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milo0914
milo0914COMMUNITY
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skill-creator

Create, test, and optimize custom AI skills with automated benchmarking.

Updated Aug 27, 2026
Search Tags:#automation#testing#benchmarking#skill-development#ai-agent#prompt-engineering
One-click install
npx skills add https://github.com/milo0914/hermes-skills-backup --skill skill-creator-milo0914
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/milo0914/hermes-skills-backup/tree/main/skill-creator
Command: npx skills add https://github.com/milo0914/hermes-skills-backup --skill skill-creator-milo0914

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill streamlines the entire lifecycle of AI skill development, from initial drafting and iterative testing to performance benchmarking and triggering optimization.

Core Features & Use Cases

  • Iterative Development: Provides a structured loop for drafting, testing, and refining skill instructions based on user feedback.
  • Quantitative Benchmarking: Automates the execution of test cases and generates comparative metrics to ensure skill reliability.
  • Trigger Optimization: Uses a dedicated loop to refine skill descriptions, ensuring the AI invokes the skill accurately when needed.
  • Use Case: If you are building a custom skill for data analysis, use this tool to run a suite of test prompts, compare the results against a baseline, and automatically improve the skill's description to ensure it triggers correctly for your specific data formats.

Quick Start

Use the skill-creator to draft a new skill for summarizing technical documentation and set up an initial test suite.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I automate testing and benchmarking for custom AI skills?▼

You can automate testing and benchmarking by running iterative test suites that execute prompts, compare results against baselines, and generate quantitative performance metrics to ensure AI skill reliability.

How does prompt engineering improve AI agent triggering accuracy?▼

Prompt engineering improves triggering accuracy by iteratively refining skill descriptions in a dedicated loop, ensuring the AI agent invokes the correct skill precisely when needed based on user inputs.

What is the best way to manage skill code and test cases during development?▼

The best way to manage skill code and test cases is integrating with local file systems to store instructions, track test prompts, and generate performance reports throughout the development lifecycle.

Can I use this to refine an existing AI skill, or is it only for drafting new ones?▼

You can use this for both drafting new AI skills and refining existing ones, supporting an iterative development loop to test, evaluate, and optimize instructions based on user feedback.

Why does my custom AI skill fail to trigger correctly for specific data formats?▼

Custom AI skills fail to trigger when descriptions lack specificity, which you solve by using description tuning loops to refine triggering accuracy for your specific data formats and use cases.

Do I need external dependencies to run quantitative benchmarking on AI skills?▼

No external dependencies are required to run quantitative benchmarking on AI skills, as the tool operates autonomously to execute test cases and generate comparative metrics locally.

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