[portfolio] Portfolio Dashboard - February 2, 2026 #13233
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This discussion was automatically closed because it expired on 2026-02-09T08:44:29.109Z.
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Quick Overview
Analyzed 640 workflow runs across 86 workflows over 45 days (Dec 20, 2025 - Feb 2, 2026). Total portfolio cost: $46.36. Success rate: 78.9%. Identified $8.74/month in cost reduction opportunities (18.8% savings) through schedule optimization and failure remediation.
Visual Summary
Cost Trends (Last 30 Days)
Key Insights:
Top Cost Drivers
Top 3 workflows account for 56.9% of total cost:
Smoke Codex- $11.30/period (24 runs, 87.5% success)Smoke Claude- $10.56/period (24 runs, 87.5% success)Changeset Generator- $4.68/period (21 runs, 85.7% success)Failure Analysis
Wasted Spend: $0.02/period on failed runs (minimal)
Overall Health
💰 Cost Reduction Opportunities
Total Potential Savings: $8.74/month (18.8% reduction)
Strategy 1: Optimize High-Cost Testing Workflows - $7.20/month
Smoke Codex - $5.65/month savings
Current state:
Recommendation: Reduce to weekly schedule (4 runs/month)
.github/workflows/smoke-codex.mdRationale: Daily smoke tests for Codex engine provide diminishing returns. Weekly testing catches regressions while reducing cost by 75%.
Smoke Claude - $5.28/month savings
Current state:
Recommendation: Reduce to weekly schedule (4 runs/month)
.github/workflows/smoke-claude.mdRationale: Same as Smoke Codex - weekly cadence sufficient for stability monitoring.
Changeset Generator - Monitor for over-scheduling
Current state:
Recommendation: No immediate action - event-driven workflow
Strategy 2: Fix High-Failure Workflows - $0.68/month
Test Dispatcher Workflow - 34.7% failure rate
Current state:
Issue: High failure rate indicates flaky test or configuration issue
Recommendation: Investigate and fix root cause
.github/workflows/test-dispatcher.mdSecurity Guard Agent 🛡️ - 35.6% failure rate
Current state:
Issue: Security scanning agent has concerning failure rate
Recommendation: Debug and stabilize
.github/workflows/security-guard-agent.mdCI Failure Doctor - 9.1% failure rate
Current state:
Recommendation: Monitor - no immediate action needed
Strategy 3: Review Test YAML Import Frequency - $1.50/month
Test YAML Import - 109 runs (highest frequency)
Current state:
Analysis: While cost is moderate ($3/month), the extremely high run count (73/month) suggests this workflow may be:
Recommendation: Review trigger conditions
.github/workflows/test-yaml-import.mdpush/pull_requestBefore optimization:
After optimization:
Strategy 4: Optimize Daily Scheduled Workflows - $0.36/month
Daily Report Workflows - Consider Consolidation
Several "Daily" workflows run on schedule with similar patterns:
Analysis: Only 2 runs each over 45 days suggests:
Recommendation:
No immediate action - insufficient data (only 2 runs each)
🎯 Priority Actions
HIGH PRIORITY - Reduce Smoke Codex and Smoke Claude to weekly schedule → Save $10.93/month (23.6% cost reduction)
.github/workflows/smoke-codex.md,.github/workflows/smoke-claude.md0 0 * * *to0 0 * * 0MEDIUM PRIORITY - Fix high-failure workflows (Test Dispatcher, Security Guard) → Save $0.68/month + improved reliability
.github/workflows/test-dispatcher.md,.github/workflows/security-guard-agent.mdLOW PRIORITY - Optimize Test YAML Import triggers → Save $1.50/month
.github/workflows/test-yaml-import.md📈 Data Quality
Data Availability Notes
✅ Strong dataset: 640 runs over 45 days provides reliable patterns
⚠️ Uneven distribution: 87% of cost in last 3 days suggests batch testing or recent activity surge
✅ **Cost (redacted) Real token usage and calculated costs available for all runs
✅ Temporal coverage: Multiple weeks of data captures recurring patterns
Unused Workflows
123 workflows (59%) have not run in the analysis period:
Recommendation: Review unused workflows in next analysis cycle (after 90 days of data)
📊 Portfolio Health Score
Key Strengths
Areas for Improvement
Methodology: Analysis based on actual workflow execution data from 640 runs spanning 45 days. Costs calculated from real token usage (694M tokens, $46.36 total cost). Savings projections based on documented run frequencies and per-run costs.
Next Steps:
References:
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