# Skill Creator

> Guide for creating effective skills. Use when creating, updating, restructuring, or validating a skill package with specialized workflows, knowledge, tool integrations, or bundled resources. Use `agent-instruction-writing` when editing the instruction text itself.

- Skill: `jmmarotta/skill-creator` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add jmmarotta/skill-creator`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jmmarotta/skill-creator/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: Complete terms in LICENSE.txt
- Author: jmmarotta (https://skillmd.com/u/jmmarotta)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/jmmarotta/skill-creator

---


# Skill Creator

This skill provides guidance for creating effective skills.

Use `agent-instruction-writing` for the wording quality of `SKILL.md`, `AGENTS.md`, and prompt text. This skill focuses on package structure, reusable resources, initialization, validation, and iteration.

## About Skills

Skills are modular, self-contained packages that extend an 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 agent equipped with
procedural knowledge that may not be present by default.

### 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

## Core Principles

### Concise Is Key

The context window is a public good. Skills share it with everything else the agent needs: system prompt, conversation history, other skills' metadata, and the actual user request.

**Default assumption: the agent is already capable.** Only add context it does not already have. Challenge each piece of information: "Is this explanation actually needed?" 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:

```text
skill-name/
├── SKILL.md (required)
│   ├── YAML frontmatter metadata (required)
│   │   ├── name: (required)
│   │   ├── description: (required)
│   │   ├── license: (optional)
│   │   ├── allowed-tools: (optional)
│   │   └── metadata: (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.)
```

#### SKILL.md (required)

Every `SKILL.md` consists of:

- **Frontmatter** (YAML): Contains `name` and `description` fields (required), plus optional fields like `license`, `allowed-tools`, and `metadata`. Only `name` and `description` are used to determine when the skill triggers, so be clear and comprehensive about 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.

#### 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 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 the agent should reference while working
- **Examples**: `references/finance.md` for financial schemas, `references/nda.md` for company templates, `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 it is actually needed
- **Best practice**: If files are large, include search hints or direct links in `SKILL.md`
- **Avoid duplication**: Information should live in either `SKILL.md` or reference files, not both. Prefer reference files for detailed information unless it is truly core to the skill.

##### 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 or 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 Not To 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`
- similar extra docs that do not directly help the agent do the work

The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxiliary context about the process that went into creating it, setup and testing procedures, or user-facing documentation unless those are truly part of the skill's job.

### Progressive Disclosure Design Principle

Skills use a three-level loading system to manage context efficiently:

1. **Metadata (name + description)** - Always in context
2. **SKILL.md body** - When the skill triggers
3. **Bundled resources** - As needed by the agent

#### Progressive Disclosure Patterns

Keep `SKILL.md` body to the essentials and split content into separate files when it becomes bulky. When splitting out content into other files, reference them from `SKILL.md` and describe clearly when to read 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 such as patterns, examples, and configuration into separate reference files.

**Pattern 1: High-level guide with references**

```markdown
# 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:

```text
bigquery-skill/
├── SKILL.md (overview and navigation)
└── references/
    ├── 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:

```text
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 and link to advanced content:

```markdown
# 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 long files, include a table of contents near the top so the agent can quickly see the full scope.

## Skill Creation Process

Skill creation involves these steps:

1. Understand the skill with concrete examples
2. Plan reusable skill contents (`scripts/`, `references/`, `assets/`)
3. Initialize the skill
4. Edit the skill
5. Validate the skill before sharing
6. 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?"

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 or React each time
2. An `assets/hello-world/` template containing the boilerplate 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 validation is needed. In this case, continue to the next step.

When creating a new skill from scratch, run the `init_skill.ts` script with Bun.

Usage:

```bash
bun skills/skill-creator/scripts/init_skill.ts <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 agent to use. Include information that would be beneficial and non-obvious. Consider what procedural knowledge, domain-specific details, or reusable assets would help another agent execute these tasks more effectively.

Use `agent-instruction-writing` when refining the actual instruction text in `SKILL.md`.

#### Learn Proven Design Patterns

Consult these 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

#### 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.

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 will not need all of them.

#### Update SKILL.md

**Writing guidelines:** Always use imperative or infinitive form.

##### Frontmatter

Write the YAML frontmatter with `name` and `description`.

- `name`: The skill name
- `description`: This is the primary triggering mechanism for your skill and helps the agent understand when to use it.
  - Include both what the skill does and specific triggers or contexts for when to use it.
  - Include all routing information here, not in the body. The body is only loaded after triggering.

Use optional frontmatter fields only when they are supported by the validator and materially useful.

##### Body

Write instructions for using the skill and its bundled resources. Keep the core workflow in `SKILL.md` and move bulky detail into `references/`.

### Step 5: Validate the Skill Before Sharing

Once development of the skill is complete, run the validator to confirm the skill is ready to share:

```bash
bun skills/skill-creator/scripts/quick_validate.ts <path/to/skill-folder>
```

The validator 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. Report success when validation passes.

If validation fails, the script will report the errors and exit with a non-zero status. Fix any validation errors and run the 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