skill-creator

Automate creation, testing, and optimization of Claude Code skills.

94|7|Updated Feb 10, 2026
One-click install
npx skills add https://github.com/jin-bo/agentao --skill skill-creator-jin-bo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/jin-bo/agentao/tree/main/skills/skill-creator
Command: npx skills add https://github.com/jin-bo/agentao --skill skill-creator-jin-bo

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Creating effective AI agent skills requires more than just writing instructions — it demands systematic testing, quantitative evaluation, and iterative refinement to ensure reliable triggering and consistent performance. Without a structured workflow, skills often undertrigger, behave inconsistently, or fail to handle edge cases.

Core Features & Use Cases

  • Structured Skill Creation: Guides you through capturing intent, drafting SKILL.md files with proper progressive disclosure, and organizing bundled resources like scripts and references.
  • Quantitative Evaluation: Runs parallel test cases with baseline comparisons, grades assertions automatically, and aggregates benchmark statistics with variance analysis.
  • Description Optimization: Uses machine learning to iteratively improve skill descriptions for better trigger accuracy, with train/test splits to prevent overfitting.
  • Blind Comparison: Provides rigorous A/B testing of skill versions using independent agents to judge output quality without bias.

Quick Start

Use the skill-creator skill to design a new skill for your specific task, run evaluation prompts against it, and automatically refine its description until it triggers reliably.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I test and benchmark AI agent skills for Claude Code?

You can benchmark AI agent skills by running parallel test cases with baseline comparisons, automatically grading assertions, and aggregating benchmark statistics with variance analysis to ensure reliable triggering and consistent performance.

What is the best way to optimize skill descriptions so they trigger reliably?

Optimizing skill descriptions uses machine learning to iteratively improve trigger accuracy, applying train/test splits to prevent overfitting and refining the text until the agent consistently activates the skill.

How do I create structured agent skills with bundled scripts and references?

Structured skill creation guides you through capturing intent, drafting SKILL.md files using progressive disclosure, and organizing bundled resources like scripts and references into a reproducible package.

Can I run blind A/B comparisons on different versions of an AI skill?

Yes, blind comparison provides rigorous A/B testing of skill versions by using independent agents to judge output quality without bias, ensuring objective evaluation of description changes.

Do I need Python and pyyaml to use the skill creation workflow?

Yes, the skill creation and evaluation workflow requires Python with the anthropic and pyyaml dependencies installed to automate benchmarking, description optimization, and packaging tasks.

Why does my AI skill undertrigger or behave inconsistently during evaluation?

AI skills undertrigger or behave inconsistently without systematic testing, quantitative evaluation, and iterative refinement to handle edge cases and ensure reliable agent performance.