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Create Skill File

Community
YYH211
create-skill-file

Guides Claude in creating well-structured SKILL.md files following best practices. Provides clear guidelines for naming, structure, and content organization to make skills easy to discover and execute.

Overview

PublisherYYH211
RepositoryClaude-meta-skill
Skill namecreate-skill-file
Stars
285
Forks
28
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by YYH211 on GitHub. Read the source before you install it.

Installation

Install the Create Skill File AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/YYH211/Claude-meta-skill/tree/main/create-skill-file-EN
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/YYH211/Claude-meta-skill.git /tmp/Claude-meta-skill
mkdir -p .claude/skills
cp -r /tmp/Claude-meta-skill/create-skill-file-EN .claude/skills/create-skill-file
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Skill File in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Create Skill File on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Create Skill File is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Claude Agent Skill Writing Guide

How to create high-quality SKILL.md files

Table of Contents


Quick Start

3 Steps to Create a Skill

Step 1: Create Directory

bash
mkdir -p .claude/skill/your-skill-name
cd .claude/skill/your-skill-name

Step 2: Create SKILL.md

markdown
---
name: your-skill-name
description: Brief description with trigger keywords and scenarios
---

# Your Skill Title

## When to Use This Skill

- User asks to [specific scenario]
- User mentions "[keyword]"

## How It Works

1. Step 1: [Action]
2. Step 2: [Action]

## Examples

**Input**: User request
**Output**: Expected result

Step 3: Test

  • Use keywords from description in conversation to trigger
  • Observe whether Claude executes correctly
  • Adjust based on effectiveness

Core Principles

1. Keep It Concise

Only add new knowledge that Claude doesn't know:

  • ✅ Project-specific workflows
  • ✅ Special naming conventions or format requirements
  • ✅ How to use custom tools and scripts
  • ❌ General programming knowledge
  • ❌ Obvious steps

Example Comparison:

markdown
# ❌ Too Detailed
1. Create Python file
2. Import necessary libraries
3. Define functions
4. Write main program logic

# ✅ Concise and Effective
Use `scripts/api_client.py` to call internal API.
Request headers must include `X-Internal-Token` (from environment variable `INTERNAL_API_KEY`).

2. Set Appropriate Freedom

FreedomUse CaseWriting Approach
HighRequires creativity, multiple solutionsProvide guiding principles, not specific steps
MediumRecommended patterns but allow variationsProvide parameterized examples and default flows
LowError-prone, requires strict executionProvide detailed step-by-step instructions or scripts

Decision Criteria:

  • Is there a clear "correct answer"? → Low freedom
  • Does it need to adapt to different scenarios? → High freedom
  • What's the cost of errors? → High cost = low freedom

3. Progressive Disclosure

Organize complex content in layers:

SKILL.md (Main document, 200-500 lines)
├── reference.md (Detailed documentation)
├── examples.md (Complete examples)
└── scripts/ (Executable scripts)

Rules:

  • SKILL.md > 500 lines → Split into sub-files
  • Sub-files > 100 lines → Add table of contents
  • Reference depth ≤ 1 level

File Structure Standards

YAML Frontmatter

yaml
---
name: skill-name-here
description: Clear description of what this skill does and when to activate it
---

Field Specifications:

FieldRequirementsDescription
nameLowercase letters, numbers, hyphens, ≤64 charactersMust match directory name
descriptionPlain text, ≤1024 charactersUsed for retrieval and activation

Naming Prohibitions:

  • ❌ XML tags, reserved words (anthropic, claude)
  • ❌ Vague terms (helper, utility, manager)
  • ❌ Spaces or underscores (use hyphens -)

Description Tips:

yaml
# ❌ Too Generic
description: Helps with code tasks

# ✅ Specific with Keywords
description: Processes CSV files and generates Excel reports with charts. Use when user asks to convert data formats or create visual reports.

# ✅ States Trigger Scenarios
description: Analyzes Python code for security vulnerabilities using bandit. Activates when user mentions "security audit" or "vulnerability scan".

Directory Organization

Basic Structure (Simple Skill):

skill-name/
└── SKILL.md

Standard Structure (Recommended):

skill-name/
├── SKILL.md
├── templates/
│   └── template.md
└── scripts/
    └── script.py

Naming and Description Standards

Skill Naming

Recommended Format: Verb-ing + noun form

✅ Good Names:
- processing-csv-files
- generating-api-docs
- managing-database-migrations

❌ Bad Names:
- csv (too brief)
- data_processor (uses underscores)
- helper (too vague)

Description Writing

Must use third person:

yaml
# ❌ Wrong
description: I help you process PDFs

# ✅ Correct
description: Processes PDF documents and extracts structured data

4C Principles:

  • Clear: Avoid jargon and vague terms
  • Concise: 1-2 sentences explaining core functionality
  • Contextual: Describe applicable scenarios
  • Complete: Functionality + trigger conditions

Content Writing Guide

"When to Use" Section

Clearly state trigger scenarios:

markdown
## When to Use This Skill

- User asks to analyze Python code for type errors
- User mentions "mypy" or "type checking"
- User is working in a Python project with type hints
- User needs to add type annotations

Patterns:

  • Direct request: "User asks to X"
  • Keywords: "User mentions 'keyword'"
  • Context: "User is working with X"
  • Task type: "User needs to X"

Workflow Design

Simple Linear Flow:

markdown
## How It Works

1. Scan the project for all `.py` files
2. Run `mypy --strict` on each file
3. Parse error output and categorize by severity
4. Generate summary report with fix suggestions

Conditional Branching Flow:

markdown
## Workflow

1. **Check project type**
   - If Django → Use `django-stubs` config
   - If Flask → Use `flask-stubs` config
   - Otherwise → Use default mypy config

2. **Run type checking**
   - If errors found → Proceed to step 3
   - If no errors → Report success and exit

Checklist Pattern (Validation tasks):

markdown
## Pre-deployment Checklist

Execute in order. Stop if any step fails.

- [ ] Run tests: `npm test` (must pass)
- [ ] Build: `npm run build` (no errors)
- [ ] Check deps: `npm audit` (no critical vulnerabilities)

Examples and Templates

Input-Output Examples:

markdown
## Examples

### Example 1: Basic Check

**User Request**: "Check my code for type errors"

**Action**:
1. Scan for `.py` files
2. Run `mypy` on all files

**Output**:

   Found 3 type errors in 2 files:
   src/main.py:15: error: Missing return type
   src/utils.py:42: error: Incompatible types

Script Integration

When to Use Scripts:

  • Simple commands → Describe directly in SKILL.md
  • Complex processes → Provide standalone scripts

Script Writing Standards:

python
#!/usr/bin/env python3
"""
Brief description of what this script does.

Usage:
    python script.py <arg> [--option value]
"""

import argparse

DEFAULT_VALUE = 80  # Use constants, not magic numbers

def main():
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("directory", help="Directory to process")
    parser.add_argument("--threshold", type=int, default=DEFAULT_VALUE)

    args = parser.parse_args()

    # Validate inputs
    if not Path(args.directory).is_dir():
        print(f"Error: {args.directory} not found")
        return 1

    # Execute
    result = process(args.directory, args.threshold)

    # Report
    print(f"Processed {result['count']} files")
    return 0

if __name__ == "__main__":
    exit(main())

Key Standards:

  • ✅ Shebang line and docstring
  • ✅ Type annotations and constants
  • ✅ Parameter validation and error handling
  • ✅ Clear return values (0=success, 1=failure)

Best Practices

Do:

  • ✅ Provide executable commands and scripts
  • ✅ Include input-output examples
  • ✅ State validation criteria and success conditions
  • ✅ Include Do/Don't lists

Don't:

  • ❌ Include general knowledge Claude already knows
  • ❌ Use abstract descriptions instead of concrete steps
  • ❌ Omit error handling guidance
  • ❌ Use pseudocode instead of real code in examples

Quality Checklist

Core Quality

  • name follows naming conventions (lowercase, hyphens, ≤64 characters)
  • description includes trigger keywords and scenarios (≤1024 characters)
  • Name matches directory name
  • Only includes information Claude doesn't know
  • No redundant or duplicate content

Functional Completeness

  • Has "When to Use" section with 3-5 trigger scenarios
  • Has clear execution flow or steps
  • At least 2-3 complete examples
  • Includes input and expected output
  • Error handling guidance provided

Structure Standards

  • Clear section organization
  • Table of contents for >200 lines
  • Reference nesting ≤ 1 level
  • All paths use forward slashes /
  • Consistent terminology

Scripts and Templates

  • Scripts include usage instructions and parameter documentation
  • Scripts have error handling
  • Avoid magic numbers, use configuration
  • Template format is clear and usable

Final Check

  • Read through for fluency and readability
  • Test triggering with actual scenarios
  • Appropriate length (200-500 lines, or split)

FAQ

Q: How long should a Skill be?

  • Minimum: 50-100 lines
  • Ideal: 200-500 lines
  • Maximum: 500 lines (split if exceeded)

Q: How to make Skills easier to activate?

  • Use keywords in description that users would say
  • State specific scenarios ("when user asks to X")
  • Mention related tool names

Q: What if multiple Skills overlap?

  • Use more specific description to differentiate
  • Explain relationships in "When to Use"
  • Consider merging into one Skill

Q: Do Skills need maintenance?

  • Review quarterly, update outdated information
  • Iterate based on usage feedback
  • Update promptly when tools or APIs change

Quick Reference

Frontmatter Template

yaml
---
name: skill-name
description: Brief description with trigger keywords
---

Basic Structure Template

markdown
# Skill Title

## When to Use This Skill
- Scenario 1
- Scenario 2

## How It Works
1. Step 1
2. Step 2

## Examples
### Example 1
...

## References
- [Link](url)

Related Resources


Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Create Skill File AI skill do?

Guides Claude in creating well-structured SKILL.md files following best practices. Provides clear guidelines for naming, structure, and content organization to make skills easy to discover and execute.

Why use Create Skill File on TypingMind?

Because you install it once and use it with any model. Create Skill File is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Create Skill File in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/YYH211/Claude-meta-skill/tree/main/create-skill-file-EN. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Create Skill File?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Create Skill File?

As many as you like. As long as a model supports skills, you can use Create Skill File with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Create Skill File AI skill free?

Yes. It is published on GitHub by YYH211 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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