Agent Skills: Skill Creator

Skill Creator

This skill provides guidance for creating effective skills.

About Skills

Skills are modular, self-contained packages that extend an agent's capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.

What Skills Provide

1. Specialized workflows - Multi-step procedures for specific domains
2. Tool integrations - Instructions for working with specific file formats or APIs
3. Domain expertise - Company-specific knowledge, schemas, business logic
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks

Core Principles

Concise is Key

The context window is a public good. Skills share the context window with everything else the agent needs: system prompt, conversation history, other Skills' metadata, and the actual user request.

Default assumption: the agent is already very smart. Only add context it doesn't already have. Challenge each piece of information: "Does the agent really need this explanation?" and "Does this paragraph justify its token cost?"

Prefer concise examples over verbose explanations.

Set Appropriate Degrees of Freedom

Match the level of specificity to the task's fragility and variability:

High freedom (text-based instructions): Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.

Medium freedom (pseudocode or scripts with parameters): Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.

Low freedom (specific scripts, few parameters): Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.

Think of the agent as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).

Anatomy of a Skill

Every skill consists of a required SKILL.md file and optional bundled resources:

skill-name/
├── SKILL.md (required)
│   ├── YAML frontmatter metadata (required)
│   │   ├── name: (required)
│   │   └── description: (required)
│   └── Markdown instructions (required)
└── Bundled Resources (optional)
    ├── scripts/          - Executable code (Python/Bash/etc.)
    ├── references/       - Documentation intended to be loaded into context as needed
    └── assets/           - Files used in output (templates, icons, fonts, etc.)

Skill Naming

Skill names must follow these rules:

• Format: hyphen-case identifier (e.g., data-analyzer, pdf-editor)
• Characters: lowercase letters, digits, and hyphens only
• Length: max 64 characters
• No leading/trailing hyphens: my-skill ✓, -my-skill ✗
• No consecutive hyphens: my-skill ✓, my--skill ✗
• Directory match: skill name must match directory name exactly

Good examples: pdf-editor, brand-guidelines, bigquery-helper Bad examples: PDFEditor, brand_guidelines, my--skill

SKILL.md (required)

Every SKILL.md consists of:

• Frontmatter (YAML): Contains name and description fields. These are the only fields the agent reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.
• Body (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).

YAML Frontmatter Tips

Quote strings containing special YAML characters:

# Bad - colon and quotes can break parsing
name: my-skill: v2
description: Use when user says "help me"

# Good - wrap in quotes
name: "my-skill: v2"
description: 'Use when user says "help me"'

Special characters requiring quotes: :, #, @, *, !, |, >, {, }, [, ], ,, &, ?

Bundled Resources (optional)

Scripts (scripts/)

Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.

• When to include: When the same code is being rewritten repeatedly or deterministic reliability is needed
• Example: scripts/rotate_pdf.py for PDF rotation tasks
• Benefits: Token efficient, deterministic, may be executed without loading into context
• Note: Scripts may still need to be read by the agent for patching or environment-specific adjustments

References (references/)

Documentation and reference material intended to be loaded as needed into context to inform the agent's process and thinking.

• When to include: For documentation that the agent should reference while working
• Examples: references/finance.md for financial schemas, references/mnda.md for company NDA template
• Use cases: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
• Benefits: Keeps SKILL.md lean, loaded only when the agent determines it's needed
• Best practice: If files are large (>10k words), include grep search patterns in SKILL.md
• Avoid duplication: Information should live in either SKILL.md or references files, not both.

Assets (assets/)

Files not intended to be loaded into context, but rather used within the output the agent produces.

• When to include: When the skill needs files that will be used in the final output
• Examples: assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates
• Use cases: Templates, images, icons, boilerplate code, fonts, sample documents
• Benefits: Separates output resources from documentation, enables the agent to use files without loading them into context

What to Not Include in a Skill

A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files:

• README.md
• INSTALLATION_GUIDE.md
• QUICK_REFERENCE.md
• CHANGELOG.md
• CONTRIBUTING.md
• .gitignore
• tests/ directory

The skill should only contain information needed for an AI agent to do the job at hand. It should not contain auxiliary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc.

Progressive Disclosure Design Principle

Skills use a three-level loading system to manage context efficiently:

1. Metadata (name + description) - Always in context (~100 words)
2. SKILL.md body - When skill triggers (<5k words)
3. Bundled resources - As needed by the agent (Unlimited because scripts can be executed without reading into context window)

Progressive Disclosure Patterns

Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit.

Key principle: When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details into separate reference files.

Pattern 1: High-level guide with references

# PDF Processing

## Quick start
Extract text with pdfplumber:
[code example]

## Advanced features
- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods

Pattern 2: Domain-specific organization

bigquery-skill/
├── SKILL.md (overview and navigation)
└── reference/
    ├── finance.md (revenue, billing metrics)
    ├── sales.md (opportunities, pipeline)
    └── product.md (API usage, features)

When a user asks about sales metrics, the agent only reads sales.md.

Pattern 3: Conditional details

# DOCX Processing

## Creating documents
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).

## Editing documents
For simple edits, modify the XML directly.
**For tracked changes**: See [REDLINING.md](REDLINING.md)

Important guidelines:

• Avoid deeply nested references - Keep references one level deep from SKILL.md
• Structure longer reference files - For files longer than 100 lines, include a table of contents

Skill Creation Process

1. Understand the skill with concrete examples
2. Plan reusable skill contents (scripts, references, assets)
3. Initialize the skill (run init_skill.py)
4. Edit the skill (implement resources and write SKILL.md)
5. Package the skill (run package_skill.py)
6. Iterate based on real usage

Step 1: Understanding the Skill with Concrete Examples

Skip this step only when the skill's usage patterns are already clearly understood.

To create an effective skill, clearly understand concrete examples of how the skill will be used:

• "What functionality should the skill support?"
• "Can you give some examples of how this skill would be used?"
• "What would a user say that should trigger this skill?"

Step 2: Planning the Reusable Skill Contents

Analyze each example by:

1. Considering how to execute on the example from scratch
2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly

Example: When building a pdf-editor skill, rotating a PDF requires re-writing the same code each time → a scripts/rotate_pdf.py script would be helpful.

Step 3: Initializing the Skill

When creating a new skill from scratch, run the init_skill.py script:

# Minimal: creates only SKILL.md
scripts/init_skill.py <skill-name> --path <output-directory>

# With specific resource directories
scripts/init_skill.py <skill-name> --path <output-directory> --resources scripts,references

# With example files in directories
scripts/init_skill.py <skill-name> --path <output-directory> --resources scripts,references --examples

Flags:

• --resources <dirs>: Comma-separated list of directories to create: scripts, references, assets
• --examples: Add example files in created directories (only works with --resources)

By default, the script creates only a SKILL.md file. Use --resources to selectively create the directories you need.

Step 4: Edit the Skill

When editing the skill, remember that it's being created for another AI agent to use. Include information that would be beneficial and non-obvious.

Learn Proven Design Patterns

Consult these helpful guides:

• Multi-step processes: See references/workflows.md for sequential workflows and conditional logic
• Specific output formats or quality standards: See references/output-patterns.md for template and example patterns

Start with Reusable Skill Contents

Start with the reusable resources identified above: scripts/, references/, and assets/ files. Added scripts must be tested by actually running them.

Update SKILL.md

Writing Guidelines: Always use imperative/infinitive form.

Frontmatter

Write the YAML frontmatter with name and description:

• name: The skill name (must match directory name)
• description: This is the primary triggering mechanism for your skill
  • Include both what the Skill does and specific triggers/contexts for when to use it
  • Include all "when to use" information here - Not in the body

Do not include any other fields in YAML frontmatter except optional license.

Body

Write instructions for using the skill and its bundled resources.

Step 5: Packaging a Skill

Once development is complete, package into a distributable .skill file:

scripts/package_skill.py <path/to/skill-folder>

# Optional output directory
scripts/package_skill.py <path/to/skill-folder> ./dist

The packaging script will:

1. Validate the skill automatically (frontmatter, naming, structure)
2. Package if validation passes, creating a .skill file (zip format)

For quick validation without packaging:

scripts/quick_validate.py <path/to/skill-folder>

Step 6: Iterate

After testing the skill, users may request improvements.

Iteration workflow:

1. Use the skill on real tasks
2. Notice struggles or inefficiencies
3. Identify how SKILL.md or bundled resources should be updated
4. Implement changes and test again