claude-code-meta-skill/SUMMARY.md

Meta Skill Generator - Summary

What I've Built

A comprehensive Claude Code skill that generates other Claude Code skills with intelligent separation of deterministic operations into Go scripts.

Core Capabilities

1. Workflow Analysis

• Automatically identifies deterministic vs dynamic operations
• Classifies operations as Go scripts, Python scripts, or agent workflows
• Uses keyword analysis and heuristics
• Generates detailed recommendation reports

2. Go Script Generation

• Creates production-ready Go code from specifications
• Includes CLI parsing, error handling, progress reporting
• Infers necessary imports and helper functions
• Generates build scripts automatically
• Updates SKILL.md with usage documentation

3. End-to-End Skill Creation

• Interactive skill creation workflow
• Gathers concrete examples from users
• Analyzes operations and recommends implementations
• Generates complete skill structure
• Validates and packages the skill

Files Created

Core Skill Files

SKILL.md (283 lines)

• Comprehensive skill documentation
• 6-step workflow process
• Detailed implementation guidance
• Best practices for Go scripts

Scripts (4 files)

generate_go_script.py (363 lines)

• Main Go script generator
• Template-based code generation
• Intelligent import inference
• Automatic build script creation
• SKILL.md integration

analyze_workflow.py (236 lines)

• Workflow analysis engine
• Keyword-based classification
• Detailed recommendation reports
• Interactive and batch modes

init_skill_with_analysis.py (266 lines)

• End-to-end skill creation
• User interaction and guidance
• Integrates all components
• Progress tracking and validation

test_skill_scripts.py (183 lines)

• Script validation and testing
• Python syntax checking
• Go compilation testing
• Bash syntax validation

References (3 files)

go-patterns.md (426 lines)

• File processing patterns
• Concurrent processing
• Progress reporting
• Error handling strategies
• CLI design patterns
• Data processing (CSV, JSON)
• Testing patterns
• 10 best practices

workflow-analysis.md (346 lines)

• Decision framework
• Detailed analysis guide
• Real-world examples
• Common patterns
• Anti-patterns
• Optimization checklist

skill-examples.md (426 lines)

• 3 complete skill examples
• PDF Tools skill
• Data Processing skill
• Image Tools skill
• Key patterns across examples
• Anti-patterns to avoid
• Success metrics

Key Features

Intelligent Classification

The analyzer uses multiple signals:

Deterministic indicators:

• Keywords: convert, transform, parse, extract, validate
• Clear input/output contracts
• Repeatable operations

Dynamic indicators:

• Keywords: analyze, understand, interpret, decide
• Context-dependent logic
• Creative or reasoning tasks

Performance indicators:

• Keywords: batch, parallel, large file, concurrent
• High-volume operations
• Binary/low-level tasks

Library indicators:

• Keywords: pandas, numpy, plot, machine learning
• Specialized Python libraries needed

Go Script Template

Generated scripts include:

1. CLI Framework

   • --help flag with usage
   • --verbose for debugging
   • Proper argument parsing

2. Error Handling

   • Input validation
   • Descriptive error messages
   • Proper exit codes (0/1/2)

3. Best Practices

   • Resource cleanup with defer
   • Progress reporting for long operations
   • Streaming for large files
   • Parallel processing where appropriate

4. Code Quality

   • Clean separation of concerns
   • Helper functions for common patterns
   • Comprehensive error wrapping
   • Table-driven testing patterns

Progressive Disclosure

Follows skill-creator principles:

SKILL.md - Core workflows and common operations
References - Detailed guides and patterns
Scripts - Executable implementations

Keeps SKILL.md under 500 lines by moving details to references.

Usage Examples

Generate a Single Script

scripts/generate_go_script.py \
  --name csv-to-json \
  --description "Convert CSV files to JSON" \
  --input "CSV file path" \
  --output "JSON array to stdout" \
  --logic "Parse CSV rows and convert to JSON array" \
  --skill-path ./data-tools

Output:

• csv-to-json.go - Complete Go source
• build_csv-to-json.sh - Build script
• Updated SKILL.md with documentation

Create Complete Skill

scripts/init_skill_with_analysis.py my-skill --path ./skills

Interactive process:

1. Gather example use cases
2. Analyze operations (auto-classify)
3. Confirm plan
4. Specify Go script details
5. Generate everything
6. Ready to package

Analyze Requirements

scripts/analyze_workflow.py --examples requirements.txt

Output:

• Go scripts recommendations
• Python scripts recommendations
• Agent workflows recommendations
• Suggested script names
• Implementation guidance

Design Decisions

Why Go for Deterministic Operations?

1. Performance - Compiled binaries are fast
2. Reliability - Strong typing catches errors
3. Deployment - Single binary, no dependencies
4. Concurrency - Built-in goroutines for parallelism
5. Standard library - Rich stdlib for common tasks

Why Keep Agent Workflows?

Not everything should be scripted:

• Content understanding requires LLM
• Context-dependent decisions
• Creative tasks
• Adaptive error handling

The skill intelligently separates these concerns.

Why Both Analysis and Generation?

Analysis helps identify what to extract
Generation creates the actual implementations

Together they provide end-to-end skill creation.

Testing

All scripts tested:

• ✅ Python syntax validation
• ✅ Executable permissions
• ✅ Help output working
• ✅ Go script generation tested
• ✅ Skill packaging successful

What This Enables

Users can now:

1. Create skills faster - Automated script generation
2. Better separation - Clear Go vs agent boundaries
3. Higher quality - Best practice templates
4. Performance - Compiled Go for speed
5. Maintainability - Consistent structure

Inspiration

Based on the skill-creator skill and the taches skill mentioned, this meta skill:

• Follows skill-creator guidelines exactly
• Adds Go script generation capability
• Includes workflow analysis
• Provides comprehensive patterns and examples
• Creates production-ready skills

Next Steps for Users

After installing this skill:

1. Create your first skill:

   scripts/init_skill_with_analysis.py my-skill --path .
   

2. Study the references:

   • go-patterns.md for implementation patterns
   • workflow-analysis.md for design decisions
   • skill-examples.md for complete examples

3. Generate scripts as needed:

   • Use generate_go_script.py for new operations
   • Follow the template patterns
   • Test with test_skill_scripts.py

4. Package and share:

   • Validate with package_skill.py
   • Share .skill files
   • Iterate based on usage

File Statistics

Total files: 8 (4 scripts, 3 references, 1 SKILL.md)
Total lines: ~2,800
Scripts tested: ✅ All passing
Package validation: ✅ Successful
Ready to use: ✅ Yes

Deliverables

1. meta-skill-generator.skill - Complete packaged skill
2. META-SKILL-GENERATOR-GUIDE.md - User guide
3. This summary document

Everything follows skill-creator best practices and is ready for production use.