[prompt-clustering] 🔬 Copilot Agent Prompt Clustering Analysis - 2025-11-18 #4298
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🔬 Copilot Agent Prompt Clustering Analysis
Analysis Date: 2025-11-18
Analysis Period: Last 30 days
NLP-based clustering analysis of 1,020 copilot agent task prompts to identify patterns, trends, and optimization opportunities.
Summary
The analysis used TF-IDF vectorization and K-means clustering to group similar tasks together, revealing distinct patterns in how copilot agents are used.
Full Analysis Report
Cluster Analysis
Cluster 4: Documentation Updates
Example PRs:
Sample Prompt: Update the frontmatter imports documentation under docs with all the supported URL and path formats
Cluster 3: Bug Fixes
Example PRs:
Sample Prompt: Recompile workflows.
Cluster 6: Documentation Updates
Example PRs:
Sample Prompt: Review the scheduled agentic workflows and spread them the entire day. Schedule the smoke workflows every 6h
Cluster 7: CI/CD & Workflows
Example PRs:
Sample Prompt: x Rename logger variables to log in all 5 Go files x pkg cli trial_command.go x pkg workflow claude_engine.go
Cluster 2: Documentation Updates
Example PRs:
Sample Prompt: Update commit changes analyzer to use the edit tool and allow bash tools.
Cluster 1: Documentation Updates
Example PRs:
Sample Prompt: The copilot engine should review the add dir folders used in the args list and make sure those folders exist before running the cli. Emit mkdir p ... to prepare those directories.
Cluster 5: Documentation Updates
Example PRs:
Sample Prompt: Fix GenAIScript OPENAI_API_KEY Missing Issue Problem The GenAIScript smoke test workflow was failing at run 18722204018 with error OPENAI_API_KEY missing because the workflow uses the openai gpt 4.1 m...
Success Rate by Cluster
Sample Data Table
Showing 10 of 1020 total PRs (see full report for complete table)
Key Findings
Recommendations
Based on clustering analysis:
Best Practices: CI/CD & Workflows tasks perform well (84.7% success). Keywords: pkg, pkg workflow, workflow, functions, code. Consider using similar prompt patterns for other task types - specifically, prompts that are concrete and reference specific file paths tend to perform better.
Prompt Clarity: Analyze successful prompts in high-performing clusters to identify effective prompt patterns and apply them to other task types. Specific, actionable prompts with clear scope tend to have higher success rates.
Documentation Tasks: These represent the majority of work but have slightly lower success rates (73-77%). Consider breaking down complex documentation tasks into smaller, more focused subtasks.
Methodology: This analysis used TF-IDF vectorization and K-means clustering (k=7) on 1,020 copilot agent task prompts extracted from PR bodies over the last 30 days. Prompts were preprocessed to extract the original task description, cleaned of markup and URLs, and vectorized using unigram and bigram features.
Generated by Copilot Prompt Clustering Analysis
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