skill-creator

Create Claude skills with SKILL.md structure and eval-driven validation.

415|44|Updated Mar 18, 2026
One-click install
npx skills add https://github.com/notque/vexjoy-agent --skill skill-creator-notque
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-creator
Source: https://github.com/notque/vexjoy-agent/tree/main/skills/meta/skill-creator
Command: npx skills add https://github.com/notque/vexjoy-agent --skill skill-creator-notque

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, bash, grep, glob, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Preventing AI from skipping methodology by building skills that are validated through eval-driven testing and evidence-based gates.

Core Features & Use Cases

  • Skill creation & scope capture: turns a user’s intent into a routed skill with triggers, pairs_with, and category/complexity metadata.
  • Eval loop for iterative improvement: drafts a skill, generates realistic test prompts, runs with-skill vs without-skill comparisons, evaluates, and improves until measurable gains plateau.
  • Maintenance-ready artifacts: supports creation/iteration with SPEC.md and EVAL.md for complex/high-impact skill behavior.
  • Validation gates & cleanliness checks: enforces frontmatter correctness, reference framing pairings, verdict tagging where patterns exist, and index regeneration.

Quick Start

Use skill-creator to scaffold a new skill from your desired workflow, then run the eval/test loop to iteratively improve triggering and execution quality.

Frequently Asked Questions about skill-creator

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

FAQPage Schema
How do I create AI skills that prevent methodology shortcutting?

You can prevent AI shortcutting by building skills with eval-driven validation gates and evidence-based benchmarks. This skill constructs routed SKILL.md files that enforce progressive-disclosure structure and deterministic validators to measure behavior improvements.

What is an eval loop for iterative skill creation?

An eval loop for skill creation drafts a skill, generates realistic test prompts, and runs with-skill versus without-skill baseline comparisons. It evaluates and improves execution quality until measurable performance gains plateau.

How do I validate frontmatter correctness and trigger routing for new skills?

You validate frontmatter correctness by running deterministic validators that enforce trigger-rich metadata, pairs_with configurations, and category complexity routing. This skill applies validation gates and cleanliness checks to ensure proper skill triggering.

Do I need Python and bash to build eval-driven skills?

Yes, you need Python3 and bash along with grep and glob to construct eval-driven skills. These dependencies support running deterministic validators, executing benchmark comparisons, and generating maintenance artifacts like SPEC.md and EVAL.md.

When should I generate SPEC.md and EVAL.md files for my workflow skills?

You should generate SPEC.md and EVAL.md files when creating complex or high-impact domain and meta workflow skills. These maintenance-ready artifacts support iterative improvement through evidence-based grading and blind comparison benchmarks.

Why does my AI skip required workflow steps without benchmarking guardrails?

AI skips methodology when skills lack eval-driven testing and evidence-based gates. This skill solves the problem by applying validation gates, constructing trigger-rich frontmatter, and iterating using benchmarks with blind comparison to enforce strict progressive-disclosure structure.