skill-creator

name	skill-creator
description	Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
license	Complete terms in LICENSE.txt

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.

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.)

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 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

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.

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

EVOKORE Authoring Contract

Skills authored for EVOKORE-MCP must satisfy a stricter shape than the upstream Anthropic skill-creator template, because resolve_workflow performs semantic ranking over description and the static composition graph parses literal phrases out of SKILL.md bodies. The quick_validate.py script enforces these rules as failures — they are NOT downgradable warnings.

• Trigger-explicit description. The frontmatter description field must start with Use when ... (case-insensitive) or contain the substring when to use. Pure noun-phrase descriptions ("Browser automation tool") are rejected because they degrade resolve_workflow ranking.
• Verb + minimum length. The description must be at least 60 characters AND contain at least one verb (heuristic: a word ending in -ing or one of the verb allowlist in quick_validate.py).
• 5-second-decide H2. The skill body must contain an H2 heading ## When to use this skill within the first 30 lines after the closing frontmatter ---. A reader should be able to decide in 5 seconds whether the skill applies to their task — this section is the answer.
• Kebab-case naming. The name field is hyphen-case ([a-z0-9-]+, no leading/trailing/consecutive hyphens). Skill directory name must match.
• Composition phrasing. When this skill should chain into another skill, use the literal phrase format invoke X skill somewhere in SKILL.md. scripts/derive-skill-composition.js parses that phrase into the static skill graph, which powers nextSteps[] in execute_skill responses.
• Optional upstream: frontmatter. Skills ported from external sources (Anthropic Cookbook, mattpocock, third-party authors) MAY include an upstream: field in frontmatter recording the canonical source URL or repository. This is a forward-compatible field; do not depend on tooling that consumes it yet.

Baseline allowlist (deletion-only ratchet)

Skills that predate this lint are listed in baseline-allowlist.txt (one POSIX-style path per line). Listed paths fail the lint as warnings and exit 0; unlisted paths that fail still exit 1. The allowlist is enforced as deletion-only by the vitest suite — entries can be removed when fixed but not added.

To run the lint against a single skill with the allowlist applied:

python "SKILLS/DEVELOPER TOOLS/skill-creator/scripts/quick_validate.py" \\
    "SKILLS/path/to/skill" \\
    --against-allowlist "SKILLS/DEVELOPER TOOLS/skill-creator/baseline-allowlist.txt"

Adapter Skills

EVOKORE-MCP vendors selected third-party skill packs as read-only git submodules under SKILLS/upstream/<vendor>/. When porting one of those upstream skills into an EVOKORE consumable form, write an adapter SKILL.md in the appropriate EVOKORE category directory (e.g., SKILLS/DEVELOPER TOOLS/<skill-name>/SKILL.md) instead of editing the submodule. Submodules are immutable from this repo's perspective.

Adapter Frontmatter Fields

In addition to the standard name and description, adapter SKILL.md files include three provenance fields:

• upstream: — short slug <owner>/<repo> of the vendored upstream (e.g., mattpocock/skills).
• upstream-sha: — pinned commit SHA of the vendored submodule. Must match the SHA recorded in .gitmodules and the relevant SKILLS/upstream/UPSTREAM-*.md file.
• upstream-path: — relative path INSIDE the submodule pointing at the upstream skill body this adapter is derived from (e.g., zoom-out/SKILL.md).

When the submodule is bumped (see SKILLS/upstream/UPSTREAM-*.md for the upgrade procedure), every adapter whose upstream-sha: references the old SHA becomes stale and should be re-validated against the new upstream body.

Adapter Body Structure

Every adapter SKILL.md must include three sections (in addition to whatever procedural body the skill needs):

1. ## When to use this skill — 5-second-decide trigger summary. Lead with the trigger, not implementation details.
2. ## Adapted From Upstream — link or nav_read_anchor pointer at the upstream file, plus a one-line license credit (e.g., "License: MIT, Copyright (c) 2026 Matt Pocock; see repo-root NOTICE").
3. ## EVOKORE-Specific Adaptations — concrete delta vs upstream (collapsed user-loops, panel-of-experts substitutions, continuity-manifest wiring, native-tool replacements, etc.).

Scaffolding Template

Use the canonical adapter template at:

SKILLS/DEVELOPER TOOLS/skill-creator/templates/adapter-template.md

Copy it into the target category directory, rename to SKILL.md, and fill in the frontmatter and body placeholders. Do NOT modify files inside SKILLS/upstream/<vendor>/ — adapter bodies live exclusively in EVOKORE category directories.

NOTE: If the template file does not exist yet in your tree, the reference above is forward-looking — the lint and authoring contract above are the authoritative gates for adapter skills regardless.