skill-creator

name

skill-creator

description

Comprehensive guide for creating effective GitHub Copilot skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Use when asked to: create/make/build/scaffold/initialize a new skill, update/modify an existing skill, validate a skill, learn about skill structure, understand how skills work, or get guidance on skill design patterns. Triggers on phrases like "create a skill", "new skill", "make a skill", "skill for X", "how do I create a skill", or "help me build a skill". Use when this capability is needed.

Skill Creator

A comprehensive guide for creating effective skills that extend GitHub Copilot agent capabilities through specialized knowledge, workflows, and tool integrations.

About Skills

Skills are modular, self-contained packages that transform a general-purpose agent into a specialized agent equipped with procedural knowledge and domain expertise. Think of them as "onboarding guides" for specific domains or tasks.

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

When to Use This Skill

• User asks to "create a skill", "make a new skill", or "scaffold a skill"
• User wants to add specialized capabilities to their GitHub Copilot setup
• User needs help structuring a skill with bundled resources
• User wants to update or validate an existing skill
• User needs guidance on skill design patterns

Core Principles

1. Concise is Key

The context window is a public good shared with system prompts, conversation history, and user requests.

Default assumption: The agent is already very capable. Only add context the agent 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.

Token budgets for frequently-used skills:

• Very frequently loaded skills (like common workflows): Target <500 words (~2-3 pages)
• Frequently loaded skills: Target <1000 words (~4-5 pages)
• Specialized skills: Can be longer but stay under 500 lines total

If your skill exceeds these targets, use progressive disclosure with references/ and templates/ directories.

2. Set Appropriate Degrees of Freedom

Match specificity to the task's fragility and variability:

• High freedom (text instructions): Multiple valid approaches, context-dependent decisions
• Medium freedom (pseudocode/parameterized scripts): Preferred patterns with acceptable variation
• Low freedom (specific scripts): Fragile operations requiring exact sequences

3. Progressive Disclosure

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 (<500 lines)
3. Bundled resources - As needed by the agent (loaded on demand)

Keep SKILL.md under 500 lines. Split content into separate reference files when approaching this limit.

When to move content out of SKILL.md:

• API documentation → references/api.md
• Comprehensive examples → references/examples.md
• Schema definitions → references/schema.md
• Starter code/boilerplate → templates/
• Long reference tables → references/

Keep in SKILL.md:

• Core principles and workflow
• When to use / when NOT to use
• Quick reference (single table/list)
• One excellent minimal example
• Links to detailed references

Skill Anatomy

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 loaded into context as needed
    ├── assets/           - Files used in output (templates, icons, fonts)
    └── templates/        - Starter code the agent modifies

What NOT to Include

Do NOT create extraneous documentation:

• ❌ README.md
• ❌ INSTALLATION_GUIDE.md
• ❌ QUICK_REFERENCE.md
• ❌ CHANGELOG.md

The skill should only contain information needed for an AI agent to do the job.

Skill Creation Process

Follow these steps in order:

Step 1: Understand with Concrete Examples

Ask users for specific examples of how the skill will be used:

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

Conclude when you have a clear sense of the functionality needed.

Step 2: Plan Reusable Contents

Analyze each example to identify helpful resources:

• What scripts would prevent rewriting the same code?
• What references would provide needed schemas/documentation?
• What assets would provide reusable templates/boilerplate?

Step 3: Create Skill Directory

Create a new folder with a lowercase, hyphenated name:

skills/<skill-name>/
└── SKILL.md          # Required

Step 4: Write SKILL.md

Frontmatter Requirements

Every SKILL.md requires YAML frontmatter:

---
name: <skill-name>
description: '<What it does>. Use when <specific triggers, scenarios, keywords>.'
---

Field	Required	Constraints
name	Yes	1-64 chars, lowercase letters/numbers/hyphens, matches folder name
description	Yes	1-1024 chars, describes WHAT it does AND WHEN to use it
license	No	License name or reference to LICENSE.txt
compatibility	No	1-500 chars, environment requirements
metadata	No	Key-value pairs for additional properties
allowed-tools	No	Space-delimited list of pre-approved tools (experimental)

Description Best Practices

CRITICAL: The description is the PRIMARY triggering mechanism. Include:

1. WHAT the skill does (capabilities)
2. WHEN to use it (triggers, scenarios, file types)
3. Keywords users might mention in prompts

Good example:

description: 'Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when working with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks.'

Poor example:

description: 'Document helpers'

Body Structure

Writing Guidelines: Always use imperative/infinitive form.

Recommended sections:

# Title

Brief overview of what the skill does.

## When to Use This Skill

Reinforces description triggers with more detail.

## Prerequisites

Required tools, dependencies, environment setup.

## Step-by-Step Workflows

Numbered steps for common tasks.

## Troubleshooting

Common issues and solutions.

## References

Links to bundled documentation files.

Step 5: Add Bundled Resources (If Needed)

Scripts (scripts/)

Executable code for deterministic reliability or repeatedly rewritten tasks.

When to include: Same code being rewritten repeatedly or deterministic reliability needed

Example: scripts/rotate_pdf.py for PDF rotation

Benefits: Token efficient, deterministic, may execute without loading into context

References (references/)

Documentation loaded into context to inform the agent's process.

When to include: For documentation the agent should reference while working

Examples:

• references/schema.md - Database schemas
• references/api_docs.md - API specifications
• references/policies.md - Company policies

Best practice: If files are large (>10k words), include search patterns in SKILL.md

Progressive Disclosure Patterns:

Pattern 1: High-level guide with references

## Advanced features

- **Form filling**: See [FORMS.md](references/FORMS.md)
- **API reference**: See [REFERENCE.md](references/REFERENCE.md)
- **Examples**: See [EXAMPLES.md](references/EXAMPLES.md)

Pattern 2: Domain-specific organization

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

Pattern 3: Framework/variant organization

cloud-deploy/
├── SKILL.md (workflow + provider selection)
└── references/
    ├── aws.md (AWS deployment patterns)
    ├── gcp.md (GCP deployment patterns)
    └── azure.md (Azure deployment patterns)

Guidelines:

• Avoid deeply nested references (keep one level deep from SKILL.md)
• For files >100 lines, include table of contents at top
• Information should live in SKILL.md OR references, not both

Assets (assets/)

Files used in the agent's output, not loaded into context.

When to include: Files needed in final output

Examples:

• assets/logo.png - Brand assets
• assets/template.pptx - PowerPoint templates
• assets/frontend-template/ - HTML/React boilerplate
• assets/font.ttf - Typography

Templates (templates/)

Starter code the agent modifies and extends.

When to include: Scaffolds that need customization

Examples:

• templates/starter.ts - TypeScript project scaffold
• templates/component.tsx - React component template

Step 6: Validate the Skill

Ensure the skill meets all requirements:

Validation Checklist:

• Folder name is lowercase with hyphens
• name field matches folder name exactly
• description is 10-1024 characters
• description explains WHAT and WHEN
• description is wrapped in single quotes
• Body content is under 500 lines
• For frequently-used skills: SKILL.md under 500 words (check with wc -w)
• For very common skills: SKILL.md under 500 words with heavy content in references/
• Long examples, API docs, or schemas moved to references/
• No extraneous files (README.md, etc.)
• Bundled assets are under 5MB each
• Scripts are tested and working
• References are properly linked from SKILL.md

Step 7: Iterate

After testing the skill:

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

Complete Example Structure

my-awesome-skill/
├── SKILL.md                    # Required instructions
├── LICENSE.txt                 # Optional license file
├── scripts/
│   └── helper.py               # Executable automation
├── references/
│   ├── api-reference.md        # Detailed docs
│   └── examples.md             # Usage examples
├── assets/
│   └── diagram.png             # Static resources
└── templates/
    └── starter.ts              # Code scaffold

Troubleshooting

Issue	Solution
Skill not discovered	Improve description with more keywords and triggers
Validation fails on name	Ensure lowercase, no consecutive hyphens, matches folder
Description too short	Add capabilities, triggers, and keywords
Assets not found	Use relative paths from skill root
Skill triggers too often	Make description more specific to use cases
Skill never triggers	Add common user phrases to description
SKILL.md too long	Split detailed content into references/ files
Context bloat	Move examples and API docs to references/
Frequently-used skill too long	Split into SKILL.md (<500 words) + references/, aim for minimal overview
Word count too high	Use wc -w SKILL.md to check; move detailed content to references/

Quick Reference: Frontmatter Template

---
name: your-skill-name
description: 'Brief capability summary. Use when [trigger 1], [trigger 2], or [specific scenario]. Supports [file types/frameworks].'
---

Key Takeaways

1. Description is critical - It's the primary triggering mechanism
2. Keep SKILL.md concise - Under 500 lines; frequently-used skills under 500 words
3. Progressive disclosure - Load only what's needed when needed; move API docs, examples, schemas to references/
4. Token efficiency matters - Every word in a frequently-loaded skill costs tokens in every conversation
5. Test bundled scripts - Ensure they actually work before including
6. Avoid duplication - Information lives in SKILL.md OR references, not both
7. No extraneous docs - Only files needed for AI agent to do the job
8. Iterate based on usage - Improve after real-world testing

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