skills.rest
TW-NLP
TW-NLPCOMMUNITY
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skill-creator

Create, improve, and evaluate AI skills with SKILL.md files.

91|11|Updated Jan 15, 2026
Search Tags:#skill creation#AI development#skill improvement#skill evaluation#AI lifecycle management
One-click install
npx skills add https://github.com/TW-NLP/DeepAgentForce --skill skill-creator-tw-nlp
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/TW-NLP/DeepAgentForce/tree/main/src/services/skills/development/skill-creator
Command: npx skills add https://github.com/TW-NLP/DeepAgentForce --skill skill-creator-tw-nlp

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the process of creating, improving, and evaluating skills, allowing users to efficiently manage their AI agent's capabilities.

Core Features & Use Cases

  • Skill Creation: Assist users in capturing intent, writing SKILL.md files, and creating test cases.
  • Skill Improvement: Iterate on skills by running evaluations, analyzing feedback, and applying improvements.
  • Skill Evaluation: Automate the testing and benchmarking of skills to measure performance and identify areas for improvement.
  • Use Case: When users want to create a new skill, optimize an existing one, or evaluate its performance.

Quick Start

Use the skill-creator skill to help me create a skill that can summarize meeting notes.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I create an AI skill from scratch using a SKILL.md file?▼

To create an AI skill, you capture user intent, write a SKILL.md file defining the behavior, and establish test cases to validate the generated skill performance.

What is the best way to evaluate and improve AI skill performance?▼

Evaluating and improving AI skill performance requires running automated benchmarking tests, analyzing feedback, and iterating on the skill description to optimize outputs.

Do I need Python to manage the AI skill lifecycle?▼

Yes, managing the AI skill lifecycle requires Python and knowledge of AI runtime environments to execute scripts, evaluate performance, and process skill components.

How does automated skill benchmarking identify areas for improvement?▼

Automated skill benchmarking identifies improvement areas by running predefined test cases against the skill, measuring performance metrics, and highlighting failures in the evaluation feedback.

Can I optimize an existing AI skill description without rewriting the entire logic?▼

Yes, you can optimize an existing AI skill description by evaluating current performance, analyzing test feedback, and iterating specifically on the SKILL.md file to refine intent capture.

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