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    jackspace

    skill-harvester

    jackspace/skill-harvester
    Coding
    8

    About

    SKILL.md

    Install

    Install via Skills CLI

    or add to your agent
    • Claude Code
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    ├─
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    About

    Meta-skill for extracting and creating reusable Claude Code skills from past work sessions...

    SKILL.md

    Skill Harvester

    Transform your past work into reusable Claude Code skills automatically.

    Overview

    The Skill Harvester is a meta-skill that helps you systematically extract reusable patterns, workflows, and expertise from your Claude Code sessions and convert them into well-structured skills that can be shared and reused.

    When to Use

    Use this skill when:

    • Completing a significant project or work session
    • Identifying repetitive patterns across multiple sessions
    • Building organizational knowledge repositories
    • Creating team-wide skill libraries
    • Documenting complex workflows for future reuse
    • Converting infrastructure/tooling expertise into skills
    • After solving complex problems that could help future work

    Skill Harvesting Process

    1. Reflection & Analysis

    Examine recent work:

    # Review recent git commits
    git log --oneline -20
    
    # Analyze file changes
    git diff HEAD~10..HEAD --stat
    
    # Check which files were most modified
    git log --pretty=format: --name-only | sort | uniq -c | sort -rg | head -20
    

    Identify domains:

    • What technologies were used? (frameworks, languages, tools)
    • What problems were solved? (deployment, testing, optimization)
    • What patterns emerged? (error handling, API integration, workflow)
    • What expertise was developed? (domain knowledge, best practices)

    2. Skill Identification

    Questions to ask:

    1. Reusability: Could this help in future projects?
    2. Generalizability: Does it apply beyond this specific context?
    3. Complexity: Is it non-trivial enough to warrant a skill?
    4. Value: Would others benefit from this pattern?
    5. Completeness: Can it be documented as a standalone skill?

    Skill categories to consider:

    • Infrastructure: Docker, Kubernetes, cloud platforms, CI/CD
    • Backend: API design, database optimization, authentication
    • Frontend: Component patterns, state management, build optimization
    • DevOps: Deployment strategies, monitoring, automation
    • Data Engineering: ETL pipelines, data validation, transformation
    • Security: Auth patterns, encryption, vulnerability scanning
    • Testing: Test strategies, mocking, coverage analysis
    • Documentation: API docs, architecture diagrams, runbooks

    3. Skill Template Creation

    Essential components of a good skill:

    ---
    name: skill-name (kebab-case)
    description: Clear, concise 1-2 sentence description of what the skill does
    license: MIT
    tags: [relevant, searchable, tags]
    ---
    
    # Skill Title
    
    Brief overview paragraph explaining the skill's purpose and value.
    
    ## When to Use
    
    - Specific scenario 1
    - Specific scenario 2
    - Specific scenario 3
    
    ## Core Concepts
    
    Explain the fundamental ideas and principles.
    
    ## Workflow
    
    Step-by-step process for using the skill.
    
    ### Step 1: [Action]
    Detailed explanation with code examples.
    
    ### Step 2: [Action]
    More details and examples.
    
    ## Common Patterns
    
    ### Pattern 1: [Name]
    Description and example.
    
    ### Pattern 2: [Name]
    Description and example.
    
    ## Best Practices
    
    ### ✅ DO
    - Recommended approach 1
    - Recommended approach 2
    
    ### ❌ DON'T
    - Anti-pattern 1
    - Anti-pattern 2
    
    ## Examples
    
    ### Example 1: [Scenario]
    Full working example with explanation.
    
    ### Example 2: [Scenario]
    Another complete example.
    
    ## Troubleshooting
    
    ### Issue 1: [Problem]
    **Symptoms**: What you see
    **Cause**: Why it happens
    **Solution**: How to fix
    
    ## Reference
    
    Quick reference table or cheat sheet.
    
    ## Additional Resources
    
    - Links to relevant documentation
    - Related skills
    - External references
    

    4. Content Extraction

    Extract from various sources:

    # From code files
    # Look for:
    # - Complex functions that solve specific problems
    # - Utility scripts with general applicability
    # - Configuration patterns that work well
    # - Error handling strategies
    # - Integration patterns
    
    # From documentation
    # Harvest:
    # - README instructions
    # - Setup guides
    # - Troubleshooting notes
    # - Architecture decisions
    # - Lessons learned
    
    # From git commits
    git log --all --grep="fix\|feat\|refactor" --pretty=format:"%h %s" -20
    
    # From issue trackers
    # Extract:
    # - Common problems and solutions
    # - Debugging strategies
    # - Workarounds and fixes
    

    5. Skill Organization

    Directory structure:

    harvestable_skills/
    ├── automation/
    │   ├── skill-name/
    │   │   └── skill.md
    ├── backend/
    ├── devops/
    ├── frontend/
    ├── infrastructure/
    ├── testing/
    └── documentation/
    

    Categorization guidelines:

    • automation: Workflow automation, scripting, batch operations
    • backend: Server-side development, APIs, databases
    • cloud: Cloud platforms, serverless, infrastructure
    • data-engineering: Data processing, ETL, analytics
    • devops: CI/CD, deployment, monitoring
    • documentation: Documentation generation, diagrams
    • frontend: UI development, client-side frameworks
    • infrastructure: Container orchestration, VMs, networking
    • security: Authentication, authorization, encryption
    • testing: Test frameworks, strategies, automation
    • web-development: Full-stack web development patterns

    Harvesting Strategies

    Strategy 1: Domain Expertise Extraction

    When you've worked extensively with a specific tool or technology:

    1. Document the mental model: How does it work? What are the key concepts?
    2. Capture common operations: What do you do most often?
    3. Record gotchas: What are the common pitfalls?
    4. Create quick reference: What do you always look up?

    Example domains:

    • Database query optimization
    • Docker multi-stage builds
    • JWT authentication patterns
    • GraphQL schema design
    • Terraform module creation

    Strategy 2: Workflow Pattern Extraction

    When you've developed an effective workflow:

    1. Map the steps: What's the sequence of actions?
    2. Identify decision points: Where are choices made?
    3. Document prerequisites: What's needed to start?
    4. Capture success criteria: How do you know it worked?

    Example workflows:

    • Blue-green deployments
    • Feature branch review process
    • Database migration strategies
    • API versioning approaches

    Strategy 3: Problem-Solution Pattern Mining

    When you've solved complex problems:

    1. Describe the problem: What was broken/missing?
    2. Explain the diagnosis: How did you identify it?
    3. Detail the solution: What fixed it?
    4. Generalize the pattern: How to prevent/solve similar issues?

    Example patterns:

    • Memory leak debugging
    • Race condition resolution
    • Performance bottleneck analysis
    • Security vulnerability patching

    Strategy 4: Tool Mastery Documentation

    When you've become proficient with a tool:

    1. Core operations: What are the essential commands?
    2. Advanced features: What are the power-user tricks?
    3. Integration patterns: How does it work with other tools?
    4. Troubleshooting: Common errors and fixes?

    Example tools:

    • kubectl for Kubernetes
    • AWS CLI for cloud operations
    • jq for JSON processing
    • git for version control

    Automation Helpers

    Bulk Skill Generation

    #!/bin/bash
    # bulk-harvest.sh - Generate multiple skills from a list
    
    SKILLS_FILE="$1"
    OUTPUT_DIR="harvestable_skills"
    
    while IFS='|' read -r category name description; do
        # Skip header and empty lines
        [[ "$category" == "Category" ]] && continue
        [[ -z "$category" ]] && continue
    
        SKILL_DIR="$OUTPUT_DIR/$category/$name"
        mkdir -p "$SKILL_DIR"
    
        cat > "$SKILL_DIR/skill.md" << EOF
    ---
    name: $name
    description: $description
    license: MIT
    ---
    
    # ${name//\-/ }
    
    $description
    
    ## When to Use
    
    TODO: Add specific scenarios
    
    ## Implementation
    
    TODO: Add implementation details
    
    ## Examples
    
    TODO: Add working examples
    
    ## Best Practices
    
    TODO: Add recommendations
    EOF
    
        echo "✓ Created: $category/$name"
    done < "$SKILLS_FILE"
    

    Usage:

    # Create skills-to-harvest.txt
    cat > skills-to-harvest.txt << EOF
    Category|Name|Description
    devops|docker-layer-optimization|Optimize Docker image layers for faster builds and smaller images
    backend|api-rate-limiting|Implement rate limiting for API endpoints with Redis
    testing|snapshot-testing|Create and manage snapshot tests for UI components
    EOF
    
    ./bulk-harvest.sh skills-to-harvest.txt
    

    Git History Analysis

    #!/bin/bash
    # analyze-work.sh - Analyze recent work for harvestable patterns
    
    echo "=== Most Modified Files ==="
    git log --since="1 month ago" --pretty=format: --name-only | \
        sort | uniq -c | sort -rg | head -20
    
    echo ""
    echo "=== Technologies Used ==="
    git log --since="1 month ago" --pretty=format:"%s" | \
        grep -oE "(docker|kubernetes|terraform|ansible|python|node|react|vue|postgres|redis|mongodb)" | \
        sort | uniq -c | sort -rg
    
    echo ""
    echo "=== Common Commit Themes ==="
    git log --since="1 month ago" --pretty=format:"%s" | \
        grep -oE "^(feat|fix|refactor|docs|test|chore)" | \
        sort | uniq -c | sort -rg
    
    echo ""
    echo "=== Recent Problem Areas ==="
    git log --since="1 month ago" --all --grep="fix\|bug\|issue" --pretty=format:"%h %s" | head -10
    

    Quality Checklist

    Before publishing a harvested skill, ensure:

    Completeness:

    • Clear, descriptive name (kebab-case)
    • Concise description (1-2 sentences)
    • "When to Use" section with specific scenarios
    • Core concepts explained
    • Step-by-step workflow
    • At least 2 working examples
    • Best practices (DO and DON'T)
    • Troubleshooting section
    • Quick reference or cheat sheet

    Quality:

    • Examples are copy-pasteable and work
    • Code is well-commented
    • Explanations are clear and concise
    • Covers common edge cases
    • Includes error handling
    • Performance considerations mentioned
    • Security implications addressed
    • Links to official documentation

    Usefulness:

    • Solves a real problem
    • Applicable to multiple scenarios
    • More efficient than starting from scratch
    • Includes domain expertise
    • Provides actionable guidance

    Organization:

    • Placed in correct category
    • Properly tagged
    • No duplication with existing skills
    • Clear relationship to related skills

    Integration Workflow

    Step 1: Create in Harvestable Directory

    mkdir -p harvestable_skills/[category]/[skill-name]
    # Create skill.md with full content
    

    Step 2: Review and Refine

    • Test all examples
    • Verify instructions
    • Add missing sections
    • Improve clarity

    Step 3: Move to Skills Collection

    # Copy to final location
    cp -r harvestable_skills/[category]/[skill-name] skills/
    
    # Or organize by category
    cp -r harvestable_skills/[category]/[skill-name] skills-by-category/[category]/
    

    Step 4: Commit and Share

    git add skills/ harvestable_skills/
    git commit -m "🎯 Harvest skills: [description]"
    git push
    

    Examples of Harvested Skills

    Example 1: From Infrastructure Work → Skill

    Original work: Managing Proxmox VE cluster with containers and VMs

    Harvested skill: proxmox-manager

    • Container lifecycle management
    • VM provisioning
    • GPU passthrough configuration
    • Network troubleshooting
    • Backup and restore procedures

    Example 2: From Problem Solving → Skill

    Original work: Dealing with Claude Code timeouts during bulk operations

    Harvested skill: session-timeout-handler

    • Chunking strategies
    • Checkpoint patterns
    • Progress tracking
    • Resume mechanisms
    • Background process management

    Example 3: From Workflow → Skill

    Original work: Managing multiple Git repositories with Claude-specific branching

    Harvested skill: claude-git-branching

    • Branch naming conventions
    • Push with retry logic
    • Multi-repo coordination
    • Conflict resolution
    • PR automation

    Tips for Effective Harvesting

    🎯 Focus on Value

    Harvest skills that:

    • Save significant time
    • Reduce errors
    • Encode expertise
    • Enable new capabilities
    • Solve recurring problems

    📝 Document Context

    Include:

    • Why this approach works
    • When to use alternatives
    • Trade-offs and considerations
    • Real-world scenarios
    • Lessons learned

    🔄 Iterate and Improve

    • Start with basic version
    • Add examples from actual use
    • Incorporate feedback
    • Refine based on experience
    • Version as needed

    🤝 Share and Collaborate

    • Contribute to team repositories
    • Accept contributions
    • Review and merge improvements
    • Build on others' skills
    • Create skill compositions

    Skill Composition

    Combine multiple skills for powerful workflows:

    # Example: Full-Stack Deployment Skill
    
    Combines:
    - docker-optimization (build efficient images)
    - kubernetes-deploy (deploy to cluster)
    - database-migration (update schema)
    - health-check-monitoring (verify deployment)
    - rollback-strategy (revert if needed)
    

    Measurement and Tracking

    Track the value of your skills:

    # Track skill usage
    echo "$(date): Used skill-harvester for project X" >> ~/.claude/skill-usage.log
    
    # Count skill reuse
    grep "skill-harvester" ~/.claude/skill-usage.log | wc -l
    
    # Measure time saved
    # Before: 4 hours to set up manually
    # After: 20 minutes with skill
    # Savings: 3.67 hours per use
    

    Advanced Patterns

    Pattern 1: Progressive Disclosure

    Start with simple template, add complexity as needed:

    1. Basic: Essential operations only
    2. Intermediate: Common patterns and variations
    3. Advanced: Edge cases and optimizations
    4. Expert: Deep dives and internals

    Pattern 2: Skill Families

    Create related skills that work together:

    database-skills/
    ├── postgres-optimization/
    ├── postgres-backup/
    ├── postgres-replication/
    └── postgres-monitoring/
    

    Pattern 3: Meta-Skills

    Skills that help create or manage other skills:

    • skill-harvester (this skill)
    • skill-tester (validate skills work)
    • skill-documenter (generate documentation)
    • skill-versioner (manage versions)

    Resources

    Skill Repositories

    • anthropics/claude-code-skills
    • Community skill collections
    • Team-specific repositories

    Tools

    • Git for version control
    • Markdown for documentation
    • YAML for metadata
    • Shell scripts for automation

    Best Practices

    • Follow Claude Code skill conventions
    • Use consistent formatting
    • Include metadata frontmatter
    • Tag appropriately
    • Version when needed

    Version: 1.0.0 Author: Harvested from your_claude_skills repository Last Updated: 2025-11-18 License: MIT

    Quick Start

    1. Reflect: Review your recent work (git log, files changed, problems solved)
    2. Identify: List 3-7 skills worth harvesting
    3. Create: Use the skill template for each
    4. Organize: Place in appropriate category
    5. Commit: Add to repository
    6. Share: Push and make available to team

    Remember: The best skills solve real problems and encode genuine expertise. Happy harvesting! 🎯

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