[prompt-clustering] Copilot Agent Prompt Clustering Analysis - 2026-01-02

[github-actions[bot]]

Daily NLP-based clustering analysis of copilot agent task prompts to identify patterns and optimization opportunities.

Summary

Analysis Date: 2026-01-02
Total Tasks Analyzed: 630
Clusters Identified: 6
Overall Success Rate: 76.0%

Quick Insights

• Most Common Task Type: New Features (278 tasks, 44.1%)
• Highest Success Rate: Coding Tasks (84.2%)
• Average Files Changed: 14.8
• Average Commits Per Task: 3.8

Full Analysis Report

Detailed Cluster Analysis

Cluster 1: New Features

Size: 278 tasks (44.1% of total)

Success Rate: 74.1% (206/278 merged)

Average Metrics:

• Files changed: 19.5
• Commits: 4.2
• Lines added: 717.9

Top Keywords: add, command, remove, file, firewall

Example PRs: #2405, #2611, #2645

Representative Tasks:

1. "Disable threat detection in..."
2. "refuse usage of minute, seconds relative time with stop-after. The "minimum" unit is hour...."

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Cluster 2: New Features

Size: 96 tasks (15.2% of total)

Success Rate: 76.0% (73/96 merged)

Average Metrics:

• Files changed: 5.2
• Commits: 3.6
• Lines added: 2043.0

Top Keywords: agentic workflow, agentic, workflow, create, github agentic

Example PRs: #3306, #2183, #2155

Representative Tasks:

1. "Port grumpy coder to an agentic workflow. Source https://github.com/sinedied/grumpydev-mcp/blob/main/genaisrc/review-code.genai.js..."
2. "Create a "mergefest" agentic workflow...."

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Cluster 5: Documentation

Size: 91 tasks (14.4% of total)

Success Rate: 80.2% (73/91 merged)

Average Metrics:

• Files changed: 12.2
• Commits: 3.6
• Lines added: 383.3

Top Keywords: update, script, command, md, docs

Example PRs: #2120, #2166, #2213

Representative Tasks:

1. "Update commit changes analyzer:..."
2. "Update blog auditor to point to url (redacted)

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Cluster 3: Bug Fixes

Size: 69 tasks (11.0% of total)

Success Rate: 75.4% (52/69 merged)

Average Metrics:

• Files changed: 9.6
• Commits: 3.2
• Lines added: 274.9

Top Keywords: original, workflow, issue, original prompt, original issue

Example PRs: #3427, #2914, #3496

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Cluster 4: Bug Fixes

Size: 58 tasks (9.2% of total)

Success Rate: 74.1% (43/58 merged)

Average Metrics:

• Files changed: 15.9
• Commits: 3.9
• Lines added: 689.0

Top Keywords: fix, workflows, agentic workflows, agentic, add

Example PRs: #2789, #2797, #2334

Representative Tasks:

1. "Recompile and fix Agentic workflows permissions..."
2. "Fix permissions in agentic workflows, look at the recompile errors...."

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Cluster 6: Coding Tasks

Size: 38 tasks (6.0% of total)

Success Rate: 84.2% (32/38 merged)

Average Metrics:

• Files changed: 18.4
• Commits: 3.4
• Lines added: 592.9

Top Keywords: coding, coding agent, copilot, copilot coding, agent

Example PRs: #2242, #2423, #2494

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Success Rate by Cluster

Cluster	Theme	Tasks	Success Rate	Avg Commits	Top Keywords
1	New Features	278	74.1%	4.2	add, command, remove
2	New Features	96	76.0%	3.6	agentic workflow, agentic, workflow
5	Documentation	91	80.2%	3.6	update, script, command
3	Bug Fixes	69	75.4%	3.2	original, workflow, issue
4	Bug Fixes	58	74.1%	3.9	fix, workflows, agentic workflows
6	Coding Tasks	38	84.2%	3.4	coding, coding agent, copilot

Key Findings

1. Task Distribution: The majority of copilot tasks fall into three categories:

   • New Features: 278 tasks (44.1%)
   • New Features: 96 tasks (15.2%)
   • Documentation: 91 tasks (14.4%)

2. Success Patterns: Tasks in the following categories have above-average success rates:

   • Coding Tasks: 84.2% success rate
   • Documentation: 80.2% success rate
   • New Features: 76.0% success rate

3. Task Complexity: Average complexity varies by task type:

   • New Features: 4.2 commits, 19.5 files
   • Bug Fixes: 3.9 commits, 15.9 files

Recommendations

Based on the clustering analysis, here are actionable recommendations:

1. Optimize for High-Success Task Types: The 'Coding Tasks' category shows the highest success rate (84.2%). Consider:

   • Analyzing what makes these tasks successful
   • Applying similar patterns to other task types

2. Address Underperforming Categories: 'New Features' tasks have a lower success rate (74.1%). Consider:

   • Reviewing failed PRs in this category for common issues
   • Improving prompts or providing better context for these tasks

3. Task Scoping: Tasks requiring 4+ commits tend to be in 'New Features'. Consider:

   • Breaking down complex tasks into smaller, manageable pieces
   • Providing more specific guidance for multi-step tasks

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Methodology

This analysis uses NLP clustering (K-means with TF-IDF vectorization) to automatically group similar task prompts. The algorithm identified 6 distinct clusters from 630 copilot-created pull requests, analyzing task descriptions, success rates, and code change patterns to provide insights into copilot agent performance.

Data Source: Last 1000 copilot-created PRs in githubnext/gh-aw
Analysis Period: Historical PR data through 2026-01-02
Clustering Algorithm: K-means with TF-IDF vectorization (100 features, bigrams)
Validation: Silhouette analysis and manual review of cluster coherence

AI generated by Copilot Agent Prompt Clustering Analysis