skill-creator
About
The skill-creator helps developers build, modify, and audit modular skills for SwarmClaw agents. It is triggered for tasks like creating a new skill from scratch or improving, reviewing, and cleaning up existing skill files and directories. This skill provides specialized guidance for authoring effective skills that add workflows, tool integrations, and domain knowledge to agents.
Quick Install
Claude Code
Recommendednpx skills add swarmclawai/swarmclaw -a claude-code/plugin add https://github.com/swarmclawai/swarmclawgit clone https://github.com/swarmclawai/swarmclaw.git ~/.claude/skills/skill-creatorCopy and paste this command in Claude Code to install this skill
Documentation
Skill Creator
Guidance for creating effective skills that extend SwarmClaw agent capabilities.
About Skills
Skills are modular, self-contained packages that provide specialized knowledge, workflows, and tools. 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 shared resource. Only add context the agent doesn't already have. Challenge each piece of information: "Does the agent really need this explanation?" Prefer concise examples over verbose explanations.
Set Appropriate Degrees of Freedom
- High freedom (text instructions): Multiple valid approaches, context-dependent decisions
- Medium freedom (pseudocode/parameterized scripts): Preferred pattern exists, some variation OK
- Low freedom (specific scripts): Fragile operations, consistency critical, exact sequence required
Anatomy of a Skill
skill-name/
├── SKILL.md (required)
│ ├── YAML frontmatter (name + description, required)
│ └── Markdown instructions (required)
└── Bundled Resources (optional)
├── scripts/ — Executable code (Python/Bash/etc.)
├── references/ — Documentation loaded into context as needed
└── assets/ — Files used in output (templates, icons, fonts)
Frontmatter
name: Skill name (hyphen-case, lowercase)description: Primary triggering mechanism. Include what the skill does AND when to use it. All "when to use" info goes here — not in the body.
Scripts (scripts/)
Executable code for tasks that require deterministic reliability or are repeatedly rewritten. Token efficient and may be executed without loading into context.
References (references/)
Documentation loaded as needed to inform the agent's process. Keep only essential instructions in SKILL.md; move detailed reference material here.
Assets (assets/)
Files not loaded into context but used in output (templates, images, fonts). Separates output resources from documentation.
What NOT to Include
- README.md, CHANGELOG.md, INSTALLATION_GUIDE.md, or other auxiliary docs
- Setup/testing procedures or user-facing documentation
- Information the agent already knows from general training
Skill Creation Process
- Understand the skill with concrete examples
- Plan reusable contents (scripts, references, assets)
- Initialize the skill
- Edit the skill (implement resources, write SKILL.md)
- Validate the skill
- Iterate based on real usage
Skill Naming
- Lowercase letters, digits, and hyphens only (hyphen-case)
- Under 64 characters
- Prefer short, verb-led phrases describing the action
- Name the skill folder exactly after the skill name
Step 1: Understanding with Concrete Examples
Ask the user clarifying questions:
- What functionality should the skill support?
- Can you give examples of how it would be used?
- What would a user say that should trigger this skill?
Step 2: Planning Reusable Contents
Analyze each example to identify what scripts, references, and assets would be helpful:
- Repeated code →
scripts/(e.g.,scripts/rotate_pdf.py) - Boilerplate →
assets/(e.g.,assets/hello-world/template) - Domain knowledge →
references/(e.g.,references/schema.md)
Step 3: Initializing the Skill
Use the bundled init script to create the directory structure:
python3 {baseDir}/scripts/init_skill.py <skill-name> --path <output-directory> [--resources scripts,references,assets] [--examples]
Examples:
python3 {baseDir}/scripts/init_skill.py my-skill --path skills
python3 {baseDir}/scripts/init_skill.py my-skill --path skills --resources scripts,references
Step 4: Edit the Skill
Write instructions that would help another agent instance execute tasks effectively. Include information that is beneficial and non-obvious.
Writing guidelines: Use imperative/infinitive form. Keep SKILL.md body under 500 lines.
Frontmatter description: Include both what the skill does and specific triggers for when to use it. This is the primary mechanism for skill selection.
Step 5: Validate the Skill
Run the validator to check structure and frontmatter:
python3 {baseDir}/scripts/quick_validate.py <path/to/skill-folder>
Step 6: Iterate
- Use the skill on real tasks
- Notice struggles or inefficiencies
- Update SKILL.md or bundled resources
- Test again
Progressive Disclosure
Skills use a three-level loading system:
- Metadata (name + description) — always in context (~100 words)
- SKILL.md body — when skill triggers (<5k words)
- Bundled resources — as needed (unlimited, since scripts can be executed without reading)
Keep SKILL.md lean. Move detailed information to reference files and describe clearly when to read them.
GitHub Repository
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