skill-creator

Create and refine Agent Skills with SKILL.md and eval generation.

Updated Apr 12, 2026
One-click install
npx skills add https://github.com/Yukine5377/common --skill skill-creator-yukine5377
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/Yukine5377/common/tree/main/.cursor/skills/skill-creator
Command: npx skills add https://github.com/Yukine5377/common --skill skill-creator-yukine5377

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a structured, end-to-end process to design, implement, evaluate, and iteratively improve Agent Skills. It guides you from capturing user intent and drafting SKILL.md to crafting test prompts, running evaluations, visualizing results, and refining the description until activation reliability is high.

Core Features & Use Cases

  • Capture Intent: Infer and clarify user goals from conversation history to bootstrap a new skill.
  • SKILL.md Generation: Create a complete Skill entry with name, description, and operational guidelines.
  • Test Prompt Fabrication: Produce initial test prompts and an eval set to probe skill behavior.
  • Evaluation & Visualization: Run evals, collect metrics, and view results via eval-review tooling and benchmarks.
  • Iterative Refinement: Improve skill description and test coverage based on results; repeat until satisfactory.
  • Deployment Readiness: Prepare packaging metadata and references/scripts for on-demand use.

Quick Start

Provide your initial skill idea; this tool scaffolds SKILL.md, generates a basic eval set, and starts the iterative loop toward a refined skill.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I create and optimize an Agent Skill from scratch?

Agent Skill creation involves capturing user intent, drafting a SKILL.md file, generating test prompts, running evals, and iteratively refining descriptions to maximize activation reliability and overall usefulness.

What is the process for evaluating and benchmarking Agent Skills?

Evaluating Agent Skills involves running test prompt sets, collecting performance metrics, and visualizing benchmarking results to measure activation reliability and behavioral accuracy.

How do I improve Agent Skill activation reliability when it fails to trigger?

Improving activation reliability requires iteratively refining the skill description and test coverage based on evaluation results, repeating the benchmarking loop until the Agent consistently triggers the correct skill.

Does the skill-creator workflow require specific dependencies like anthropic and pyyaml?

Yes, the skill-creator workflow relies on the anthropic and pyyaml dependencies to scaffold SKILL.md files, package metadata, and execute scripts for automated testing and evaluation.

What is the best way to structure test prompts for Agent Skill development?

The best way to structure test prompts is to fabricate an initial eval set that probes specific skill behaviors, then expand test coverage based on benchmarking results and iterative refinement.