code-extraction
OfficialOptimize AI prompts by extracting reusable knowledge.
Software Engineering#refactoring#prompt optimization#AI skills#agent prompts#semantic density#knowledge extraction#operational knowledge
Authorelevanaltd
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Large, verbose AI agent prompts can lead to token bloat, reduced efficiency, and difficulty in maintenance. This Skill analyzes agent prompts and codebases to identify reusable blocks of operational knowledge suitable for extraction into separate, optimized Skills.
Core Features & Use Cases
- Operational Knowledge Identification: Pinpoints multi-step workflows, command sequences, framework-specific patterns, and reference materials.
- Prompt Analysis: Scans agent prompts for large knowledge blocks that can be refactored into standalone Skills.
- Skills Creation Opportunities: Generates structured recommendations for new Skills, including proposed names, descriptions, and impact analysis.
- Use Case: If your AI agent prompts are becoming too long or contain repetitive operational procedures, use this Skill to identify and extract that knowledge into reusable Skills, making your agents more efficient and maintainable.
Quick Start
Analyze the supabase-expert agent prompt for potential operational knowledge extraction opportunities.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: code-extraction Download link: https://github.com/elevanaltd/eav-monorepo/archive/main.zip#code-extraction Please download this .zip file, extract it, and install it in the .claude/skills/ directory.