pex-lo-skill-creator

Leverages the multiple CLIs including PEX, pdf-search, hge, researcher, limitless, pieces, screenapp and more, to extract all relevant LOs across both CICM and ANZCA PEX exams, cross reference them with past SAQ questions, extract examiner comments, cross reference this with recommended textbooks via pdf-search, generate a hypergraph using hge, validate insights with researcher, evaluate against pkm using limitless and pieces, and look for additional context to add polish with screenapp and others. Then leverages the PEX and SAQ skill, as well as the metaskills that exist in .claudeate a scaffolding for a modular, programmatic, state of the art skill that integrates quantitative physiological parameters using the qp skill, teleologically grounded framing using the physiology-style and telos skill and follows all of the principles of the code, mega, and agency skills. Finally it should be recursively optimised with the abduct, critique and refactoring agent skillls. Ergo, this skill makes SOTA PEX LO skills.

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Install skill "pex-lo-skill-creator" with this command: npx skills add zpankz/mcp-skillset/zpankz-mcp-skillset-pex-lo-skill-creator

pex-lo-skill-creator

Overview

This skill provides guidance for first-principles biophysical critical care medical reasoning to emergent systems thinking tasks using modern best practices and proven patterns.

When to Use This Skill

Use this skill when:

  • Working with first-principles biophysical critical care medical reasoning to emergent systems thinking projects
  • Implementing first-principles biophysical critical care medical reasoning to emergent systems thinking-related features
  • Following best practices for first-principles biophysical critical care medical reasoning to emergent systems thinking

Core Principles

1. Follow Industry Standards

Always adhere to established conventions and best practices

# Example: Follow naming conventions and structure
# Adapt this to your specific domain and language

2. Prioritize Code Quality

Write clean, maintainable, and well-documented code

  • Use consistent formatting and style
  • Add meaningful comments for complex logic
  • Follow SOLID principles where applicable

3. Test-Driven Approach

Write tests to validate functionality

  • Unit tests for individual components
  • Integration tests for system interactions
  • End-to-end tests for critical workflows

Best Practices

Structure and Organization

  • Organize code into logical modules and components
  • Use clear and descriptive naming conventions
  • Keep files focused on single responsibilities
  • Limit file size to maintain readability (< 500 lines)

Error Handling

  • Implement comprehensive error handling
  • Use specific exception types
  • Provide actionable error messages
  • Log errors with appropriate context

Performance Considerations

  • Optimize for readability first, performance second
  • Profile before optimizing
  • Use appropriate data structures and algorithms
  • Consider memory usage for large datasets

Security

  • Validate all inputs
  • Sanitize outputs to prevent injection
  • Use secure defaults
  • Keep dependencies updated

Common Patterns

Pattern 1: Configuration Management

# Separate configuration from code
# Use environment variables for sensitive data
# Provide sensible defaults

Pattern 2: Dependency Injection

# Inject dependencies rather than hardcoding
# Makes code testable and flexible
# Reduces coupling between components

Pattern 3: Error Recovery

# Implement graceful degradation
# Use retry logic with exponential backoff
# Provide fallback mechanisms where appropriate

Anti-Patterns

❌ Avoid: Hardcoded Values

Don't hardcode configuration, credentials, or magic numbers

# BAD: Hardcoded values
API_TOKEN = "hardcoded-value-bad"  # Never do this!
max_retries = 3

Instead: Use configuration management

# GOOD: Configuration-driven
API_TOKEN = os.getenv("API_TOKEN")  # Get from environment
max_retries = config.get("max_retries", 3)

❌ Avoid: Silent Failures

Don't catch exceptions without logging or handling

# BAD: Silent failure
try:
    risky_operation()
except Exception:
    pass

Instead: Explicit error handling

# GOOD: Explicit handling
try:
    risky_operation()
except SpecificError as e:
    logger.error(f"Operation failed: {e}")
    raise

❌ Avoid: Premature Optimization

Don't optimize without measurements

Instead: Profile first, then optimize

  • Measure performance with realistic workloads
  • Identify actual bottlenecks
  • Optimize the critical paths only
  • Validate improvements with benchmarks

Testing Strategy

Unit Tests

  • Test individual functions and classes
  • Mock external dependencies
  • Cover edge cases and error conditions
  • Aim for >80% code coverage

Integration Tests

  • Test component interactions
  • Use test databases or services
  • Validate data flow across boundaries
  • Test error propagation

Best Practices for Tests

  • Make tests independent and repeatable
  • Use descriptive test names
  • Follow AAA pattern: Arrange, Act, Assert
  • Keep tests simple and focused

Debugging Techniques

Common Issues and Solutions

Issue: Unexpected behavior in production

Solution:

  1. Enable detailed logging
  2. Reproduce in staging environment
  3. Use debugger to inspect state
  4. Add assertions to catch assumptions

Issue: Performance degradation

Solution:

  1. Profile the application
  2. Identify bottlenecks with metrics
  3. Optimize critical paths
  4. Monitor improvements with benchmarks

Related Skills

  • test-driven-development: Write tests before implementation
  • systematic-debugging: Debug issues methodically
  • code-review: Review code for quality and correctness

References

  • Industry documentation and best practices
  • Official framework/library documentation
  • Community resources and guides
  • Code examples and patterns

Version History

  • 1.0.0 (2026-01-15): Initial version

Source Transparency

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