Skill Forge
Generate complete, production-ready skills for any domain with optimal architecture and all required resources.
Core Capability
Skill Forge transforms skill requests into complete, validated, distributable .skill packages by:
- •Intelligent requirement analysis - Extract skill purpose, triggers, workflows, and resource needs
- •Optimal architecture design - Determine appropriate freedom levels, resource structure, and patterns
- •Complete resource generation - Create scripts, references, assets, and comprehensive SKILL.md
- •Automatic validation - Ensure all requirements met before packaging
- •Distributable packaging - Generate ready-to-use .skill files
When to Use Skill Forge
Trigger when users request:
- •"Make me a skill for [domain/task]"
- •"Create a skill that does [functionality]"
- •"I need a skill to help with [workflow]"
- •"Generate a [topic] skill"
- •Any request to create, design, or improve a skill
Skill Generation Workflow
Phase 1: Understand Requirements
Goal: Extract clear examples of how the skill will be used.
Ask targeted questions to understand:
- •Functionality: What should this skill do? What are the main tasks?
- •Triggers: What would a user say to invoke this skill?
- •Context: Who will use it? What's their expertise level?
- •Examples: "Can you give 3-5 concrete examples of queries this skill should handle?"
- •Constraints: Any specific requirements, formats, or limitations?
Avoid overwhelming users - Ask 2-3 questions max per message, prioritize most important.
Conclude when: You have 3-5 concrete usage examples and understand the scope.
Phase 2: Analyze Architecture
Goal: Design optimal skill structure and identify all required resources.
For each concrete example, determine:
- •
Workflow complexity:
- •Simple (single operation) → Concise instructions
- •Medium (multi-step) → Sequential workflow with checkpoints
- •Complex (branching logic) → Conditional workflow with decision trees
- •
Required resources:
- •Scripts (
scripts/): Repeated code, deterministic operations, fragile processes - •References (
references/): Schemas, API docs, domain knowledge, examples - •Assets (
assets/): Templates, boilerplate, images, fonts, sample files
- •Scripts (
- •
Freedom level:
- •High freedom: Multiple valid approaches, context-dependent decisions
- •Medium freedom: Preferred patterns with some flexibility
- •Low freedom: Fragile operations requiring specific sequences
- •
Progressive disclosure needs:
- •Core workflow in SKILL.md (<500 lines)
- •Detailed references in separate files
- •Optional resources loaded as needed
Output: Complete architectural plan listing all resources to generate.
Phase 3: Generate Skill Resources
Order of generation:
- •Create bundled resources first (scripts/references/assets)
- •Write SKILL.md last (after understanding all resources)
Generate Scripts (scripts/)
Create Python/Bash scripts for:
- •Repeated operations (same code written multiple times)
- •Deterministic tasks requiring exact execution
- •Complex algorithms or data processing
- •Fragile operations prone to errors
Script requirements:
- •Executable and tested
- •Clear docstrings and comments
- •Proper error handling
- •Command-line friendly (argparse for Python)
Example: For PDF rotation skill, create scripts/rotate_pdf.py
Generate References (references/)
Create reference files for:
- •Database schemas and relationships
- •API documentation and endpoints
- •Domain-specific knowledge
- •Detailed examples and patterns
- •Company policies or guidelines
Reference file principles:
- •Structured and scannable (headers, lists, tables)
- •Include search keywords for easy grep
- •Avoid duplication with SKILL.md
- •Load only when needed
Example: For BigQuery skill, create references/schema.md with table schemas
Generate Assets (assets/)
Create asset files for:
- •Templates to copy or modify
- •Boilerplate code structures
- •Brand assets (logos, fonts, colors)
- •Sample documents or files
- •Static resources used in output
Asset principles:
- •Not loaded into context
- •Used in final output
- •Ready to copy/modify
- •Organized by type
Example: For webapp skill, create assets/react-template/ with boilerplate React project
Generate SKILL.md
Create comprehensive SKILL.md with:
Frontmatter (YAML):
--- name: skill-name description: Complete description including WHAT the skill does and WHEN to use it. Include all triggers, contexts, and use cases here since body loads only after triggering. Examples: "Use when user requests X", "Triggers include Y", "Handles Z tasks". ---
Body (Markdown):
- •Overview - Brief capability summary
- •Core workflow - Main process or steps
- •Resource usage - How to use bundled scripts/references/assets
- •Examples - Concrete input/output demonstrations
- •Advanced patterns - Optional techniques or variations
- •References to external files - When to load each reference
Writing principles:
- •Concise (challenge every paragraph's token cost)
- •Imperative/infinitive form ("Use X" not "You should use X")
- •Examples over explanations
- •Keep under 500 lines (split to references if longer)
- •Assume Claude is smart (don't over-explain)
Progressive disclosure:
- •Essential workflow in SKILL.md
- •Detailed guidance in references
- •Variants in separate files
Phase 4: Validate & Package
- •
Run validation using
scripts/quick_validate.py:- •YAML frontmatter format
- •Required name and description fields
- •Skill naming conventions
- •Directory structure
- •Description completeness
- •Resource references
- •
Package skill using
scripts/package_skill.py:- •Creates
skill-name.skillfile (zip with .skill extension) - •Includes all files and directory structure
- •Ready for distribution
- •Creates
- •
Provide to user:
- •Link to download .skill file
- •Brief usage instructions
- •Trigger phrase examples
Best Practices by Skill Type
Technical Integration Skills
Examples: API clients, file format processors, database tools
Key resources:
- •
scripts/for API wrappers and processing logic - •
references/for API documentation, schemas, endpoints - •Minimal SKILL.md focused on workflow
Pattern:
# API Integration Workflow 1. Authenticate (use scripts/auth.py) 2. Fetch data (use scripts/fetch.py) 3. Process response (see references/schema.md) 4. Transform output
Domain Expertise Skills
Examples: Finance, legal, medical, industry-specific
Key resources:
- •
references/for domain knowledge, terminology, frameworks - •
assets/for templates and examples - •Detailed SKILL.md with decision trees
Pattern:
# Domain Analysis Workflow 1. Identify document type (see references/types.md) 2. Apply framework (see references/framework.md) 3. Generate output using template (assets/template.docx)
Multi-Step Workflow Skills
Examples: Report generation, data pipelines, content creation
Key resources:
- •
scripts/for each major step - •
references/for examples and quality standards - •Clear sequential workflow in SKILL.md
Pattern:
# Workflow Steps 1. Gather inputs (run scripts/gather.py) 2. Process data (run scripts/process.py) 3. Generate output (run scripts/generate.py) 4. Validate result (run scripts/validate.py)
Creative Content Skills
Examples: Writing, design, content generation
Key resources:
- •
references/for style guides, examples, voice/tone - •
assets/for templates, brand assets - •Template pattern in SKILL.md
Pattern:
# Content Creation Follow brand voice in references/voice.md Use templates from assets/templates/ Examples in references/examples.md
Skill Generation Checklist
Before finalizing any skill, verify:
- • Frontmatter has
nameand completedescriptionwith triggers - • Description includes WHEN to use the skill (all triggers)
- • SKILL.md under 500 lines (or split appropriately)
- • All scripts are tested and executable
- • References are well-structured and scannable
- • Assets are ready to use in output
- • No README.md or extraneous documentation
- • Progressive disclosure used appropriately
- • Examples demonstrate key functionality
- • Validation passes (
quick_validate.py) - • Package created successfully (
package_skill.py)
Advanced Patterns
Multi-Framework Skills
When skill supports multiple frameworks/variations:
SKILL.md:
# Core Workflow 1. Choose framework (see references/frameworks.md) 2. Follow framework-specific guide ## Framework Selection - React → See references/react.md - Vue → See references/vue.md - Angular → See references/angular.md
Each framework guide in separate reference file.
Conditional Workflows
For branching logic:
# Workflow 1. Determine task type: **Creating new?** → Creation workflow (below) **Modifying existing?** → Modification workflow (below) **Analyzing?** → Analysis workflow (below) ## Creation Workflow [Steps for creation] ## Modification Workflow [Steps for modification] ## Analysis Workflow [Steps for analysis]
Template-Based Skills
For consistent output:
# Output Format ALWAYS use this structure: # [Title] ## Executive Summary [One paragraph] ## Key Findings - Finding 1 with data - Finding 2 with data ## Recommendations 1. Actionable recommendation 2. Actionable recommendation
Use "ALWAYS" for strict requirements, "suggested format" for flexible guidance.
Common Anti-Patterns to Avoid
❌ Don't:
- •Create README.md, CHANGELOG.md, or auxiliary docs
- •Duplicate content between SKILL.md and references
- •Over-explain basic concepts Claude already knows
- •Use first-person language ("I will" or "You should")
- •Create single-purpose skills that could be general-purpose
- •Include setup instructions or testing procedures
- •Make SKILL.md longer than 500 lines without splitting
✅ Do:
- •Keep SKILL.md focused on essential workflow
- •Use imperative form ("Use", "Run", "Follow")
- •Trust Claude's intelligence
- •Split detailed content to references
- •Design for reusability across contexts
- •Focus on procedural knowledge Claude doesn't have
- •Test all scripts before finalizing
Iteration & Improvement
After generating a skill:
- •Test with real queries - Try actual use cases
- •Identify friction points - Where does Claude struggle?
- •Analyze root cause - Missing resource? Unclear instructions? Wrong pattern?
- •Update resources - Modify scripts, references, or SKILL.md
- •Re-validate and package - Ensure improvements work
- •Document learnings - Note patterns for future skills
Using Skill Forge Effectively
For users:
- •Provide 3-5 concrete usage examples
- •Specify expertise level of end users
- •Share any existing templates, docs, or code
- •Indicate must-haves vs nice-to-haves
For Skill Forge:
- •Ask targeted questions (2-3 max per message)
- •Generate complete resources, not just outlines
- •Test scripts before including them
- •Validate before packaging
- •Provide clear usage instructions with .skill file
Skill Generation Speed Patterns
Quick skills (10 min):
- •Simple domain knowledge
- •No scripts needed
- •Light references
- •Template-based output
Medium skills (30 min):
- •2-4 scripts
- •Multiple references
- •Asset templates
- •Multi-step workflows
Complex skills (60+ min):
- •5+ scripts
- •Extensive references
- •Asset libraries
- •Conditional workflows
- •Framework variations
Set expectations based on complexity.
Script Tools
Use the initialization and packaging scripts from skill-creator:
Initialize new skill:
/mnt/skills/examples/skill-creator/scripts/init_skill.py <skill-name> --path <output-dir>
Validate skill:
/mnt/skills/examples/skill-creator/scripts/quick_validate.py <skill-directory>
Package skill:
/mnt/skills/examples/skill-creator/scripts/package_skill.py <skill-directory> [output-dir]
Example: Complete Skill Generation
User request: "Make me a skill for analyzing financial reports"
Phase 1: Requirements Q: "What types of financial reports? (10-K, earnings, balance sheets, all?)" Q: "What analysis do you need? (ratios, trends, comparisons, recommendations?)" Q: "Any specific output format requirements?"
Phase 2: Architecture
- •Workflow: Sequential (load → analyze → generate report)
- •Scripts: None needed (analysis is context-dependent)
- •References:
references/financial-ratios.md,references/analysis-framework.md,references/report-examples.md - •Assets:
assets/report-template.md - •Freedom: High (analysis varies by report type)
Phase 3: Generate
- •Create
references/financial-ratios.mdwith ratio definitions and formulas - •Create
references/analysis-framework.mdwith step-by-step analysis approach - •Create
references/report-examples.mdwith sample analyses - •Create
assets/report-template.mdwith output structure - •Write
SKILL.mdwith workflow and resource references
Phase 4: Validate & Package
- •Run
quick_validate.py→ Pass - •Run
package_skill.py→ Generatefinancial-analysis.skill - •Provide download link and usage examples
Summary
Skill Forge generates complete, production-ready skills by:
- •Understanding requirements through targeted questions
- •Designing optimal architecture based on patterns
- •Generating all resources (scripts, references, assets)
- •Creating comprehensive SKILL.md
- •Validating and packaging for distribution
Every generated skill follows best practices, leverages progressive disclosure, and focuses on the essential procedural knowledge that makes Claude effective at specialized tasks.