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Animism001
Animism001COMMUNITY
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skill-creator

Automates creation, evaluation, refinement, and packaging of AI skills via SKILL.md and .skill files.

Updated Apr 14, 2026
Search Tags:#automation#workflow#evaluation#engineering#skill#prompt-engineering
One-click install
npx skills add https://github.com/Animism001/skills --skill skill-creator-animism001
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/Animism001/skills/tree/main/skills/skill-creator
Command: npx skills add https://github.com/Animism001/skills --skill skill-creator-animism001

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

The Skill Creator enables teams to rapidly design, refine, and validate AI skills by orchestrating the end-to-end lifecycle: drafting, evaluating, and iterating based on structured feedback and quantitative metrics.

Core Features & Use Cases

  • Skill creation from zero: scaffold new skills with a consistent SKILL.md structure and starter bodies.
  • Skill optimization and testing: iterate on descriptions, run evals, and compare against baselines or prior iterations.
  • Eval-driven improvement: automatically collect results, generate actionable improvements, and push updates back into the skill.
  • Packaging and deployment readiness: validate and package skills into distributable .skill files for sharing.

Quick Start

Write a new SKILL.md with a simple capability, run an initial eval set, and let the tool suggest improvements in subsequent iterations.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I automate AI skill creation and evaluation at scale?▼

Automating AI skill creation involves scaffolding a new SKILL.md structure, running structured eval prompts, and iteratively refining the skill based on quantitative metrics to ensure reliable development.

What is the best way to optimize and test prompt-engineering workflows?▼

Optimizing prompt-engineering workflows requires running structured evals against baselines, collecting actionable feedback, and automatically pushing improvements back into the skill descriptions.

How do I package AI skills for deployment and distribution?▼

Packaging AI skills for deployment requires validating the SKILL.md body and optional components, then bundling them into distributable .skill files for sharing across teams.

Does skill evaluation require specific frontmatter or file formats?▼

Skill evaluation requires frontmatter-defined name and description in a standard SKILL.md file, alongside optional scripts, references, or assets to support pipeline steps for improvement.

Can I use this workflow to improve existing AI skills instead of starting from scratch?▼

You can use this workflow to iteratively improve existing AI skills by running new eval sets, comparing results against prior iterations, and applying automated refinement steps.

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