claude/skills/skill-creator/SKILL.md
Guide for creating and iterating on skills — modular packages that extend Claude with specialized workflows, tool integrations, domain expertise, and bundled resources (scripts, references, assets). Use when: (1) creating a new skill from scratch ('create a skill for X', 'build a skill that does Y', 'I need a skill for Z'); (2) updating or improving an existing skill ('add a script to the foo skill', 'the bar skill is missing X', 'iterate on the baz skill'); (3) packaging a skill for distribution ('package the skill', 'generate a .skill file'); (4) understanding skill design patterns ('how should I structure this skill?', 'when should I use a script vs a reference?').
npx skillsauth add lanej/dotfiles skill-creatorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Skills are modular packages that extend Claude with specialized workflows, tool integrations, domain expertise, and bundled resources (scripts, references, assets). The context window is shared — only include what Claude doesn't already have, and match specificity to task fragility: high freedom for open-ended tasks, low freedom (specific scripts, few parameters) for fragile or error-prone sequences. For skill anatomy detail and progressive disclosure patterns, see references/design.md.
Skill creation involves these steps:
Follow these steps in order, skipping only if there is a clear reason why they are not applicable.
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:
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.
To turn concrete examples into an effective skill, analyze each example by:
Example: When building a pdf-editor skill to handle queries like "Help me rotate this PDF," the analysis shows:
scripts/rotate_pdf.py script would be helpful to store in the skillExample: 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:
assets/hello-world/ template containing the boilerplate HTML/React project files would be helpful to store in the skillExample: When building a big-query skill to handle queries like "How many users have logged in today?" the analysis shows:
references/schema.md file documenting the table schemas would be helpful to store in the skillTo establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.
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:
scripts/, references/, and assets/After initialization, customize or remove the generated SKILL.md and example files as needed.
When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Claude to use. Include 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.
Consult these helpful guides based on your skill's needs:
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/.
Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.
Any example files and directories not needed for the skill should be deleted. The initialization script creates example files in scripts/, references/, and assets/ to demonstrate structure, but most skills won't need all of them.
Writing Guidelines: Always use imperative/infinitive form.
Write the YAML frontmatter with name and description:
name: The skill namedescription: This is the primary triggering mechanism for your skill, and helps Claude understand when to use the skill.
docx skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when Claude needs to work 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"Do not include any other fields in YAML frontmatter.
Write instructions for using the skill and its bundled resources.
Skip this step if you are building a skill for your own use. Packaging is for distributing a skill to other users. If the skill lives in your own ~/.claude/skills/ or a project's .claude/skills/, work directly in that directory — no packaging needed.
Once development of the skill is complete and you need to distribute it, package it into a distributable .skill file. 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:
Validate the skill automatically, checking:
Package the skill if validation passes, creating a .skill file named after the skill (e.g., my-skill.skill) that includes all files and maintains the proper directory structure for distribution. The .skill file is a zip file with a .skill extension.
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.
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:
~/.claude/skills/skill-name/ or the project .claude/skills/ equivalent) — do not extract a zip to a temp directorydevops
DORA engineering metrics project at ~/src/dora. Load when: querying DORA BigQuery views (deployment frequency, lead time, change failure rate, alerts, review time) from any project; joining against DORA.unified_identity or DORA_clean.* views from any project; running the data pipeline (just refresh, just download-*, just upload-*); making OpenTofu infrastructure changes to DORA tables or views; working with team attribution, team identity, or engineer roster data.
development
Data pipeline architecture patterns and best practices, including medallion/three-layer architecture (Raw/Staging/Enriched or Bronze/Silver/Gold), YAML-based schema management, and ETL workflow patterns. Use when designing or implementing data pipelines, working with data warehouse layers, or managing table schemas in YAML.
data-ai
Delegate research and context-gathering tasks to a sub-agent to protect the primary context window. Use when the user asks to "research X", "look into X", "find out about X", "gather context on X", or any investigative framing where answering requires 2+ searches or multiple sources. Also use proactively before starting substantive work when prior context is unknown. Never run research inline — always delegate.
documentation
--- name: qmd-math description: Math notation conventions for Quarto/EPQ documents rendered via lualatex. Use when: writing or adding a formula, equation, or mathematical expression to a .qmd file; asked about display math, inline math, or LaTeX notation in a QMD/Quarto context; defining a where-clause or variable definitions for an equation; converting prose variable descriptions into structured math notation; fixing math that renders badly in a PDF; using \lvert, \begin{aligned}, \tfrac, \text