Skill Creator

Skill Creator

This skill provides guidance for creating effective skills.

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.

IMPORTANT:

• Skills are not documentation, they are practical instructions for Claude Code to use the tools, packages, plugins or APIs to achieve the tasks.
• Each skill teaches Claude how to perform a specific development task, not what a tool does.
• Claude Code can activate multiple skills automatically to achieve the user's request.

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:

.opencode/skills/
└── skill-name/
    ├── SKILL.md (required)
    │   ├── YAML frontmatter metadata (required)
    │   │   ├── name: (required)
    │   │   ├── description: (required)
    │   │   ├── license: (optional)
    │   │   └── version: (optional)
    │   └── 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.)

Requirements (IMPORTANT)

• Skill should be combined into specific topics, for example: cloudflare, cloudflare-r2, cloudflare-workers, docker, gcloud should be combined into devops
• SKILL.md should be less than 150 lines and include the references of related markdown files and scripts.
• Each script or referenced markdown file should be also less than 150 lines, remember that you can always split them into multiple files (progressive disclosure principle).
• Descriptions in metadata of SKILL.md files should be both concise (less than 200 characters) and still contains enough usecases of the references and scripts, this will help skills can be activated automatically during the implementation process of Claude Code.
• Referenced markdowns:
  • Sacrifice grammar for the sake of concision when writing these files.
  • Can reference other markdown files or scripts as well.
• Referenced scripts:
  • Prefer nodejs or python scripts instead of bash script, because bash scripts are not well-supported on Windows.
  • If you're going to write python scripts, make sure you have requirements.txt
  • Make sure scripts respect .env file follow this order: process.env > .opencode/skills/${SKILL}/.env > .opencode/skills/.env > .opencode/.env
  • Create .env.example files to show the required environment variables.
  • Always write tests for these scripts.

IMPORTANT:

• Always keep in mind that SKILL.md and reference files should be token consumption efficient, so that progressive disclosure can be leveraged at best.
• SKILL.md should be less than 150 lines
• Referenced markdown files should be also less than 150 lines, remember that you can always split them into multiple files (progressive disclosure principle).
• Referenced scripts: no limit on length, just make sure it works, no compile issues, no runtime issues, no dependencies issues, no environment issues, no platform issues.

Why? Better context engineering: leverage progressive disclosure technique of Agent Skills, when agent skills are activated, Claude Code will consider to load only relevant files into the context, instead of reading all long SKILL.md as before.

SKILL.md (required)

File name: SKILL.md (uppercase) File size: Under 150 lines, if you need more, split it to multiple files (<150 lines each) in references folder. SKILL.md is always short and concise, straight to the point, treat it as a quick reference guide.

Metadata Quality: The name and description (MUST be under 200 characters) in YAML frontmatter determine when Claude will use the skill. Be specific about what the skill does and when to use it, DO NOT sound generic, vague or educational. 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

IMPORTANT:

• Write tests for scripts.
• Run tests and make sure it works, if tests fail, fix them and run tests again, repeat until tests pass.
• Run scripts manually with some usecases to make sure it works.
• Make sure scripts respect .env file follow this order: process.env > .opencode/skills/docs-seeker/.env > .opencode/skills/.env > .opencode/.env

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, best practices, common workflows, cheatsheets, tool instructions, API documentation, domain knowledge, company policies, detailed workflow guides
• Benefits: Keeps SKILL.md lean, loaded only when Claude determines it's needed, makes information discoverable without hogging the context window.
• Best practice: If files are large (>150 lines), split them into multiple files (<150 lines each) in references folder, 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.

IMPORTANT:

• Referenced markdown files should be also less than 150 lines, remember that you can always split them into multiple files (progressive disclosure principle).
• Referenced markdown files are practical instructions for Claude Code to use the tools, packages, plugins or APIs to achieve the tasks.
• Each skill teaches Claude how to perform a specific development task, not what a tool does.

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 (less than 200 characters)
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 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.

Use AskUserQuestion tool to gather user feedback and validate understanding.

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: Research on The Internet

An effective skill is a subset of real-life workflows from professional workflows and case studies, so it's important to research on the internet to understand the current state of the art and best practices.

Activate /docs-seeker skill to search for documentation if needed.

If you receive a lot of URLs or files, use multiple WebFetch tools and Explore subagents to explore them in parallel, then report back to main agent.

Activate /research skill to research for:

• Best practices & industry standards
• Existing CLI tools (executable via npx, bunx or pipx) and their usage patterns
• Workflows & success case studies
• Common patterns, use cases & examples
• Edge cases, potential pitfalls & avoidance strategies

Write down the reports from the research to be used in the next step.

Step 3: Planning the Reusable Skill Contents

To turn concrete examples into an effective skill, analyze each example by:

1. Considering how to execute on the example from scratch
2. Prefer existing CLI tools' execution (via npx, bunx or pipx) over writing custom code
3. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly
4. Analyze the current skills catalog to avoid duplicating functionality, re-using existing skills where possible.

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.

• Make sure scripts respect .env file follow this order: process.env > .opencode/skills/docs-seeker/.env > .opencode/skills/.env > .opencode/.env
• Make sure scripts have tests, run all tests and ensure they pass. DO NOT SKIP THIS STEP.

Step 4: 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 5: 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.

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 (MUST be under 200 characters)
   • 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. Notice token usage and performance
4. Identify how SKILL.md or bundled resources should be updated
5. Implement changes and test again

Validation Criteria

Detailed validation criteria for evaluating skills:

• Quick checklist: references/validation-checklist.md
• Metadata quality: references/metadata-quality-criteria.md
• Token efficiency: references/token-efficiency-criteria.md
• Script quality: references/script-quality-criteria.md
• Structure & organization: references/structure-organization-criteria.md

References

• Agent Skills
• Agent Skills Spec
• Agent Skills Overview
• Best Practices