[daily regulatory] Regulatory Report - 2026-01-23

[github-actions[bot]]

Over the last 24 hours, 53 daily report discussions were generated across the gh-aw repository. Analysis of 6 key report types reveals a mixed data quality assessment with 2 critical issues requiring immediate attention.

Key Findings:

• Critical Issue: Observability Coverage Report shows complete log collection failure (0 runs analyzed)
• Data Quality: Firewall report using simulated data instead of production logs
• High Costs: Token consumption at $343.39 over 30 days, with top 3 workflows accounting for 40% of costs
• Positive: All other reports show healthy metrics with appropriate scope documentation

The most pressing concern is the observability pipeline failure, which prevents validation of firewall and MCP gateway coverage. This requires immediate investigation of the log collection system.

📋 Full Regulatory Report

📊 Reports Reviewed

Report	Title	Created	Status
Observability	[observability] Observability Coverage Report - 2026-01-23	2026-01-23T16:31:53Z	❌ Failed
Daily Issues	[daily issues] Daily Issues Report - 2026-01-23	2026-01-23T16:24:15Z	✅ Valid
Issue Arborist	[Issue Arborist] Issue Arborist Daily Report	2026-01-23T14:47:43Z	✅ Valid
Firewall	Daily Firewall Report - January 23, 2026	2026-01-23T12:48:51Z	⚠️ Simulated Data
Token	📊 Daily Copilot Token Consumption Report - January 23, 2026	2026-01-23T11:20:38Z	✅ Valid
Performance	[daily performance] Daily Performance Summary - 2026-01-23	2026-01-23T05:12:03Z	✅ Valid

🔍 Data Consistency Analysis

Cross-Report Metrics Comparison

Reference specs/metrics-glossary.md for metric definitions and scopes.

Metric	Daily Issues	Issue Arborist	Performance	Scope Match	Status
issues_analyzed	1,000	69	-	⚠️ Different Scopes	ℹ️ See Note 1
open_issues	70	-	0 (sample)	✅ Same	⚠️ See Note 2
closed_issues	930	-	0 (sample)	✅ Same	⚠️ See Note 2
total_prs	-	-	63	N/A	✅ Valid
merged_prs	-	-	52	N/A	✅ Valid
workflow_runs_analyzed	-	-	-	✅ Same	❌ Critical

Scope Notes:

1. issues_analyzed: Daily Issues Report (1,000 total issues) vs Issue Arborist (69 open issues without parent) - Different scopes by design per specs/metrics-glossary.md. This is expected and NOT a discrepancy.

2. Performance Report Sample Size: Performance report is based on sampled data (63 PRs, 50 issues) rather than complete dataset. The report explicitly states "sample is smaller than the full 90-day window".

3. workflow_runs_analyzed: Firewall Report (7d window) = 12 runs, Observability Report (7d window) = 0 runs - This is a critical discrepancy indicating log collection failure.

Consistency Score

• Overall Consistency: 83% (5 of 6 reports operational)
• Critical Discrepancies: 2 (Observability failure, simulated firewall data)
• Minor Discrepancies: 0 (Performance report sample size acknowledged)

⚠️ Issues and Anomalies

Critical Issues

1. Observability Report Failed - Zero Runs Analyzed

• Affected Reports: Observability Coverage Report
• Metric: runs_analyzed (per specs/metrics-glossary.md#workflows_analyzed)
• Description: The observability report shows 0 runs analyzed over a 7-day period, indicating a complete data collection failure. The report explicitly states: "Unable to compute observability coverage for the last 7 days because the log download step failed for all workflows in this run."
• Expected: > 0 workflow runs analyzed (Firewall report analyzed 12 runs in same period)
• Actual: 0 runs
• Scope Analysis: Both Firewall and Observability reports cover identical 7-day windows per glossary. The discrepancy (12 vs 0) indicates a pipeline failure, not a scope mismatch.
• Severity: Critical 🔴
• Recommended Action:
  1. Investigate agentic_workflows/logs tool failure immediately
  2. Check GitHub Actions logs for run §21293282518
  3. Verify log storage and retrieval permissions
  4. Re-run observability report once logs are accessible
  5. Add monitoring for log download failures to prevent silent gaps

2. Inconsistent Workflow Run Analysis Across Reports

• Affected Reports: Daily Firewall Report, Observability Coverage Report
• Metric: workflow_runs_analyzed (per specs/metrics-glossary.md#workflows_analyzed)
• Description: Firewall report successfully analyzed 12 workflow runs while Observability report failed to analyze any runs, despite both covering the same 7-day period.
• Expected: Both reports should analyze similar runs (12 ± 10% tolerance)
• Actual: Firewall: 12 runs, Observability: 0 runs (100% discrepancy)
• Scope Analysis: Per specs/metrics-glossary.md, both reports use identical scope (last 7 days). This is a true discrepancy, not a scope mismatch.
• Severity: Critical 🔴
• Recommended Action: Root cause is the observability log collection failure. Once agentic_workflows/logs is restored, both reports should show matching run counts within tolerance.

Warnings

1. Firewall Report Uses Simulated Data

• Details: The Daily Firewall Report (Daily Firewall Report - January 23, 2026 #11507) explicitly states: "This report is generated from simulated data to demonstrate the firewall reporting capability. In production, this would analyze actual firewall logs from workflow runs."
• Impact:
  • Blocked domain counts (15 unique domains, 505 requests) may not reflect actual production activity
  • Block rate of 22.1% is synthetic and should not be used for trend analysis
  • Cannot validate actual firewall effectiveness or identify genuine security issues
• Severity: Medium ⚠️
• Recommendation: Transition to production firewall logs. The simulated data includes realistic patterns (tracking pixels, social media APIs, analytics domains) but lacks real threat intelligence.

2. High Token Consumption Detected

• Details: Copilot Token Consumption Report (📊 Daily Copilot Token Consumption Report - January 23, 2026 #11486) shows:
  • Total tokens: 114,462,428 (over 30 days)
  • Total cost: $343.39
  • Average cost per run: $1.63
  • Top 3 workflows account for 40.2% of total costs:
    • CI Cleaner: $63.16 (21.1M tokens, 3 runs)
    • Agent Persona Explorer: $55.07 (18.4M tokens, 2 runs)
    • Code Scanning Fixer: $23.45 (7.8M tokens, 40 runs)
• Impact: High operational costs with concentration risk. CI Cleaner consuming 7M tokens per run suggests potential optimization opportunities.
• Severity: Medium ⚠️
• Recommendation:
  1. Review CI Cleaner workflow for caching opportunities (could save ~$31.58/month per report)
  2. Consider incremental analysis vs. full repository scans
  3. Monitor token consumption trends weekly to catch cost spikes early

Data Quality Notes

• Performance Report Sampling: The Daily Performance Summary explicitly notes it's based on sampled data (63 PRs, 50 issues, 50 discussions) rather than the full 90-day dataset. Trend interpretations should be treated as directional, not exhaustive.
• Observability Log Collection: Complete pipeline failure prevents any validation of firewall access.log and MCP gateway.jsonl coverage.
• Firewall Metrics: While report shows healthy structure, simulated data limits actionable insights until production logs are used.

📈 Trend Analysis

Week-over-Week Comparison

Metric	This Week	Last Week	Change	Source
Daily Issues Analyzed	1,000	N/A (new baseline)	-	Daily Issues Report
Open Issues	70	N/A	-	Daily Issues Report
Closed Issues	930	N/A	-	Daily Issues Report
Token Consumption (30d)	114.5M	N/A (30d window)	-	Token Report
Total Cost (30d)	$343.39	N/A (30d window)	-	Token Report
Workflow Runs (7d)	12 (Firewall)	N/A	-	Firewall Report
Observability Coverage	0% ❌	Unknown	Critical Failure	Observability Report

Note: Week-over-week comparison is limited because this is the first regulatory report with standardized metrics tracking. Future reports will provide trend analysis.

Notable Trends

• Issue Velocity: Daily Issues Report shows 93% closure rate with average time-to-close under 1 day (~19h 32m). This indicates high throughput automation.
• Labeling Backlog: 81 issues remain unlabeled (8.1% of analyzed issues), presenting opportunity for improved categorization.
• Token Cost Concentration: Top 3 workflows consume 40% of costs, suggesting optimization focus should target CI Cleaner and Agent Persona Explorer first.
• Observability Gap: First reported instance of complete log collection failure. Requires immediate monitoring to prevent recurring issues.

📝 Per-Report Analysis

Observability Coverage Report

Source: Discussion #11534
Time Period: Last 7 days
Quality: ❌ Failed

Extracted Metrics:

Metric	Value	Validation
runs_analyzed	0	❌ Critical - Complete failure
firewall_coverage	N/A	❌ Cannot compute
mcp_coverage	N/A	❌ Cannot compute

Notes:

• Report explicitly states "log download step failed for all workflows in this run"
• Blocks validation of firewall (access.log) and MCP gateway (gateway.jsonl) coverage
• References workflow run §21293282518
• Action Required: Restore agentic_workflows/logs functionality before next run

Daily Issues Report

Source: Discussion #11533
Time Period: Last 1,000 issues
Quality: ✅ Valid

Extracted Metrics:

Metric	Value	Validation
issues_analyzed	1,000	✅ Valid (per scope definition)
open_issues	70 (7.0%)	✅ Healthy
closed_issues	930 (93.0%)	✅ Excellent closure rate
issues_opened_7d	381	✅ High activity
stale_issues	0	✅ No stale issues
issues_without_labels	81	⚠️ 8.1% unlabeled

Notes:

• High-throughput pipeline with 93% closure rate
• Average time-to-close: ~19h 32m (under 1 day)
• Automation dominates dataset (985/1000 issues)
• Opportunity: 81 unlabeled issues need categorization

Issue Arborist Report

Source: Discussion #11515
Time Period: Daily (open issues without parent)
Quality: ✅ Valid

Extracted Metrics:

Metric	Value	Validation
issues_analyzed	69	✅ Valid (different scope than Daily Issues)
links_created	42	✅ Active linking
parent_issues_created	0	✅ No new clusters

Notes:

• Successfully linked 42 sub-issues to parent issues
• Primary focus on Workflow Normalizer output (issue [workflow-style] Workflow Normalizer - Issue Group #11271)
• Scope intentionally different from Daily Issues Report (see glossary)

Daily Firewall Report

Source: Discussion #11507
Time Period: Last 7 days (simulated data)
Quality: ⚠️ Simulated Data

Extracted Metrics:

Metric	Value	Validation
runs_analyzed	12	⚠️ Simulated
workflows_analyzed	4	⚠️ Simulated
requests_blocked	505 (22.1%)	⚠️ Simulated
requests_allowed	1,776 (77.9%)	⚠️ Simulated
unique_blocked_domains	15	⚠️ Simulated
block_rate	22.1%	⚠️ Simulated

Notes:

• Report explicitly uses "simulated data to demonstrate capability"
• Realistic patterns (tracking pixels, analytics, social media APIs)
• Cannot validate actual firewall effectiveness until production logs used
• Structure and reporting format are solid - ready for production data

Daily Copilot Token Consumption Report

Source: Discussion #11486
Time Period: Last 30 days
Quality: ✅ Valid

Extracted Metrics:

Metric	Value	Validation
total_tokens	114,462,428	✅ Valid
total_cost	$343.39	✅ Valid
workflow_runs	211	✅ Valid
unique_workflows	52	✅ Valid
avg_cost_per_run	$1.63	✅ Calculated

Notes:

• Top 3 workflows account for 40.2% of total costs
• CI Cleaner highest per-run cost ($21.05, 7M tokens)
• Code Scanning Fixer most active (40 runs, $23.45 total)
• Report includes detailed optimization recommendations

Daily Performance Summary

Source: Discussion #11437
Time Period: Recent sample (not full 90-day window)
Quality: ✅ Valid (with sampling note)

Extracted Metrics:

Metric	Value	Validation
total_prs	63	✅ Valid (sample)
merged_prs	52 (82.5%)	✅ Healthy merge rate
open_prs	4 (6.3%)	✅ Low backlog
avg_merge_time	< 1 hour	✅ Fast cycle

Notes:

• Based on sampled data, not exhaustive
• Report acknowledges limitations: "sample is smaller than the full 90-day window"
• Trends are directional rather than comprehensive
• PR activity leads overall volume

💡 Recommendations

Process Improvements

1. Restore Observability Log Collection Pipeline (Critical)

   • Priority: Immediate
   • Action: Investigate and fix agentic_workflows/logs tool failure
   • Rationale: Without log collection, firewall and MCP gateway coverage cannot be validated, creating a blind spot in security monitoring
   • Owner: Infrastructure team
   • Timeline: Within 24 hours

2. Transition Firewall Report to Production Data (High)

   • Priority: High
   • Action: Replace simulated data with actual Squid access.log parsing
   • Rationale: Current simulated data provides no actionable security insights or threat detection
   • Owner: Security/Observability team
   • Timeline: Within 1 week

3. Optimize High-Cost Workflows (Medium)

   • Priority: Medium
   • Action: Review CI Cleaner and Agent Persona Explorer for caching/incremental analysis opportunities
   • Rationale: CI Cleaner consuming 7M tokens per run ($21.05) offers significant cost savings potential (~$31.58/month if optimized to 50% efficiency)
   • Owner: Workflow optimization team
   • Timeline: Within 2 weeks

Data Quality Actions

1. Add Log Collection Monitoring (Critical)

   • Action: Implement alerting for agentic_workflows/logs failures
   • Rationale: Prevent silent observability gaps by detecting log collection failures early
   • Implementation: Add health check to daily observability workflow

2. Standardize Scope Documentation (Medium)

   • Action: Ensure all daily reports reference specs/metrics-glossary.md and document metric scopes in output
   • Rationale: Reduces regulatory report complexity and prevents false-positive discrepancy flags
   • Implementation: Update report templates to include glossary links

3. Expand Performance Report Sampling (Low)

   • Action: Consider increasing sample size or documenting exact sampling methodology
   • Rationale: Current "smaller than full 90-day window" note is vague; clearer methodology improves confidence in trends
   • Implementation: Update performance report to specify sample size and selection criteria

Workflow Suggestions

1. Enable Trend Tracking for Regulatory Reports (Medium)

   • Action: Store key metrics in time-series database for week-over-week comparison
   • Rationale: First regulatory report establishes baseline; future reports can track trends and identify degradation patterns
   • Implementation: Create metrics storage workflow that runs after all daily reports complete

2. Cross-Report Consistency Validation (Low)

   • Action: Automate cross-checks for metrics with identical scopes (e.g., open_issues, workflow_runs_analyzed)
   • Rationale: Reduces manual regulatory analysis effort and catches discrepancies faster
   • Implementation: Add validation step to regulatory workflow with 10% tolerance thresholds

📊 Regulatory Metrics

Metric	Value
Reports Reviewed	53 (6 key reports analyzed in detail)
Reports Passed	4 (Daily Issues, Issue Arborist, Token, Performance)
Reports with Issues	2 (Observability: Failed, Firewall: Simulated Data)
Reports Failed	1 (Observability Coverage)
Overall Health Score	67% (4/6 key reports operational)
Critical Issues	2
Warnings	2
Notes	2

---

Report generated automatically by the Daily Regulatory workflow
Data sources: Daily report discussions from githubnext/gh-aw
Metric definitions: specs/metrics-glossary.md
Analysis period: 2026-01-22 to 2026-01-23 (24-48 hour window)

References:

• §21293282518 - Observability Report Run (Failed)
• §21297768790 - Current Regulatory Report Run

AI generated by Daily Regulatory Report Generator

• expires on Jan 26, 2026, 7:11 PM UTC

[github-actions[bot]]

This regulatory report has been superseded by the 2026-01-24 Regulatory Report, which includes analysis of 25 daily reports from January 24, 2026.

Key Updates in New Report:

• ✅ 25 reports analyzed across 7 categories
• 🔴 Critical finding: Observability report failure due to log download issues
• ⚠️ Open issues discrepancy identified (29% variance between reports)
• 📊 92% overall health score with detailed cross-report validation

The new report includes enhanced metrics extraction, comprehensive cross-checking using specs/metrics-glossary.md, and actionable recommendations for process improvements.

[github-actions[bot]]

This regulatory report has been superseded by the newer [daily regulatory] Regulatory Report - 2026-01-25. The latest report includes updated metrics from January 24-25, 2026 and provides current cross-report analysis and consistency checks.