[prompt-clustering] Daily Copilot Agent Prompt Clustering Analysis - January 26, 2026 #11833
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Daily NLP-based clustering analysis of copilot agent task prompts to identify patterns, insights, and optimization opportunities.
Analysis Date: 2026-01-26
Total Tasks Analyzed: 999
Clusters Identified: 9
Overall Success Rate: 77.5%
Summary Statistics
Task Type Distribution
The most common task types across all analyzed PRs:
Detailed Cluster Analysis
Cluster 1: Testing & Coverage (21.8%)
Example Tasks
Cluster 2: Feature Implementation (20.7%)
Example Tasks
Cluster 3: Configuration & Setup (15.6%)
Example Tasks
Cluster 4: Bug Fixes & Error Resolution (13.6%)
Example Tasks
Cluster 5: Security & Vulnerability Fixes (9.1%)
Example Tasks
Cluster 6: Documentation & Comments (8.7%)
Example Tasks
Cluster 7: Dependencies & Updates (5.8%)
Example Tasks
Cluster 8: Other (3.9%)
Example Tasks
Cluster 9: Refactoring & Code Quality (0.7%)
Success Rate Comparison
Key Findings
Actionable Recommendations
Based on clustering analysis of 999 PRs:
1. Prioritize High-Success Task Types
Dependencies & Updates (87.9%), Documentation (83.9%), and Configuration (82.1%) show excellent success rates. These task types have:
Action: Use successful examples from these clusters as templates for new prompts.
2. Improve Low-Success "Other" Cluster (38.5%)
Tasks in this cluster show:
Action: Provide more detailed prompts with:
3. Break Down Complex Testing Tasks
Testing & Coverage requires most iterations (4.2 commits, 1.9 comments):
Action: Break large testing tasks into smaller, incremental subtasks.
4. Maintain Current Documentation Standards
Documentation tasks show 83.9% success with minimal interaction (0.7 comments):
Action: Continue using documentation patterns as model for other task types.
References:
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