[prompt-clustering] Copilot Agent Prompt Clustering Analysis - February 11, 2026 #14890
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🔬 Copilot Agent Prompt Clustering Analysis - February 11, 2026
Daily NLP-based clustering analysis of copilot agent task prompts using TF-IDF vectorization and K-means clustering.
Summary
Analysis Period: Last 30 days (1,218 tasks analyzed)
Clusters Identified: 7
Overall Success Rate: 66.0% (804/1218 PRs merged)
Data Source: Copilot-created PRs in
github/gh-awrepositoryCluster Overview
Visualizations
📊 Cluster Distribution

📈 Success Rates by Cluster

🗺️ Cluster Visualization (PCA)

📉 Elbow Analysis

View Full Analysis Report
General Insights
Detailed Cluster Analysis
Cluster 1: In The
Size: 443 tasks (36.4% of total)
Success Rate: 70.9% (314 merged)
Avg Code Changes: 18.7 files, +381/-283 lines
Top Keywords:
Key Phrases:
Characteristics:
Sample Tasks:
Cluster 2: On The
Size: 296 tasks (24.3% of total)
Success Rate: 58.4% (173 merged)
Avg Code Changes: 15.4 files, +267/-376 lines
Top Keywords:
Key Phrases:
Characteristics:
Sample Tasks:
@copilotto workflow sync issues when agent token availableCluster 3: Test + Pkg
Size: 169 tasks (13.9% of total)
Success Rate: 66.3% (112 merged)
Avg Code Changes: 8.2 files, +454/-267 lines
Top Keywords:
Key Phrases:
Characteristics:
Sample Tasks:
Cluster 4: Mcp Server
Size: 120 tasks (9.9% of total)
Success Rate: 61.7% (74 merged)
Avg Code Changes: 39.0 files, +503/-856 lines
Top Keywords:
Key Phrases:
Characteristics:
Sample Tasks:
Cluster 5: Reference: Debug
Size: 82 tasks (6.7% of total)
Success Rate: 65.9% (54 merged)
Avg Code Changes: 23.7 files, +1016/-95 lines
Top Keywords:
Key Phrases:
Characteristics:
Sample Tasks:
Cluster 6: On The
Size: 70 tasks (5.7% of total)
Success Rate: 67.1% (47 merged)
Avg Code Changes: 8.7 files, +383/-448 lines
Top Keywords:
Key Phrases:
Characteristics:
Sample Tasks:
Cluster 7: Job Id:
Size: 38 tasks (3.1% of total)
Success Rate: 78.9% (30 merged)
Avg Code Changes: 23.9 files, +2072/-139 lines
Top Keywords:
Key Phrases:
Characteristics:
Sample Tasks:
Key Findings
Most Common Task Type: In The represents 36.4% of all tasks (443 tasks). These are primarily agentic-related tasks with a success rate of 70.9%.
Highest Success Rate: Job Id: cluster has the highest success rate at 78.9%. These tasks typically involve job, fix, workflow and tend to be more straightforward fixes.
Most Challenging Tasks: On The cluster has the lowest success rate at 58.4%. These tasks often involve workflow, issue, gh which may require more complex changes or multiple iterations.
Code Change Patterns: On average, tasks modify 18.4 files. Tasks with smaller, focused changes tend to have higher merge rates.
Recommendations
Based on clustering analysis:
Optimize for Success Patterns: Tasks in the 'Job Id:' cluster have 78.9% success rate. Consider breaking down complex tasks into smaller, focused requests similar to this pattern.
Improve Challenging Task Types: 'On The' tasks have lower success rates (58.4%). Consider providing more context, examples, or breaking these into multiple steps.
Provide Clear Requirements: Tasks with specific, actionable prompts tend to have higher success rates. Include file paths, expected outcomes, and acceptance criteria.
Leverage Successful Patterns: Review merged PRs in high-performing clusters to identify effective prompt patterns and replicate them.
Monitor Task Complexity: Tasks requiring changes to 5+ files have varied success rates. Consider splitting large tasks into multiple smaller PRs for better outcomes.
View Recent Tasks Table (Top 100)
@actions/exec3.0.0,@typ...(Table truncated to first 10 entries for brevity - full data available in analysis files)
Analysis Date: 2026-02-11 05:07 UTC
Methodology: TF-IDF vectorization with K-means clustering (n_clusters=7)
Data Range: Last 30 days of copilot-created PRs
Repository: github/gh-aw
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