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On 2026-03-31, Copilot-powered agentic workflows consumed 80,923,350 tokens across 111 workflow runs covering 66 unique workflows, totalling 1,627 agent turns and 890 action minutes (~14.8 hours of compute). This represents a -51.4% decrease in token consumption and -43.1% fewer runs compared to the previous snapshot (2026-02-20).
Key Highlights
Metric
Value
🔢 Total Tokens
80,923,350
🔄 Total Runs
111 (66 unique workflows)
💬 Total Turns
1,627
⏱️ Total Action Minutes
890 min (14.8 hrs)
📊 Avg Tokens / Run
729,039
💡 Avg Turns / Run
14.7
🏆 Highest token consumer: Copilot CLI Deep Research Agent (5,168,054 tokens, 68 turns — single run)
🔄 Most active workflow: Issue Monster (15 runs, 4,843,129 total tokens)
⚠️Most turns in a run: Daily Syntax Error Quality Check (90 turns, 4,495,202 tokens)
📉 Trend: Token usage is significantly down (-51.4%) vs. prior period — fewer runs this cycle
🏆 Top Workflows by Token Consumption
Top 10 Most Expensive Workflows
Rank
Workflow
Total Tokens
% of Total
Runs
Avg Tokens/Run
Avg Turns/Run
1
Copilot CLI Deep Research Agent
5,168,054
6.4%
1
5,168,054
68.0
2
Issue Monster
4,843,129
6.0%
15
322,875
8.7
3
Contribution Check
4,779,736
5.9%
6
796,622
24.8
4
Daily Syntax Error Quality Check
4,495,202
5.6%
1
4,495,202
90.0
5
Code Simplifier
4,202,294
5.2%
1
4,202,294
66.0
6
Daily Community Attribution Updater
3,452,781
4.3%
1
3,452,781
37.0
7
Dead Code Removal Agent
3,098,087
3.8%
1
3,098,087
46.0
8
Smoke Multi PR
2,831,029
3.5%
1
2,831,029
65.0
9
Auto-Triage Issues
2,818,847
3.5%
7
402,692
11.1
10
Slide Deck Maintainer
2,425,181
3.0%
1
2,425,181
42.0
The top 10 workflows account for ~44.1% of total token consumption (35,714,360 tokens).
📊 Token Efficiency Analysis
The scatter plot above maps total tokens vs. total turns for all workflows (bubble size = number of runs). Workflows in the upper-right are high-cost and turn-heavy; those in the lower-left are lean and efficient.
Outliers to watch:
Daily Syntax Error Quality Check: 90 turns in a single run — extremely high agentic exploration; could benefit from deterministic pre-steps
Copilot CLI Deep Research Agent: 68 turns, 5.2M tokens — expected for deep research tasks
Observation: 90 agent turns in a single run is extremely high — this workflow is iterating heavily, likely doing exhaustive file-by-file scanning agentically
Recommendation: Move file discovery/listing to deterministic pre-steps; batch file analysis; consider a lighter model (e.g., claude-haiku-4-5) for syntax-only checks
Copilot CLI Deep Research Agent — 68 turns, 5.2M tokens
Observation: Deep research workflows are inherently token-heavy, but 68 turns suggests broad tool exploration
Recommendation: Scope research questions more tightly; set explicit turn limits via max_turns
Data Source: Pre-downloaded workflow run logs from gh-aw audit covering last 30 days
Engine Filter: Copilot engine workflows
Token field: token_usage per run (not available for all runs)
Cost data: Not available in this dataset (cost reported as 0 in summary)
Analysis Date: 2026-03-31T11:36Z
Historical Data: 7 snapshots from Jan–Mar 2026
Data Quality Notes
14 workflows reported zero token usage — may be non-Copilot execution steps, failed runs before token logging, or infrastructure/smoke workflows
Cost figures are not available in the current log format (cost = 0); token counts are the primary efficiency metric
The current run (Daily Copilot Token Consumption Report, run §23794580649) was in_progress at time of data collection and is excluded from token counts
🎯 Action Items
Investigate Daily Syntax Error Quality Check — 90 turns is a red flag; move file enumeration to deterministic pre-steps
Scope Code Simplifier per run — run per-package rather than whole-repo; cap at 30 turns
Review Contribution Check — 6 runs × ~797K tokens is the largest multi-run cost; cache results or reduce frequency
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Executive Summary
On 2026-03-31, Copilot-powered agentic workflows consumed 80,923,350 tokens across 111 workflow runs covering 66 unique workflows, totalling 1,627 agent turns and 890 action minutes (~14.8 hours of compute). This represents a -51.4% decrease in token consumption and -43.1% fewer runs compared to the previous snapshot (2026-02-20).
Key Highlights
🏆 Top Workflows by Token Consumption
Top 10 Most Expensive Workflows
The top 10 workflows account for ~44.1% of total token consumption (35,714,360 tokens).
📊 Token Efficiency Analysis
The scatter plot above maps total tokens vs. total turns for all workflows (bubble size = number of runs). Workflows in the upper-right are high-cost and turn-heavy; those in the lower-left are lean and efficient.
Outliers to watch:
🌐 Token Distribution by Task Domain
General Automation dominates at 32.3% of all tokens — a broad category worth decomposing to identify optimization targets.
📈 Historical Trends
Historical Snapshot Comparison
Observations:
💡 Insights & Recommendations
High-Turn Workflows Driving Costs
Daily Syntax Error Quality Check — 90 turns, 4.5M tokens
claude-haiku-4-5) for syntax-only checksCopilot CLI Deep Research Agent — 68 turns, 5.2M tokens
max_turnsCode Simplifier — 66 turns, 4.2M tokens (single run)
agentic_fractionimprovements to move data-gathering to pre-stepsContribution Check — 24.8 avg turns over 6 runs (4.8M total)
Model Downgrade Opportunities
Several workflows were flagged with model_downgrade_available assessments in the raw data. Consider lighter models for:
gpt-4.1-miniorclaude-haiku-4-5gpt-4.1-miniEstimated potential savings: 15–30% of total tokens if model downgrades are applied to eligible workflows.
Workflows with No Token Data (14 workflows)
The following workflows ran but reported zero tokens (likely non-Copilot steps or completed before token logging):
Recommendation: Investigate
Smoke Copilot(56 action minutes, 0 tokens) — this may indicate a non-Copilot smoke test runner or a token reporting gap.Per-Workflow Detailed Statistics (All 66 Workflows)
Methodology & Data Notes
Methodology
gh-aw auditcovering last 30 daystoken_usageper run (not available for all runs)Data Quality Notes
in_progressat time of data collection and is excluded from token counts🎯 Action Items
Daily Syntax Error Quality Check— 90 turns is a red flag; move file enumeration to deterministic pre-stepsCode Simplifierper run — run per-package rather than whole-repo; cap at 30 turnsContribution Check— 6 runs × ~797K tokens is the largest multi-run cost; cache results or reduce frequencySmoke Copilot— 7 runs, 56 action minutes, 0 tokens logged is anomalousReferences:
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