skill-creator

Create, evaluate, and refine AI agent skills with SKILL.md files.

1|Updated Sep 15, 2024
One-click install
npx skills add https://github.com/mysticfall/alleycat --skill skill-creator-mysticfall
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/mysticfall/alleycat/tree/main/.opencode/skills/skill-creator
Command: npx skills add https://github.com/mysticfall/alleycat --skill skill-creator-mysticfall

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Managing and scaling AI agent capabilities is hard. This Skill Unit provides a repeatable process to create, update, evaluate, and improve AI agent skills, turning ad-hoc experiments into a maintainable workflow.

Core Features & Use Cases

  • Capture Intent: Define the skill's goal, triggers, and success criteria.
  • Iterative Improvement: Run evaluation loops to refine prompts, metrics, and descriptions.
  • Documentation & Organization: Manage SKILL.md content, test prompts, and references.
  • Packaging & Distribution: Validate and package skills into .skill files for reuse.

Quick Start

Define the skill's goal, draft the SKILL.md, run trigger evaluation on realistic prompts, and iterate until you converge on a stable description.

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 test AI skills with a repeatable workflow?

To create and test AI skills, define the skill's goal and success criteria, draft the SKILL.md, run trigger evaluations on realistic prompts, and iterate until the description stabilizes. This coordinates utility scripts and references into a repeatable workflow.

What is the best way to manage prompt engineering iteration for AI agents?

The best way to manage prompt engineering iteration is running evaluation loops that refine prompts, metrics, and descriptions. This approach captures intent and turns ad-hoc prompt experiments into a maintainable, testable skill-creation workflow.

How do I package and distribute AI agent skills for reuse?

To package and distribute AI agent skills, validate your SKILL.md, test prompts, and references, then package them into .skill files. This process ensures your skills are organized and ready for reuse across different environments.

Can I use YAML to organize AI skill documentation and references?

Yes, you can use YAML to organize skill documentation. The workflow relies on PyYAML to manage SKILL.md content and references, ensuring your AI skill metadata and configurations are structured and valid.

Why does my AI skill trigger evaluation fail on realistic prompts?

Skill trigger evaluation fails when the description, metrics, and prompts are misaligned. You must run iterative improvement loops to refine the SKILL.md triggers and success criteria until the evaluation converges on a stable result.

Do I need utility scripts to automate AI skill creation and refinement?

Yes, utility scripts are required to automate AI skill creation and refinement. They coordinate the generation of SKILL.md, manage test prompts, and execute evaluation loops to produce repeatable, testable Skill Units.