Skill: chengxindl/skills-ttt (version 1.0.1)

--- name: skill-creator description: "Guide for creating effective skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Use this skill when the user asks to: (1) create a new skill, (2) make a skill, (3) build a skill, (4) set up a skill, (5) initialize a skill, (6) scaffold a skill, (7) update or modify an existing skill, (8) validate a skill, (9) learn about skill structure, (10) understand how skills work, or (11) get guidance on skill design patterns. Trigger on phrases like \"create a skill\", \"new skill\", \"make a skill\", \"skill for X\", \"how do I create a skill\", or \"help me build a skill\"." --- # Skill Creator This skill provides guidance for creating effective skills. ## About Skills Skills are modular, self-contained packages that extend agent 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 and domain expertise. ### Skill Location for Deepagents In deepagents CLI, skills are stored in `~/.deepagents/<agent>/skills/` where `<agent>` is your agent configuration name (default is `agent`). For example, with the default configuration, skills live at: ``` ~/.deepagents/agent/skills/ ├── skill-name-1/ │ └── SKILL.md ├── skill-name-2/ │ └── SKILL.md └── ... ``` ### 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 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 capable.** Only add context the agent 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 (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. These are the only fields that 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 (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 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 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: 1. **Metadata (name + description)** - Always in context (~100 words) 2. **SKILL.md body** - When skill triggers (<5k words) 3. **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** ```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: ``` 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: ```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 files longer than 100 lines, include a table of contents at the top so the agent can see the full scope when previewing. ## 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 (run init_skill.py) 4. Edit the skill (implement resources and write SKILL.md) 5. Validate the skill (run quick_validate.py) 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/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: ```bash scripts/init_skill.py <skill-name> --path <output-directory> ``` For deepagents CLI, use the agent's skills directory: ```bash scripts/init_skill.py <skill-name> --path ~/.deepagents/agent/skills ``` 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 an agent 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 the agent 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 name - `description`: 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. - 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 working 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. ##### Body Write instructions for using the skill and its bundled resources. ### Step 5: Validate the Skill Once development of the skill is complete, validate it to ensure it meets all requirements: ```bash scripts/quick_validate.py <path/to/skill-folder> ``` The validation script checks: - YAML frontmatter format and required fields - Skill naming conventions (hyphen-case, max 64 characters) - Description completeness (no angle brackets, max 1024 characters) - Required fields: `name` and `description` - Allowed frontmatter properties only: `name`, `description`, `license`, `allowed-tools`, `metadata` If validation fails, fix the reported errors and run the validation 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

path: scripts/init_skill.py
content: #!/usr/bin/env python3
"""Skill Initializer - Creates a new skill from template.

Usage:
 init_skill.py <skill-name> --path <path>

Examples:
 init_skill.py my-new-skill --path skills/public
 init_skill.py my-api-helper --path skills/private
 init_skill.py custom-skill --path /custom/location

For deepagents CLI:
 init_skill.py my-skill --path ~/.deepagents/agent/skills
"""

import sys
from pathlib import Path

SKILL_TEMPLATE = """---
name: {skill_name}
description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
---

# {skill_title}

## Overview

[TODO: 1-2 sentences explaining what this skill enables]

## Structuring This Skill

[TODO: Choose the structure that best fits this skill's purpose. Common patterns:

**1. Workflow-Based** (best for sequential processes)
- Works well when there are clear step-by-step procedures
- Example: DOCX skill with "Workflow Decision Tree" → "Reading" → "Creating" → "Editing"
- Structure: ## Overview → ## Workflow Decision Tree → ## Step 1 → ## Step 2...

**2. Task-Based** (best for tool collections)
- Works well when the skill offers different operations/capabilities
- Example: PDF skill with "Quick Start" → "Merge PDFs" → "Split PDFs" → "Extract Text"
- Structure: ## Overview → ## Quick Start → ## Task Category 1 → ## Task Category 2...

**3. Reference/Guidelines** (best for standards or specifications)
- Works well for brand guidelines, coding standards, or requirements
- Example: Brand styling with "Brand Guidelines" → "Colors" → "Typography" → "Features"
- Structure: ## Overview → ## Guidelines → ## Specifications → ## Usage...

**4. Capabilities-Based** (best for integrated systems)
- Works well when the skill provides multiple interrelated features
- Example: Product Management with "Core Capabilities" → numbered capability list
- Structure: ## Overview → ## Core Capabilities → ### 1. Feature → ### 2. Feature...

Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).

Delete this entire "Structuring This Skill" section when done - it's just guidance.]

## [TODO: Replace with the first main section based on chosen structure]

[TODO: Add content here. See examples in existing skills:
- Code samples for technical skills
- Decision trees for complex workflows
- Concrete examples with realistic user requests
- References to scripts/templates/references as needed]

## Resources

This skill includes example resource directories that demonstrate how to organize different types of bundled resources:

### scripts/
Executable code (Python/Bash/etc.) that can be run directly to perform specific operations.

**Examples from other skills:**
- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation
- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing

**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.

**Note:** Scripts may be executed without loading into context, but can still be read by Claude for patching or environment adjustments.

### references/
Documentation and reference material intended to be loaded into context to inform Claude's process and thinking.

**Examples from other skills:**
- Product management: `communication.md`, `context_building.md` - detailed workflow guides
- BigQuery: API reference documentation and query examples
- Finance: Schema documentation, company policies

**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Claude should reference while working.

### assets/
Files not intended to be loaded into context, but rather used within the output Claude produces.

**Examples from other skills:**
- Brand styling: PowerPoint template files (.pptx), logo files
- Frontend builder: HTML/React boilerplate project directories
- Typography: Font files (.ttf, .woff2)

**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.

---

**Any unneeded directories can be deleted.** Not every skill requires all three types of resources.
"""  # noqa: E501

EXAMPLE_SCRIPT = '''#!/usr/bin/env python3
"""
Example helper script for {skill_name}

This is a placeholder script that can be executed directly.
Replace with actual implementation or delete if not needed.

Example real scripts from other skills:
- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields
- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images
"""

def main():
    print("This is an example script for {skill_name}")
    # TODO: Add actual script logic here
    # This could be data processing, file conversion, API calls, etc.

if __name__ == "__main__":
    main()
'''

EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title}

This is a placeholder for detailed reference documentation.
Replace with actual reference content or delete if not needed.

Example real reference docs from other skills:
- product-management/references/communication.md - Comprehensive guide for status updates
- product-management/references/context_building.md - Deep-dive on gathering context
- bigquery/references/ - API references and query examples

## When Reference Docs Are Useful

Reference docs are ideal for:
- Comprehensive API documentation
- Detailed workflow guides
- Complex multi-step processes
- Information too lengthy for main SKILL.md
- Content that's only needed for specific use cases

## Structure Suggestions

### API Reference Example
- Overview
- Authentication
- Endpoints with examples
- Error codes
- Rate limits

### Workflow Guide Example
- Prerequisites
- Step-by-step instructions
- Common patterns
- Troubleshooting
- Best practices
"""

EXAMPLE_ASSET = """# Example Asset File

This placeholder represents where asset files would be stored.
Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed.

Asset files are NOT intended to be loaded into context, but rather used within
the output Claude produces.

Example asset files from other skills:
- Brand guidelines: logo.png, slides_template.pptx
- Frontend builder: hello-world/ directory with HTML/React boilerplate
- Typography: custom-font.ttf, font-family.woff2
- Data: sample_data.csv, test_dataset.json

## Common Asset Types

- Templates: .pptx, .docx, boilerplate directories
- Images: .png, .jpg, .svg, .gif
- Fonts: .ttf, .otf, .woff, .woff2
- Boilerplate code: Project directories, starter files
- Icons: .ico, .svg
- Data files: .csv, .json, .xml, .yaml

Note: This is a text placeholder. Actual assets can be any file type.
"""


def title_case_skill_name(skill_name):
    """Convert hyphenated skill name to Title Case for display."""
    return " ".join(word.capitalize() for word in skill_name.split("-"))


def init_skill(skill_name, path):
    """Initialize a new skill directory with template SKILL.md.

    Args:
        skill_name: Name of the skill
        path: Path where the skill directory should be created

    Returns:
        Path to created skill directory, or None if error
    """
    # Determine skill directory path
    skill_dir = Path(path).resolve() / skill_name

    # Check if directory already exists
    if skill_dir.exists():
        print(f"❌ Error: Skill directory already exists: {skill_dir}")
        return None

    # Create skill directory
    try:
        skill_dir.mkdir(parents=True, exist_ok=False)
        print(f"✅ Created skill directory: {skill_dir}")
    except Exception as e:
        print(f"❌ Error creating directory: {e}")
        return None

    # Create SKILL.md from template
    skill_title = title_case_skill_name(skill_name)
    skill_content = SKILL_TEMPLATE.format(skill_name=skill_name, skill_title=skill_title)

    skill_md_path = skill_dir / "SKILL.md"
    try:
        skill_md_path.write_text(skill_content)
        print("✅ Created SKILL.md")
    except Exception as e:
        print(f"❌ Error creating SKILL.md: {e}")
        return None

    # Create resource directories with example files
    try:
        # Create scripts/ directory with example script
        scripts_dir = skill_dir / "scripts"
        scripts_dir.mkdir(exist_ok=True)
        example_script = scripts_dir / "example.py"
        example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))
        example_script.chmod(0o755)
        print("✅ Created scripts/example.py")

        # Create references/ directory with example reference doc
        references_dir = skill_dir / "references"
        references_dir.mkdir(exist_ok=True)
        example_reference = references_dir / "api_reference.md"
        example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))
        print("✅ Created references/api_reference.md")

        # Create assets/ directory with example asset placeholder
        assets_dir = skill_dir / "assets"
        assets_dir.mkdir(exist_ok=True)
        example_asset = assets_dir / "example_asset.txt"
        example_asset.write_text(EXAMPLE_ASSET)
        print("✅ Created assets/example_asset.txt")
    except Exception as e:
        print(f"❌ Error creating resource directories: {e}")
        return None

    # Print next steps
    print(f"\n✅ Skill '{skill_name}' initialized successfully at {skill_dir}")
    print("\nNext steps:")
    print("1. Edit SKILL.md to complete the TODO items and update the description")
    print("2. Customize or delete the example files in scripts/, references/, and assets/")
    print("3. Run the validator when ready to check the skill structure")

    return skill_dir


def main():
    if len(sys.argv) < 4 or sys.argv[2] != "--path":
        print("Usage: init_skill.py <skill-name> --path <path>")
        print("\nSkill name requirements:")
        print(" - Hyphen-case identifier (e.g., 'data-analyzer')")
        print(" - Lowercase letters, digits, and hyphens only")
        print(" - Max 40 characters")
        print(" - Must match directory name exactly")
        print("\nExamples:")
        print(" init_skill.py my-new-skill --path skills/public")
        print(" init_skill.py my-api-helper --path skills/private")
        print(" init_skill.py custom-skill --path /custom/location")
        print("\nFor deepagents CLI:")
        print(" init_skill.py my-skill --path ~/.deepagents/agent/skills")
        sys.exit(1)

    skill_name = sys.argv[1]
    path = sys.argv[3]

    print(f"🚀 Initializing skill: {skill_name}")
    print(f"   Location: {path}")
    print()

    result = init_skill(skill_name, path)

    if result:
        sys.exit(0)
    else:
        sys.exit(1)


if __name__ == "__main__":
    main()


path: scripts/quick_validate.py
content: #!/usr/bin/env python3
"""Quick validation script for skills - minimal version.

For deepagents CLI, skills are located at:
~/.deepagents/<agent>/skills/<skill-name>/

Example:
 python quick_validate.py ~/.deepagents/agent/skills/my-skill
"""

import re
import sys
from pathlib import Path

import yaml


def validate_skill(skill_path):
    """Basic validation of a skill"""
    skill_path = Path(skill_path)

    # Check SKILL.md exists
    skill_md = skill_path / "SKILL.md"
    if not skill_md.exists():
        return False, "SKILL.md not found"

    # Read and validate frontmatter
    content = skill_md.read_text()
    if not content.startswith("---"):
        return False, "No YAML frontmatter found"

    # Extract frontmatter
    match = re.match(r"^---\n(.*?)\n---", content, re.DOTALL)
    if not match:
        return False, "Invalid frontmatter format"

    frontmatter_text = match.group(1)

    # Parse YAML frontmatter
    try:
        frontmatter = yaml.safe_load(frontmatter_text)
        if not isinstance(frontmatter, dict):
            return False, "Frontmatter must be a YAML dictionary"
    except yaml.YAMLError as e:
        return False, f"Invalid YAML in frontmatter: {e}"

    # Define allowed properties
    ALLOWED_PROPERTIES = {"name", "description", "license", "allowed-tools", "metadata"}

    # Check for unexpected properties (excluding nested keys under metadata)
    unexpected_keys = set(frontmatter.keys()) - ALLOWED_PROPERTIES
    if unexpected_keys:
        return False, (
            f"Unexpected key(s) in SKILL.md frontmatter: {', '.join(sorted(unexpected_keys))}. "
            f"Allowed properties are: {', '.join(sorted(ALLOWED_PROPERTIES))}"
        )

    # Check required fields
    if "name" not in frontmatter:
        return False, "Missing 'name' in frontmatter"
    if "description" not in frontmatter:
        return False, "Missing 'description' in frontmatter"

    # Extract name for validation
    name = frontmatter.get("name", "")
    if not isinstance(name, str):
        return False, f"Name must be a string, got {type(name).__name__}"
    name = name.strip()
    if name:
        # Check naming convention (hyphen-case: lowercase with hyphens)
        if not re.match(r"^[a-z0-9-]+$", name):
            return (
                False,
                f"Name '{name}' should be hyphen-case (lowercase letters, digits, and hyphens only)",
            )
        if name.startswith("-") or name.endswith("-") or "--" in name:
            return (
                False,
                f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens",
            )
        # Check name length (max 64 characters per spec)
        if len(name) > 64:
            return False, f"Name is too long ({len(name)} characters). Maximum is 64 characters."

    # Extract and validate description
    description = frontmatter.get("description", "")
    if not isinstance(description, str):
        return False, f"Description must be a string, got {type(description).__name__}"
    description = description.strip()
    if description:
        # Check for angle brackets
        if "<" in description or ">" in description:
            return False, "Description cannot contain angle brackets (< or >)"
        # Check description length (max 1024 characters per spec)
        if len(description) > 1024:
            return (
                False,
                f"Description is too long ({len(description)} characters). Maximum is 1024 characters.",
            )

    return True, "Skill is valid!"


if __name__ == "__main__":
    if len(sys.argv) != 2:
        print("Usage: python quick_validate.py <skill_directory>")
        sys.exit(1)

    valid, message = validate_skill(sys.argv[1])
    print(message)
    sys.exit(0 if valid else 1)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)