
skill-creator
by TechNickAI
Python project template with Ruff for linting/formatting, pytest for testing, pre-commit hooks, and GitHub Actions CI/CD. Includes Claude Code and Cursor configuration.
SKILL.md
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.
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 100以上
3ヶ月以内に更新
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
Reviews coming soon

