skill-creator

Create and iteratively improve AI agent skills through structured evaluation workflows.

19|3|Updated May 17, 2026
One-click install
npx skills add https://github.com/cline/skills --skill skill-creator-cline
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/cline/skills/tree/main/skills/skill-creator
Command: npx skills add https://github.com/cline/skills --skill skill-creator-cline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyYAML, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Building effective AI agent skills requires more than just writing instructions—it demands systematic testing, measurement, and iterative refinement to ensure reliable triggering and consistent performance across diverse user queries.

Core Features & Use Cases

  • Skill Creation & Editing: Draft new skills from user intent or improve existing ones with structured workflows.
  • Quantitative Evaluation: Run evals with subagent comparisons, grading, and variance analysis to measure skill impact.
  • Description Optimization: Automatically improve skill triggering accuracy using train/test splits and Claude-powered iteration loops.
  • Packaging & Distribution: Validate and package skills into distributable .skill files for installation across agents.

Quick Start

Use the skill-creator skill to build a new skill for extracting invoice data from PDFs by describing the workflow and test cases you want to validate.

Frequently Asked Questions about skill-creator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I benchmark AI agent skills to measure performance improvements?

AI agent skills are improved through structured evaluation workflows that apply quantitative benchmarking, blind comparison testing, and description optimization for trigger accuracy. This systematic approach measures reliable performance across diverse user queries.

What is the best way to optimize AI agent skill descriptions for trigger accuracy?

Optimize AI agent skill descriptions for trigger accuracy by using train/test splits with Claude-powered iteration loops. This automated description improvement loop refines how reliably skills activate for intended queries.

How do I package and distribute AI workflows as installable files?

Package and distribute AI workflows by validating and compressing them into distributable .skill files. This packaging process enables installation across multiple AI agents for standardized workflow deployment.

Do I need Python scripts to run iterative testing for AI agent evaluation?

Python scripts are required for AI agent evaluation to handle eval aggregation, HTML report generation, and Claude Code CLI integration. These scripts automate the iterative testing and description improvement loops.

Can I use PyYAML dependencies for AI workflow skill creation and editing?

PyYAML is required as a dependency for AI workflow skill creation and editing. It supports the structured workflows needed to draft new skills from user intent or improve existing ones.