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:
- •docs/claude_code_agent_skills.md - Complete guide to creating and managing skills
- •docs/claude_code_agent_skills_overview.md - Architecture and how skills work
- •docs/blog_equipping_agents_with_skills.md - Design principles and best practices
Understanding Skills
What is a Skill?
- •A directory containing a
SKILL.mdfile 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):
- •Metadata (always loaded):
nameanddescriptionin YAML frontmatter - •Instructions (loaded when triggered): Main body of SKILL.md
- •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:
- •What task or domain should this skill cover?
- •When should Claude use this skill? (triggers)
- •What expertise or workflows need to be captured?
- •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:
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:
--- 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:
- •Prerequisites - Required dependencies, tools, environment setup
- •Workflow - Step-by-step process (numbered steps)
- •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:
### Workflow 1. **First step description**: ```bash command to run
- •Additional context
- •Options or variations
- •
Second step description:
- •Detailed instructions
- •What to look for
- •Expected outcomes
- •
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
- •Next steps...
- •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>/
- •
Check YAML frontmatter is valid:
bashhead -10 .claude/skills/<skill-name>/SKILL.md
- •
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
- •
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:
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:
- •Read the documentation files in docs/
- •Ask clarifying questions:
- •What specific best practices? (PEP 8, security, performance?)
- •Should it check only or suggest fixes?
- •Any specific frameworks or libraries?
- •Create the skill directory:
bash
mkdir -p .claude/skills/python-code-review
- •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 ---
- •Add Instructions section with:
- •Prerequisites (none needed, uses built-in tools)
- •Workflow:
- •Read the Python file(s)
- •Check PEP 8 compliance
- •Identify security issues
- •Suggest performance improvements
- •Provide summary with specific line references
- •Add 3 examples:
- •Example 1: Single file review
- •Example 2: Multi-file project review
- •Example 3: Focused security review
- •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:
- •Read documentation files
- •Define scope with user:
- •What statistics? (mean, median, correlations?)
- •What visualizations? (charts, plots?)
- •Output format? (markdown report, images?)
- •Create structure:
bash
mkdir -p .claude/skills/csv-analysis/scripts mkdir -p .claude/skills/csv-analysis/templates
- •Write SKILL.md referencing:
- •
scripts/analyze.py- Statistical analysis script - •
scripts/visualize.py- Chart generation script - •
templates/report_template.md- Output template
- •
- •Create Python scripts with inline dependencies:
python
# /// script # requires-python = ">=3.10" # dependencies = ["pandas", "matplotlib", "seaborn"] # ///
- •Write clear instructions for:
- •When to run which script
- •How to interpret output
- •How to customize analysis
- •Add examples showing:
- •Basic statistics
- •Visualization generation
- •Custom report creation
- •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:
- •Read documentation files
- •Gather requirements:
- •Get company style guide document
- •What types of docs? (API, user guides, architecture?)
- •Any templates or examples?
- •Create comprehensive structure:
bash
mkdir -p .claude/skills/tech-docs/{templates,examples,guidelines} - •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
- •
- •Write SKILL.md that:
- •References guidelines by doc type
- •Uses progressive disclosure (only load needed guidelines)
- •Provides workflow for each doc type
- •Add examples for:
- •API endpoint documentation
- •User guide creation
- •Architecture decision records
- •Test with various documentation requests
Example 4: Creating a Spec Validation Skill
User request:
Create a skill that validates spec quality before proceeding
You would:
- •Read the documentation files
- •Define scope with user:
- •What to validate? (EARS format, traceability, completeness)
- •When to validate? (After each phase or on-demand)
- •What level of strictness? (Warnings vs errors)
- •Review existing spec skills for patterns:
- •See requirements-skill/VALIDATION.md for quality checks
- •See design-skill for traceability patterns
- •See tasks-skill for completeness checks
- •Create structure:
bash
mkdir -p .claude/skills/spec-validation
- •Write SKILL.md with:
yaml
--- name: Spec Quality Validation description: Validate specification quality across all phases. Use when reviewing specs, checking EARS format, verifying traceability, or ensuring completeness before phase transitions. allowed-tools: Read, Grep ---
- •Add validation workflow:
- •Load spec document
- •Check format (EARS keywords, SHALL usage)
- •Verify traceability (REQ references present)
- •Assess completeness (all sections filled)
- •Generate validation report
- •Create supporting files:
- •
CHECKLIST.md- Complete validation checklist - •
EXAMPLES.md- Good vs bad spec examples - •
FIXES.md- How to fix common issues
- •
- •Test with sample specs from examples/ directory
Example 5: Extending an Existing Skill
User request:
Add spell correction to our transcribe skill
You would:
- •Read current skill:
bash
cat .claude/skills/transcribe/SKILL.md
- •Identify where to add the feature:
- •After transcription step
- •Before final output
- •Create supporting file:
bash
touch .claude/skills/transcribe/spell_corrections.md
- •Write correction mappings in new file:
markdown
# Spell Corrections - "cloud code" → "claude code" - "API" → "API" (ensure caps) ...
- •Update SKILL.md workflow:
- •Add step: "Apply spell corrections from spell_corrections.md"
- •Reference the corrections file
- •Update examples to show correction step
- •Test with audio that has common errors
Summary
Creating skills is about packaging expertise into discoverable, composable capabilities. Follow these principles:
- •Read the docs first - Understand progressive disclosure and skill architecture
- •Write clear descriptions - Include what AND when
- •Keep instructions focused - Use supporting files for additional context
- •Test thoroughly - Verify Claude discovers and uses the skill correctly
- •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.