skill-creator

---

name: skill-creator description: Use when creating new skills or editing existing skills - applies prompt engineering principles to write clear, goal-focused process documentation that trusts LLM intelligence

Core principle: Trust the LLM's intelligence. Describe what needs to happen and why, not step-by-step how.

Skip skills for one-off solutions, well-documented standard practices, or project-specific conventions (use CLAUDE.md instead).

---
name: skill-name-with-hyphens
description: Use when [triggering conditions] - [what it does and how it helps]
---

# Skill Name

## Overview

What is this? Core principle in 1-2 sentences.

## When to Use

Clear triggers and symptoms. When NOT to use.

## Core Pattern

Show desired approach with examples. Describe alternatives in prose.

## Common Pitfalls

What goes wrong and how to avoid it.

Frontmatter requirements:

name: Letters, numbers, hyphens only. Use verb-first active voice (e.g., creating-skills not skill-creation).

description: Third-person, under 500 characters. Start with "Use when..." to describe triggering conditions, then explain what it does. Include concrete symptoms and situations, not just abstract concepts.

Good: "Use when tests have race conditions or pass/fail inconsistently - replaces arbitrary timeouts with condition polling for reliable async tests"

Good pattern:

// Use condition-based waiting for reliable async tests
await waitFor(() => element.textContent === "loaded");
await waitFor(() => user.isAuthenticated === true);
await waitFor(() => data.length > 0);

Then in prose: "Avoid arbitrary timeouts like setTimeout() which make tests brittle and slow."

Focus on goals, not process: Describe outcomes and constraints. Let the LLM figure out how to achieve them.

Good: "Ensure each test has a clear failure mode that identifies what's wrong. Tests should verify behavior, not implementation details."

Positive framing: Frame as "do this" not "avoid that." Focus on what success looks like.

Good: "Write minimal code to pass the test. Add features only when tests require them."

Trust intelligence: Assume the LLM can handle edge cases and variations. Specify boundaries, not decision trees.

Good: "Check if files exist before copying. If they differ, show changes and ask the user what to do."

With supporting files (when needed):

skill-name/
  SKILL.md           # Overview + patterns
  reference.md       # Heavy API docs (100+ lines)
  tool-example.ts    # Reusable code to adapt

Only separate files for heavy reference material (comprehensive API docs) or reusable tools (actual code to copy/adapt).

Keep inline: Principles and concepts, code patterns under 50 lines, everything else.

Put searchable terms in the description and throughout the content.

Content:

• Goals and outcomes, not rigid procedures
• Positive framing (show what to do)
• Trust LLM intelligence (avoid over-prescription)
• Keywords for search throughout
• Common pitfalls addressed

Organization:

• Self-contained in SKILL.md when possible
• Supporting files only when truly needed
• Under 500 words unless it's reference material

Showing anti-patterns: Demonstrating "wrong" code teaches that pattern. Describe alternatives in prose instead.

Vague triggers: "Use when debugging" is too broad. "Use when encountering test failures with unclear root causes" is specific.

First person: Skills inject into system prompts. Write "Use when..." not "I can help when..."

Missing keywords: Future Claude searches for skills by symptoms and errors. Include the terms someone would actually search for.