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Create New Skills

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disler
Create New Skills

Creates new Agent Skills for Claude Code following best practices and documentation. Use when the user wants to create a new skill, extend Claude's capabilities, or package domain expertise into a reusable skill.

Overview

Publisherdisler
Repositoryclaude-code-hooks-multi-agent-observability
Skill nameCreate New Skills
Stars
1.5K
Forks
384
Bundled files
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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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Create New Skills 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/disler/claude-code-hooks-multi-agent-observability/tree/main/.claude/skills/meta-skill
  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/disler/claude-code-hooks-multi-agent-observability.git /tmp/claude-code-hooks-multi-agent-observability
mkdir -p .claude/skills
cp -r /tmp/claude-code-hooks-multi-agent-observability/.claude/skills/meta-skill .claude/skills/disler-create-new-skills
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create New Skills 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 New Skills 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 New Skills 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.

Create New Skills

Instructions

This skill helps you create new Agent Skills for Claude Code. Before starting, read the comprehensive documentation files in the docs/ directory for complete context.

Prerequisites

Required Reading - Read these files in order before creating a skill:

  1. docs/claude_code_agent_skills.md - Complete guide to creating and managing skills
  2. docs/claude_code_agent_skills_overview.md - Architecture and how skills work
  3. docs/blog_equipping_agents_with_skills.md - Design principles and best practices

Understanding Skills

What is a Skill?

  • A directory containing a SKILL.md file with YAML frontmatter
  • Instructions that Claude loads on-demand when relevant
  • Optional supporting files (scripts, documentation, templates)
  • Like an onboarding guide for a new team member

Progressive Disclosure (3 Levels):

  1. Metadata (always loaded): name and description in YAML frontmatter
  2. Instructions (loaded when triggered): Main body of SKILL.md
  3. Resources (loaded as needed): Additional files, scripts, templates

Key Principle: Only relevant content enters the context window at any time.

Skill Creation Workflow

Step 1: Define the Skill's Purpose

Ask the user these questions:

  1. What task or domain should this skill cover?
  2. When should Claude use this skill? (triggers)
  3. What expertise or workflows need to be captured?
  4. Does it need scripts, templates, or other resources?

Document the answers for reference.

Step 2: Create the Skill Directory Structure

Create skills in the project's .claude/skills/ directory for team sharing:

bash
mkdir -p .claude/skills/<skill-name>

Naming conventions:

  • Use lowercase with hyphens (e.g., pdf-processing, data-analysis)
  • Be descriptive but concise
  • Avoid generic names

Note: Project skills (.claude/skills/) are automatically shared with your team via git. For personal skills only you use, create in ~/.claude/skills/ instead.

Step 3: Design the SKILL.md Structure

Every skill must have:

yaml
---
name: Your Skill Name
description: Brief description of what this Skill does and when to use it
---

# Your Skill Name

## Instructions
[Clear, step-by-step guidance for Claude]

## Examples
[Concrete examples of using this Skill]

Frontmatter Requirements:

  • name: Required, max 64 characters
  • description: Required, max 1024 characters
    • Include BOTH what it does AND when to use it
    • Mention key trigger words/phrases
    • Be specific, not vague

Optional Frontmatter (Claude Code only):

  • allowed-tools: Restrict which tools Claude can use (e.g., Read, Grep, Glob)
Step 4: Write the Instructions Section

Structure the instructions as:

  1. Prerequisites - Required dependencies, tools, environment setup
  2. Workflow - Step-by-step process (numbered steps)
  3. Supporting Details - Additional context, script usage, error handling

Best Practices:

  • Use clear, actionable language
  • Number sequential steps
  • Use bullet points for options/lists
  • Include code blocks with bash commands
  • Reference supporting files with relative links: [reference.md](reference.md)
  • Keep focused on one capability

Example workflow format:

markdown
### Workflow

1. **First step description**:
   ```bash
   command to run
  • Additional context
  • Options or variations
  1. Second step description:

    • Detailed instructions
    • What to look for
    • Expected outcomes
  2. Third step...


#### Step 5: Write the Examples Section

Provide 2-4 concrete examples showing:
- Different use cases
- Various input formats
- Step-by-step execution
- Expected outcomes

**Example format:**
```markdown
### Example 1: Descriptive Title

User request:

User's exact request text


You would:
1. First action
2. Second action with command:
   ```bash
   actual command
  1. Next steps...
  2. Final result

#### Step 6: Add Supporting Files (Optional)

If the skill needs additional context:
1. Create files alongside SKILL.md
2. Reference them from instructions: `[forms.md](forms.md)`
3. Use progressive disclosure - split by topic/scenario

**Common supporting file types:**
- Additional instructions (e.g., `advanced_usage.md`)
- Reference documentation (e.g., `api_reference.md`)
- Scripts in `scripts/` directory
- Templates in `templates/` directory
- Configuration examples

**Script guidelines:**
- Make executable: `chmod +x scripts/*.py`
- Add PEP 723 inline dependencies for Python scripts
- Include usage instructions in SKILL.md
- Return clear output for Claude to parse

#### Step 7: Test the Skill

1. Verify file structure:
   ```bash
   ls -la .claude/skills/<skill-name>/
  1. Check YAML frontmatter is valid:

    bash
    head -10 .claude/skills/<skill-name>/SKILL.md
  2. Test with relevant queries:

    • Ask questions matching the skill's description
    • Verify Claude loads and uses the skill
    • Check that instructions are clear and actionable
  3. Iterate based on testing:

    • Refine description if skill doesn't trigger
    • Clarify instructions if Claude struggles
    • Add examples for common edge cases
Step 8: Commit to Version Control

Since project skills are automatically shared with your team, commit them to git:

bash
git add .claude/skills/<skill-name>
git commit -m "Add <skill-name> skill"
git push

Note: Team members will get the skill automatically when they pull the latest changes.

Best Practices Summary

Description writing:

  • ✅ "Transcribes audio/video files to text using Fireworks API. Use when user asks to transcribe, convert speech to text, or needs transcripts."
  • ❌ "Helps with audio"

Instruction organization:

  • Keep main instructions focused (under 5k tokens ideal)
  • Split complex content into linked files
  • Use progressive disclosure for optional/advanced content

Skill scope:

  • One skill = one capability or workflow
  • Don't combine unrelated tasks
  • Make focused, composable skills

File references:

  • Use relative paths: [file.md](file.md) not absolute paths
  • Reference scripts with full path from skill root
  • Make it clear when Claude should read vs execute files

Common Patterns from Existing Skills

Pattern 1: Transcription skill

  • Prerequisites section with environment setup
  • Clear numbered workflow
  • Multiple examples showing different formats
  • Supporting file for corrections/mappings

Pattern 2: Morning debrief skill

  • Two-step process (transcribe, extend)
  • Reference to detailed prompt in separate file
  • File organization step
  • Clear output structure specification

Pattern 3: Meta-skill (this one)

  • Extensive prereading documentation
  • Step-by-step creation workflow
  • Multiple examples with variations
  • Best practices and common patterns

Examples

Example 1: Creating a Simple Code Review Skill

User request:

Create a skill that reviews Python code for best practices

You would:

  1. Read the documentation files in docs/
  2. Ask clarifying questions:
    • What specific best practices? (PEP 8, security, performance?)
    • Should it check only or suggest fixes?
    • Any specific frameworks or libraries?
  3. Create the skill directory:
    bash
    mkdir -p .claude/skills/python-code-review
  4. Write SKILL.md with:
    yaml
    ---
    name: Python Code Review
    description: Reviews Python code for PEP 8 compliance, security issues, and performance. Use when reviewing Python code, checking code quality, or analyzing Python files.
    allowed-tools: Read, Grep, Glob
    ---
  5. Add Instructions section with:
    • Prerequisites (none needed, uses built-in tools)
    • Workflow:
      1. Read the Python file(s)
      2. Check PEP 8 compliance
      3. Identify security issues
      4. Suggest performance improvements
      5. Provide summary with specific line references
  6. Add 3 examples:
    • Example 1: Single file review
    • Example 2: Multi-file project review
    • Example 3: Focused security review
  7. Test with sample Python files

Example 2: Creating a Data Analysis Skill with Scripts

User request:

Build a skill for analyzing CSV data with statistics and visualizations

You would:

  1. Read documentation files
  2. Define scope with user:
    • What statistics? (mean, median, correlations?)
    • What visualizations? (charts, plots?)
    • Output format? (markdown report, images?)
  3. Create structure:
    bash
    mkdir -p .claude/skills/csv-analysis/scripts
    mkdir -p .claude/skills/csv-analysis/templates
  4. Write SKILL.md referencing:
    • scripts/analyze.py - Statistical analysis script
    • scripts/visualize.py - Chart generation script
    • templates/report_template.md - Output template
  5. Create Python scripts with inline dependencies:
    python
    # /// script
    # requires-python = ">=3.10"
    # dependencies = ["pandas", "matplotlib", "seaborn"]
    # ///
  6. Write clear instructions for:
    • When to run which script
    • How to interpret output
    • How to customize analysis
  7. Add examples showing:
    • Basic statistics
    • Visualization generation
    • Custom report creation
  8. Test with sample CSV files

Example 3: Creating a Multi-File Documentation Skill

User request:

Create a skill for writing technical documentation with our company's style guide

You would:

  1. Read documentation files
  2. Gather requirements:
    • Get company style guide document
    • What types of docs? (API, user guides, architecture?)
    • Any templates or examples?
  3. Create comprehensive structure:
    bash
    mkdir -p .claude/skills/tech-docs/{templates,examples,guidelines}
  4. Organize content:
    • SKILL.md - Overview and workflow
    • guidelines/style_guide.md - Company style rules
    • guidelines/api_docs.md - API documentation specifics
    • guidelines/user_guides.md - User guide standards
    • templates/api_template.md - API doc template
    • templates/guide_template.md - User guide template
    • examples/ - Sample documentation
  5. Write SKILL.md that:
    • References guidelines by doc type
    • Uses progressive disclosure (only load needed guidelines)
    • Provides workflow for each doc type
  6. Add examples for:
    • API endpoint documentation
    • User guide creation
    • Architecture decision records
  7. Test with various documentation requests

Example 4: Extending an Existing Skill

User request:

Add spell correction to our transcribe skill

You would:

  1. Read current skill:
    bash
    cat .claude/skills/transcribe/SKILL.md
  2. Identify where to add the feature:
    • After transcription step
    • Before final output
  3. Create supporting file:
    bash
    touch .claude/skills/transcribe/spell_corrections.md
  4. Write correction mappings in new file:
    markdown
    # Spell Corrections
    - "cloud code" → "claude code"
    - "API" → "API" (ensure caps)
    ...
  5. Update SKILL.md workflow:
  6. Update examples to show correction step
  7. Test with audio that has common errors

Summary

Creating skills is about packaging expertise into discoverable, composable capabilities. Follow these principles:

  1. Read the docs first - Understand progressive disclosure and skill architecture
  2. Write clear descriptions - Include what AND when
  3. Keep instructions focused - Use supporting files for additional context
  4. Test thoroughly - Verify Claude discovers and uses the skill correctly
  5. Iterate with feedback - Refine based on actual usage

Skills transform general-purpose Claude into a specialist for your domain. Start small, test early, and expand as needed.

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 New Skills AI skill do?

Creates new Agent Skills for Claude Code following best practices and documentation. Use when the user wants to create a new skill, extend Claude's capabilities, or package domain expertise into a reusable skill.

Why use Create New Skills on TypingMind?

Because you install it once and use it with any model. Create New Skills 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 New Skills in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/disler/claude-code-hooks-multi-agent-observability/tree/main/.claude/skills/meta-skill. 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 New Skills?

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 New Skills?

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

Is the Create New Skills AI skill free?

It is published on GitHub by disler. Check the repository for licensing terms. 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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