skill-creator
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El creador de habilidades ayuda a los desarrolladores a construir, modificar y auditar habilidades modulares para los agentes de SwarmClaw. Se activa para tareas como crear una nueva habilidad desde cero o mejorar, revisar y limpiar archivos y directorios de habilidades existentes. Esta habilidad proporciona orientación especializada para crear habilidades efectivas que añaden flujos de trabajo, integraciones de herramientas y conocimiento del dominio a los agentes.
Instalación rápida
Claude Code
Recomendadonpx skills add swarmclawai/swarmclaw -a claude-code/plugin add https://github.com/swarmclawai/swarmclawgit clone https://github.com/swarmclawai/swarmclaw.git ~/.claude/skills/skill-creatorCopia y pega este comando en Claude Code para instalar esta habilidad
Documentación
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.
Repositorio GitHub
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