| name | skill-creator |
| description | Guide for creating effective skills. Use when users want to create a new skill (or update an existing skill) that extends the agent's capabilities with specialized knowledge, workflows, or tool integrations. Also use when setting up, installing, or configuring skill installation (setup.sh, symlinks, copy to .agents). Triggers: create skill, new skill, skill setup, setup skill, install skill, настроить скил, создать скил, сетап скила, установить скил, скил креатор.
|
Skill Creator
This skill provides guidance for creating effective skills.
About Skills
Skills are modular, self-contained packages that extend the agent's capabilities by providing
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
domains or tasks—they transform a general-purpose agent into a specialized one
equipped with procedural knowledge that no model can fully possess.
What Skills Provide
- Specialized workflows - Multi-step procedures for specific domains
- Tool integrations - Instructions for working with specific file formats or APIs
- Domain expertise - Company-specific knowledge, schemas, business logic
- Bundled resources - Scripts, references, and assets for complex and repetitive tasks
Core Principles
Concise is Key
The context window is a public good. Skills share the context window with everything else the agent needs: system prompt, conversation history, other Skills' metadata, and the actual user request.
Default assumption: the agent is already very smart. Only add context it 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.
Set Appropriate Degrees of Freedom
Match the level of specificity to the task's fragility and variability:
High freedom (text-based instructions): Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.
Medium freedom (pseudocode or scripts with parameters): Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.
Low freedom (specific scripts, few parameters): Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.
Think of the agent as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).
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 (Bash/etc.)
├── references/ - Documentation intended to be loaded into context as needed
└── assets/ - Files used in output (templates, icons, fonts, etc.)
SKILL.md (required)
Every SKILL.md consists of:
- Frontmatter (YAML): Contains
name and description fields. These are the only fields the agent reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.
- Body (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).
Bundled Resources (optional)
Scripts (scripts/)
Executable code (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.sh for PDF rotation tasks
- Benefits: Token efficient, deterministic, may be executed without loading into context
- Note: Scripts may still need to be read by the agent for patching or environment-specific adjustments
References (references/)
Documentation and reference material intended to be loaded as needed into context to inform the agent's process and thinking.
- When to include: For documentation that the agent 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 the agent 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 the agent 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 the agent to use files without loading them into context
What to Not Include in a Skill
A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
- README.md
- INSTALLATION_GUIDE.md
- QUICK_REFERENCE.md
- CHANGELOG.md
- etc.
The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxilary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.
Progressive Disclosure Design Principle
Skills use a three-level loading system to manage context efficiently:
- Metadata (name + description) - Always in context (~100 words)
- SKILL.md body - When skill triggers (<5k words)
- Bundled resources - As needed by the agent (Unlimited because scripts can be executed without reading into context window)
Progressive Disclosure Patterns
Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.
Key principle: When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.
Pattern 1: High-level guide with references
# PDF Processing
## Quick start
Extract text with pdfplumber:
[code example]
## Advanced features
- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns
The agent loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.
Pattern 2: Domain-specific organization
For Skills with multiple domains, organize content by domain to avoid loading irrelevant context:
bigquery-skill/
├── SKILL.md (overview and navigation)
└── reference/
├── finance.md (revenue, billing metrics)
├── sales.md (opportunities, pipeline)
├── product.md (API usage, features)
└── marketing.md (campaigns, attribution)
When a user asks about sales metrics, the agent only reads sales.md.
Similarly, for skills supporting multiple frameworks or variants, organize by variant:
cloud-deploy/
├── SKILL.md (workflow + provider selection)
└── references/
├── aws.md (AWS deployment patterns)
├── gcp.md (GCP deployment patterns)
└── azure.md (Azure deployment patterns)
When the user chooses AWS, the agent only reads aws.md.
Pattern 3: Conditional details
Show basic content, link to advanced content:
# DOCX Processing
## Creating documents
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).
## Editing documents
For simple edits, modify the XML directly.
**For tracked changes**: See [REDLINING.md](REDLINING.md)
**For OOXML details**: See [OOXML.md](OOXML.md)
The agent reads REDLINING.md or OOXML.md only when the user needs those features.
Important guidelines:
- Avoid deeply nested references - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.
- Structure longer reference files - For files longer than 100 lines, include a table of contents at the top so the agent can see the full scope when previewing.
- Use unordered lists - Always prefer unordered lists (
-) over numbered lists (1.). Numbered lists are harder to maintain — adding/removing/reordering items requires renumbering. Exception: when order truly matters for correctness (e.g., step must come before another).
Skill Creation Process
Skill creation involves these steps (in order):
- Understand the skill with concrete examples
- Plan reusable skill contents (scripts, references, assets)
- Initialize the skill (run init-skill.sh)
- Edit the skill (implement resources and write SKILL.md)
- Package the skill (run package-skill.sh)
- Iterate based on real usage
Follow these steps in order, skipping 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?"
- "What languages will you use this skill in?" (e.g. English only, Russian, mixed)
On trigger languages: A skill with only English triggers will NOT activate when the user speaks another language. This is a common failure mode. Always ask about target languages, then ensure frontmatter description and any external trigger configs include terms in all of them.
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:
- Considering how to execute on the example from scratch
- 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:
- Rotating a PDF requires re-writing the same code each time
- A
scripts/rotate-pdf.sh 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:
- Writing a frontend webapp requires the same boilerplate HTML/React each time
- 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:
- Querying BigQuery requires re-discovering the table schemas and relationships each time
- 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.
Skill Location Patterns
Two deployment models: project-local skills and standalone skill repos.
Project-Local Skills
For skills that live inside a project (not reusable across projects):
project/
agents/skills/<skill-name>/ ← source of truth (visible in Finder)
.claude/skills/<skill-name> ← symlink → ../../agents/skills/<skill-name>
.codex/skills/<skill-name> ← symlink → ../../agents/skills/<skill-name>
Setup:
mkdir -p agents/skills/<skill-name> .claude/skills .codex/skills
ln -s ../../agents/skills/<skill-name> .claude/skills/<skill-name>
ln -s ../../agents/skills/<skill-name> .codex/skills/<skill-name>
Why: agents/skills/ is visible in Finder (no dot prefix), serves as single source of truth, and symlinks wire it up for compatible agents.
Standalone Skill Repos (Global Skills)
For reusable skills distributed as separate git repos. The installation pattern:
~/src/skill-<name>/ ← development repo (edit here)
setup.sh ← runs install: copy + symlink
~/.agents/skills/<name>/ ← INSTALLED COPY (not a symlink!)
~/.claude/skills/<name> ← symlink → ~/.agents/skills/<name>
~/.codex/skills/<name> ← symlink → ~/.agents/skills/<name>
Key rule: ~/.agents/skills/<name>/ is a copy (via rsync), not a symlink to the src repo. This ensures agents don't break if the src repo is moved, rebased, or on a broken branch.
setup.sh handles everything — copy to .agents, create symlinks:
#!/usr/bin/env bash
set -euo pipefail
SKILL_NAME="<skill-name>"
SKILL_DIR="$(cd "$(dirname "$0")" && pwd)"
AGENTS_DIR="$HOME/.agents/skills"
CLAUDE_DIR="$HOME/.claude/skills"
CODEX_DIR="$HOME/.codex/skills"
echo "Installing skill: $SKILL_NAME"
if [ -L "$AGENTS_DIR/$SKILL_NAME" ]; then
rm -f "$AGENTS_DIR/$SKILL_NAME"
fi
mkdir -p "$AGENTS_DIR/$SKILL_NAME"
rsync -a --delete "$SKILL_DIR/" "$AGENTS_DIR/$SKILL_NAME/" \
--exclude='.git' --exclude='setup.sh'
echo " Copied -> $AGENTS_DIR/$SKILL_NAME/"
mkdir -p "$CLAUDE_DIR"
rm -f "$CLAUDE_DIR/$SKILL_NAME"
ln -s "$AGENTS_DIR/$SKILL_NAME" "$CLAUDE_DIR/$SKILL_NAME"
mkdir -p "$CODEX_DIR"
rm -f "$CODEX_DIR/$SKILL_NAME"
ln -s "$AGENTS_DIR/$SKILL_NAME" "$CODEX_DIR/$SKILL_NAME"
echo "Done. Installed $(git -C "$SKILL_DIR" describe --tags --always 2>/dev/null || echo 'unknown')"
Workflow: edit in src repo → run setup.sh → updated copy in .agents → agents pick up changes.
For skills with binaries (Go CLI tools, etc.), setup.sh also builds binaries and symlinks to ~/.local/bin/ before the skill copy step. See skill-project-management/scripts/setup.sh for example.
Using init-skill.sh
When creating a new skill from scratch, run the init-skill.sh script to scaffold the directory structure.
Usage:
scripts/init-skill.sh <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
scripts/, references/, and assets/ directories
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 agent instance to use. Include information that would be beneficial and non-obvious to the agent. Consider what procedural knowledge, domain-specific details, or reusable assets would help another agent instance execute these tasks more effectively.
Learn Proven Design Patterns
Consult these helpful guides based on your skill's needs:
- Multi-step processes: See references/workflows.md for sequential workflows and conditional logic
- Specific output formats or quality standards: See references/output-patterns.md for template and example patterns
These files contain established best practices for effective skill design.
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/.
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.
Update SKILL.md
Writing Guidelines: Always use imperative/infinitive form.
Frontmatter
Write the YAML frontmatter with name and description:
name: The skill namedescription: This is the primary triggering mechanism for your skill, and helps the agent understand when to use the skill.
- Include both what the Skill does and specific triggers/contexts for when to use it.
- Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to the agent.
- Multi-language triggers: If the skill will be used in non-English languages, include key trigger terms in those languages directly in the description. The description is always in context — if it only contains English terms, the agent won't match it against non-English user input. Also update any external trigger configs (e.g.
INSTRUCTIONS_SKILL_TRIGGERS.md) if the project uses one.
- Example description for a
docx skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when the agent 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.
Strict requirements:
- Frontmatter must be the very first content in
SKILL.md (line 1 is exactly ---).
- Frontmatter must be closed by a second
--- before any markdown heading.
- Do not place a title/header before frontmatter.
- Description must be a YAML string. Use a folded block (
description: >) for long text.
- If description contains punctuation like
: and you use one-line style, quote it.
Use this exact safe template:
---
name: your-skill-name
description: >
What this skill does and exactly when to use it.
---
Do not include any other fields in SKILL.md frontmatter unless explicitly required by platform policy.
Body
Write instructions for using the skill and its bundled resources.
Language
All skills must be written in English. This ensures:
- Consistent tooling and script compatibility
- Broader reusability across projects and teams
- Standard terminology for technical concepts
Step 5: Packaging a Skill
Once development of the skill is complete, package it into a distributable .skill file. The script validates first, then zips:
scripts/package-skill.sh <path/to/skill-folder>
scripts/package-skill.sh <path/to/skill-folder> ./dist
Standalone validation:
scripts/validate-skill.sh <path/to/skill-folder>
Validates: frontmatter format, required fields, naming conventions, body length. If validation fails, fix errors and re-run.
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:
- Use the skill on real tasks
- Notice struggles or inefficiencies
- Identify how SKILL.md or bundled resources should be updated
- Implement changes and test again
