000ms
Occurrences: 4

Root Cause: Long-running MCP queries to the gh-aw logs tool exceeded the 60-second timeout limit. The workflow attempted to fetch large datasets without proper pagination.

Affected Operations:

• Large log dataset retrieval
• jq filter parsing on oversized responses
• Response size limit exceeded (multiple occurrences)

Recommendation:

1. Immediate: Increase MCP timeout to 120 seconds for logs operations
2. Short-term: Implement automatic pagination for large datasets
3. Long-term: Add streaming support for large log queries

Issue #2: MCP Server Spawn Failures

Severity: 🔴 CRITICAL
Count: 2 failures across 2 workflows

Failure 2.1: agentic_workflows Server

Workflow: Daily Firewall Logs Collector and Reporter
Run ID: §19227830399
Error: spawn gh ENOENT

Root Cause: GitHub CLI (gh) not found in system PATH. The agentic_workflows MCP server depends on the gh CLI but couldn't locate it.

Recommendation:

• Verify gh CLI is installed in workflow environment
• Add explicit PATH configuration in workflow setup
• Add dependency validation before MCP server initialization

Failure 2.2: tavily Remote Server

Workflow: Daily News
Run ID: §19226280715
Error: TypeError: fetch failed

Root Cause: Network connectivity issue or remote tavily server unavailable.

Recommendation:

• Implement retry logic with exponential backoff
• Verify server URL and credentials configuration
• Add health check before workflow execution
• Consider fallback to alternative news sources

Issue #3: JSON Parsing Errors

Severity: 🟡 MEDIUM
Workflow: Dependabot Go Module Dependency Checker
Run ID: §19226427396
Occurrences: 9 errors
Status: Success (despite errors)

Error Patterns:

- "Content ty" (4 occurrences)
- "Contents o" (4 occurrences)
- Additional parsing error (1)

Root Cause: Tool responses not properly formatted as JSON. Truncated error messages suggest output corruption or incomplete response handling.

Recommendation:

• Add JSON validation with detailed error messages
• Implement fallback parsing strategies
• Log full error context (currently truncated)

Issue #4: MCP Response Size Limit Exceeded

Severity: 🟡 MEDIUM
Occurrences: 3
Affected Workflows: Smoke Claude, Weekly Workflow Analysis

Error Details:

MCP response size (79,373 tokens) exceeds limit (25,000 tokens)

Impact:

• Partial data retrieval
• Increased token usage (and costs)
• Workflow inefficiency

Recommendation:

• Implement pagination for all list operations
• Use filtering parameters to reduce response size
• Request only required fields instead of full objects

✅ Success Stories

Perfect Performance: Smoke Codex

Run ID: §19230980711
Agent: Codex
Duration: 4.2 minutes
Errors: 0
Warnings: 0
Status: ✅ Success

Insight: This run demonstrates optimal workflow performance and can serve as a benchmark for other workflows.

Clean Run: Smoke Copilot

Run ID: §19230999224
Agent: Copilot
Duration: 1.9 minutes
Errors: 0
Warnings: 2 (minor)
Status: ✅ Success

🛡️ Firewall Analysis

Security Status: EXCELLENT ✅

Metric	Value
Total Requests	21
Allowed	21 (100%)
Denied	0 (0%)
Unique Domains	3

Domain Breakdown

Domain	Requests	% of Total	Purpose
api.enterprise.githubcopilot.com:443	14	67%	Copilot AI API
api.github.com:443	4	19%	GitHub API
registry.npmjs.org:443	3	14%	NPM packages

Workflows Using Firewall

1. Daily Firewall Logs Collector and Reporter - 9 requests
2. Daily News - 7 requests
3. Smoke Copilot - 5 requests

Security Assessment: No suspicious activity detected. All traffic is legitimate and expected for normal workflow operations.

🔧 Missing Tools Report

Status: ✅ EXCELLENT - No missing tool requests detected

All workflows had access to required tools during the audit period. This indicates proper tool configuration and availability across the system.

📊 Tool Usage Statistics

Total Tool Calls: 134 across 10 unique tools

Tool	Calls	% of Total	Max Output	Max Duration
github	104	77.6%	N/A	N/A
agentic_workflows_logs	11	8.2%	N/A	N/A
safeoutputs	10	7.5%	N/A	N/A
TodoWrite	7	5.2%	N/A	N/A
github_list_pull_requests	4	3.0%	N/A	N/A
Read	2	1.5%	2,750	15.8s
Bash	2	1.5%	N/A	N/A
Write	2	1.5%	N/A	N/A
Edit	1	0.7%	N/A	N/A
Glob	1	0.7%	N/A	N/A

Insights:

• GitHub tools dominate usage (77.6%), indicating heavy API interaction
• Read tool is the slowest (15.8s max) and produces largest output (2,750 bytes)
• Good tool diversity with 10 different tools used

🎯 Problematic Workflows Detail

Workflow #1: Weekly Workflow Analysis

Priority: 🔴 CRITICAL

Attribute	Value
Run ID	§19226397498
Status	❌ FAILURE
Agent	Claude
Duration	11.0 minutes
Errors	16 (highest)
Warnings	10
Token Usage	Not reported

Issues:

• 4x MCP timeout errors
• Multiple jq filter parsing failures
• Response size limits exceeded
• Complete workflow failure

Action Required: Immediate attention needed to fix timeout and pagination issues.

Workflow #2: Smoke Claude

Priority: 🟡 MEDIUM

Attribute	Value
Run ID	§19230997564
Status	✅ SUCCESS (with issues)
Agent	Claude
Duration	2.8 minutes
Token Usage	408,061
Cost	$0.52
Errors	10
Warnings	6

Issues:

• Response size exceeded limit (79,373 vs 25,000 tokens)
• Repository access errors
• Pagination issues
• High token consumption

Action Required: Optimize to reduce token usage and implement proper pagination.

Workflow #3: Copilot PR Prompt Pattern Analysis

Priority: 🟡 MEDIUM

Attribute	Value
Run ID	§19226406194
Status	❌ FAILURE
Agent	Unknown (not specified)
Duration	28 seconds
Errors	1

Issue: No agent specified in workflow configuration, causing immediate failure.

Action Required: Fix agent configuration in workflow definition.

📈 30-Day Historical Context

Overall Trends (Oct 12 - Nov 11, 2025)

Metric	Value
Total Runs	101
Active Days	6 of 31 (19.4%)
Overall Success Rate	72.3%
Active Days Avg Success	87.1%
Total Tokens (30d)	42,473,809
Total Cost (30d)	$30.86
Daily Avg Cost	$5.14 (active days)
Avg Tokens/Run	984,163

Top Workflows (by run count)

1. Smoke Claude - 11 runs
2. Smoke Codex - 10 runs
3. Go Pattern Detector - 10 runs
4. Smoke Copilot - 10 runs
5. Tidy - 5 runs

Notable Observations

Activity Pattern: Workflow activity is concentrated in recent days (95% in last 6 days), suggesting either:

• Recent system deployment or activation
• Increased development activity
• Log retention only capturing recent data

Token Usage Concern: Average of 1M+ tokens per run is unusually high and warrants investigation. This could indicate:

• Large context windows being used unnecessarily
• Inefficient prompt engineering
• Missing pagination in data retrieval
• Multiple retry attempts inflating token counts

Success Rate Volatility: Daily success rates vary from 70% to 100%, with volume correlation (high volume days show lower success rates).

🎯 Recommendations

Immediate Actions (Next 24 Hours)

Priority	Action	Owner	Impact
🔴 Critical	Fix MCP timeout configuration - increase to 120s for logs operations	DevOps	Prevent workflow failures
🔴 Critical	Resolve gh CLI availability in agentic_workflows MCP server	DevOps	Restore firewall collector functionality
🔴 Critical	Fix tavily server connectivity with retry logic	DevOps	Restore news workflow
🟡 High	Implement pagination for all gh-aw logs queries	Engineering	Reduce token usage & timeouts

Short-term Improvements (This Week)

Priority	Action	Impact
🟡 High	Optimize Smoke Claude workflow to reduce 408K token usage	Cost reduction
🟡 High	Fix agent configuration for Copilot PR Prompt Pattern Analysis	Restore workflow
🟡 High	Add JSON validation with better error messages	Improve reliability
🟠 Medium	Implement retry logic for MCP server failures	Improve resilience
🟠 Medium	Add response size validation before processing	Prevent errors

Long-term Enhancements (This Month)

Priority	Action	Impact
🟠 Medium	Establish performance baselines and alerting	Proactive monitoring
🟠 Medium	Review token usage patterns across all workflows	Cost optimization
🟢 Low	Add streaming support for large log queries	Scalability
🟢 Low	Create workflow performance dashboard	Visibility

📊 Data Quality & Limitations

Strengths:

• Comprehensive 24-hour coverage with detailed metrics
• 30-day trend analysis with proper date handling
• Complete firewall audit with domain-level analysis
• Accurate error categorization and pattern detection

Limitations:

• Token usage data missing for 90% of 24h runs (likely due to failures)
• Historical data shows only 6 active days in 30-day window
• Limited sample size for some workflows
• Truncated error messages in some cases

📁 Audit Artifacts

All audit data has been saved to /tmp/gh-aw/audit-data/:

• summary.json - Overall statistics and metrics
• errors.json - Detailed error patterns
• missing_tools.json - Missing tool requests (empty)
• mcp_failures.json - MCP server failures
• runs.json - Complete run details
• firewall.json - Firewall analysis
• tool_usage.json - Tool usage statistics

Raw logs: /tmp/gh-aw/aw-mcp/logs

---

🔮 Next Audit

The next automated audit will run in 24 hours (November 12, 2025 00:00 UTC).

Focus areas for next audit:

• Monitor resolution of MCP timeout issues
• Track token usage improvements
• Verify gh CLI and tavily server fixes
• Assess success rate improvement

---

References:

• §19226397498 - Weekly Workflow Analysis (FAILURE)
• §19230997564 - Smoke Claude (HIGH COST)
• §19227830399 - Daily Firewall Collector (MCP FAILURE)

AI generated by Agentic Workflow Audit Agent

[github-actions[bot]]

Performance Engineering Session - 2025-11-11

Goal Selected

Attempted to optimize test suite parallelization (Priority 1) with focus on TestMCPAddIntegration_AddAllServers (1.31s, slowest test).

Findings

Current Performance Baselines (Measured):

• CLI startup time: ~47ms (./gh-aw --version)
• Build time: 0.125s (make build) ✅ Excellent
• Full workflow compilation: 2.1s for 74 workflows
• Slowest tests identified via make test-perf:
  1. TestMCPAddIntegration_AddAllServers: 1.31s
  2. TestMainFunctionExecutionPath: 1.24s
  3. TestCompileWithPoutineAndZizmor: 0.82s

Technical Challenges Encountered:

1. Test Infrastructure Complexity with t.Parallel():

   • Integration tests use shared setupIntegrationTest() with defer cleanup()
   • When subtests use t.Parallel(), they execute after parent test returns
   • This triggers cleanup before parallel subtests run, causing directory deletion
   • Attempted fixes with absolute paths still failed due to cleanup timing
   • Root cause: The defer setup.cleanup() pattern is incompatible with t.Parallel() subtests

2. TypeScript Type Definition Issue:

   • make agent-finish fails at build-js step
   • Error: Cannot find type definition file for 'node'
   • This is blocking agent-finish performance measurement
   • Not addressed in this session (separate issue)

Lessons Learned

For Test Parallelization:

• Tests using shared setup with deferred cleanup cannot easily use t.Parallel() without refactoring
• Options for future work:
  1. Refactor integration test setup to use t.Cleanup() instead of defer cleanup()
  2. Don't share setup between parallel subtests - each creates its own temp directory
  3. Target simpler unit tests for parallelization first

Better Optimization Candidates:

• CLI command profiling (already very fast at 47ms)
• Workflow compilation caching (would require file hash tracking)
• Makefile target parallelization (e.g., run fmt and lint concurrently in agent-finish)

Recommendation for Next Session

Focus on simpler, isolated optimizations rather than complex test infrastructure changes:

1. Low-hanging fruit: Measure and optimize make agent-finish execution order

   • Current: Sequential execution of 9 targets
   • Opportunity: Parallelize independent targets (fmt + lint, etc.)
   • Expected impact: 20-30% reduction in agent-finish time

2. Unit test parallelization: Target tests without shared setup

   • Start with fast unit tests that are CPU-bound
   • Less complex than integration test parallelization

3. Fix TypeScript setup before attempting agent-finish optimization

   • Resolve @types/node dependency issue
   • Ensure make build-js succeeds reliably

Performance Guide Updates Needed

The build performance guide should include:

• Note about t.Parallel() incompatibility with shared test setup using defer
• Example of refactoring to use t.Cleanup() for parallel-safe setup
• Measurement methodology for identifying parallelization candidates

Status: Research completed, no PR created this session due to technical blockers. Valuable findings documented for future optimization work.

Related Items

• Discussion: #3592

AI generated by Daily Perf Improver

To add this workflow in your repository, run gh aw add githubnext/agentics/workflows/daily-perf-improver.md@1f181b37d3fe5862ab590648f25a292e345b5de6. See usage guide.

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