skill-creator

name	skill-creator
description	Orchestrator skill for creating effective skills. Guides through 6 steps - understanding examples, planning contents with scope assessment, initialization, editing with contracts, packaging, and iteration. Use when creating a new skill or updating an existing skill.
skill_type	orchestrator
license	Complete terms in LICENSE.txt

Skill Creator

This skill provides guidance for creating effective skills.

Contract

Inputs:

• User request to create or update a skill
• Domain knowledge or examples of how the skill will be used
• (Optional) Existing skill directory if updating

Outputs:

• Complete skill directory with SKILL.md and optional resources
• Validated and packaged skill (if packaging requested)

Success Criteria:

• Skill has valid SKILL.md with frontmatter (name, description, skill_type)
• Contract section defines inputs, outputs, success criteria
• Skill type (atomic/orchestrator) is appropriate for scope
• Bundled resources (scripts, references, assets) support the skill's purpose

About Skills

Skills are modular, self-contained packages that extend Claude's capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform Claude from 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

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.)

Naming Convention

Skill names use category prefixes for organization. The prefix indicates the skill's domain.

Prefix	Category	Examples
db-	Database	db-postgres, db-sqlite
auth-	Authentication	auth-better-auth, auth-lucia
infra-	Infrastructure & deployment	infra-railway, infra-docker, infra-env
ui-	Frontend & design	ui-design-system, ui-principles
state-	State management	state-effector, state-tanstack
tools-	External integrations	tools-linear, tools-email, tools-youtube
secrets-	Secrets management	secrets-1password
(none)	Core workflow skills	feature-build, skill-creator, judge

Framework skills use the framework name first: nextjs-16, react-19

Naming rules:

• Lowercase with hyphens: my-skill-name
• Category prefix when applicable
• Specific enough to be discoverable
• Max 40 characters

SKILL.md (required)

Metadata Quality: The name and description in YAML frontmatter determine when Claude will use the skill. Be specific about what the skill does and when to use it. Use the third-person (e.g. "This skill should be used when..." instead of "Use this skill when...").

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 Claude for patching or environment-specific adjustments

References (references/)

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

• When to include: For documentation that Claude should reference while working
• Examples: references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specifications
• Use cases: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
• Benefits: Keeps SKILL.md lean, loaded only when Claude 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. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.

Assets (assets/)

Files not intended to be loaded into context, but rather used within the output Claude 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, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typography
• Use cases: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
• Benefits: Separates output resources from documentation, enables Claude to use files without loading them into context

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 Claude (Unlimited*)

*Unlimited because scripts can be executed without reading into context window.

Skill Scope Assessment (For Complex Skills)

For most simple skills, skip this section - just build what you need. For complex workflows, consider whether the skill should be atomic or an orchestrator.

Atomic Skills

Atomic skills do ONE thing well with clear boundaries. They:

• Complete a single, focused task
• Receive minimum viable context (only what's needed for the task)
• Produce a defined output
• Execute statelessly (no accumulated context between invocations)
• Do not coordinate with or reference other skills

Examples: db-postgres, auth-better-auth, email-resend, docker-local

Orchestrator Skills

Orchestrator skills coordinate multiple phases or compose atomic skills. They:

• Break complex work into discrete steps
• Delegate to atomic skills or phases
• Manage workflow state through external mechanisms (files, git)
• May loop back to earlier phases based on results

Examples: feature-build, project-setup

Assessment Questions

To determine skill type, ask:

1. Does the skill have 3+ distinct phases? → Likely an orchestrator
2. Does the skill reference or invoke other skills? → Likely an orchestrator
3. Can the skill complete in one focused session? → Likely atomic
4. Does the skill need project-wide context? → Consider splitting or making it an orchestrator

Design Principle

Complexity belongs in orchestration, not in individual skills.

Atomic skills that try to do too much become brittle and hard to compose. When in doubt, split into smaller atomic skills and create an orchestrator to coordinate them.

For detailed patterns on composing skills, see references/orchestration-patterns.md.

Skill Creation Process

To create a skill, follow the "Skill Creation Process" in order, skipping steps only if there is a clear reason why they are not applicable.

Step 1: Understanding the Skill with Concrete Examples

Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.

To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.

For example, when building an image-editor skill, relevant questions include:

• "What functionality should the image-editor skill support? Editing, rotating, anything else?"
• "Can you give some examples of how this skill would be used?"
• "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?"
• "What would a user say that should trigger this skill?"

To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.

Conclude this step when there is a clear sense of the functionality the skill should support.

Step 2: Planning the Reusable Skill Contents

Before diving into implementation details, assess the skill's scope:

1. Is this a single focused task or a multi-step workflow?

   • Single task → Design as atomic skill
   • Multi-step workflow → Either split into atomic skills OR design as explicit orchestrator

2. If multi-step, can the phases be executed independently?

   • Yes → Create separate atomic skills + orchestrator to compose them
   • No → Design as orchestrator with clear phase boundaries

To turn concrete examples into an effective skill, 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 to handle queries like "Help me rotate this PDF," the analysis shows:

1. Rotating a PDF requires re-writing the same code each time
2. A scripts/rotate_pdf.py script would be helpful to store in the skill

Example: When designing a frontend-webapp-builder skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:

1. Writing a frontend webapp requires the same boilerplate HTML/React each time
2. An assets/hello-world/ template containing the boilerplate HTML/React project files would be helpful to store in the skill

Example: When building a big-query skill to handle queries like "How many users have logged in today?" the analysis shows:

1. Querying BigQuery requires re-discovering the table schemas and relationships each time
2. A references/schema.md file documenting the table schemas would be helpful to store in the skill

To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.

Step 3: Initializing the Skill

At this point, it is time to actually create the skill.

Skip this step only if the skill being developed already exists, and iteration or packaging is needed. In this case, continue to the next step.

When creating a new skill from scratch, always run the init_skill.py script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.

Usage:

scripts/init_skill.py <skill-name> --path <output-directory>

The script:

• Creates the skill directory at the specified path
• Generates a SKILL.md template with proper frontmatter and TODO placeholders
• Creates example resource directories: scripts/, references/, and assets/
• Adds example files in each directory that can be customized or deleted

After initialization, customize or remove the generated SKILL.md and example files as needed.

Step 4: Edit the Skill

When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Claude to use. Focus on including information that would be beneficial and non-obvious to Claude. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Claude instance execute these tasks more effectively.

Start with Reusable Skill Contents

To begin implementation, start with the reusable resources identified above: scripts/, references/, and assets/ files. Note that this step may require user input. For example, when implementing a brand-guidelines skill, the user may need to provide brand assets or templates to store in assets/, or documentation to store in references/.

Also, delete any example files and directories not needed for the skill. The initialization script creates example files in scripts/, references/, and assets/ to demonstrate structure, but most skills won't need all of them.

Update SKILL.md

Writing Style: Write the entire skill using imperative/infinitive form (verb-first instructions), not second person. Use objective, instructional language (e.g., "To accomplish X, do Y" rather than "You should do X" or "If you need to do X"). This maintains consistency and clarity for AI consumption.

To complete SKILL.md, answer the following questions:

1. What is the purpose of the skill, in a few sentences?
2. When should the skill be used?
3. In practice, how should Claude use the skill? All reusable skill contents developed above should be referenced so that Claude knows how to use them.

Add a Contract Section (Optional - For Complex Skills)

For multi-phase workflows or skills that will be composed with others, consider adding a Contract section that defines clear boundaries:

## Contract

**Inputs:**
- [What the skill needs to begin - files, context, user input]

**Outputs:**
- [What the skill produces when complete]

**Success Criteria:**
- [ ] [Testable condition that indicates successful completion]

When to add a contract:

• Orchestrator skills with multiple phases
• Skills that will be invoked by other orchestrators
• Complex workflows where handoff points matter

When to skip:

• Simple, single-purpose skills (e.g., "format SQL", "generate commit message")
• Personal productivity skills with obvious scope
• Skills where the description already makes boundaries clear

Step 5: Packaging a Skill

Once the skill is ready, it should be packaged into a distributable zip file that gets shared with the user. The packaging process automatically validates the skill first to ensure it meets all requirements:

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

Optional output directory specification:

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

The packaging script will:

1. Validate the skill automatically, checking:

   • YAML frontmatter format and required fields
   • Skill naming conventions and directory structure
   • Description completeness and quality
   • File organization and resource references

2. Package the skill if validation passes, creating a zip file named after the skill (e.g., my-skill.zip) that includes all files and maintains the proper directory structure for distribution.

If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again.

Step 6: Iterate

After testing the skill, users may request improvements. Often this happens right after using the skill, with fresh context of how the skill performed.

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