Skill Dependency Mapper

Analyze skill ecosystems to optimize workflows, identify bottlenecks, and recommend effective skill combinations through dependency mapping.

Skill Dependency Mapper

A tool for analyzing skill ecosystems to optimize workflows, identify bottlenecks, and recommend effective skill combinations through comprehensive dependency mapping.

This skill is perfect for developers managing complex skill ecosystems who want to optimize workflow efficiency and understand skill relationships.

Skill Structure

The repository provides analysis tools and reference materials:

Main Files:

  • SKILL.md - Core dependency analysis framework

Resource Directories:

  • references/ - Relationship analysis guides and templates
  • scripts/ - Automated dependency detection tools

Core Purpose

The Skill Dependency Mapper analyzes relationships between skills to:

  • Optimize workflows by identifying complementary skills
  • Detect bottlenecks causing performance issues
  • Recommend skill stacks for specific tasks
  • Visualize dependencies showing how skills interconnect

Five Core Capabilities

1. Skill Analysis

Extracts comprehensive metadata from each skill:

  • Tool dependencies (file I/O, API calls, computation)
  • Supported file formats
  • Domain categories
  • Complexity metrics (token usage, tool calls)

2. Bottleneck Detection

Identifies workflow inefficiencies by analyzing:

  • High token usage patterns
  • Excessive tool call chains
  • Performance constraints
  • Resource-intensive operations

3. Dependency Mapping

Creates text-based visualizations showing:

  • Which skills work together effectively
  • Shared characteristics and patterns
  • Workflow sequences and chains
  • Relationship strength indicators

4. Stack Recommendations

Suggests optimal skill combinations for:

  • Data analysis pipelines
  • Document processing workflows
  • Financial reporting tasks
  • Custom use case scenarios

5. Custom Analysis

Filters and analyzes skills by:

  • Required tools
  • Domain expertise
  • Complexity levels
  • Specific criteria

Relationship Metrics

Skills are categorized by dependency strength:

Dependency Categories:

  • Strong (3+ shared characteristics) - Highly complementary skills
  • Medium (2 shared characteristics) - Compatible skill pairs
  • Weak (1 shared characteristic) - Loosely related skills

Bottleneck Severity Levels

The system identifies performance issues by severity:

  • Low - Under 5k tokens, minimal impact
  • Medium - 5-10k tokens, moderate concern
  • High - Over 10k tokens with 5+ tool calls, significant bottleneck

Practical Applications

Common Use Cases

Workflow Optimization

Example: Data Analysis Workflow

  • Identify skills for data ingestion, processing, and visualization
  • Map dependencies between analysis steps
  • Detect bottlenecks in transformation pipelines
  • Recommend optimized skill sequences

Troubleshooting

Example: Document Processing Slowdowns

  • Analyze token usage across document skills
  • Identify expensive operations
  • Find alternative skill combinations
  • Suggest performance improvements

Stack Building

Example: Financial Reporting Stack

  • Recommend skills for data extraction, calculation, and reporting
  • Ensure compatibility across the stack
  • Optimize for performance and accuracy
  • Validate complete workflow coverage

Ecosystem Visualization

Example: Skill Relationship Mapping

  • Generate dependency graphs
  • Identify skill clusters
  • Find redundant capabilities
  • Discover integration opportunities

Important Limitations

Analysis Constraints:

  • Uses heuristic-based detection (not definitive)
  • Requires skills in /mnt/skills directory structure
  • Provides approximate token estimates
  • Cannot access actual runtime usage patterns
  • Relationships inferred from metadata, not execution data

Analysis Features

The framework provides:

  • Automated metadata extraction from skill files
  • Text-based dependency visualizations
  • Performance bottleneck identification
  • Stack recommendation algorithms
  • Custom filtering and querying

Output Formats

Analysis results include:

  1. Dependency graphs showing relationships
  2. Bottleneck reports with severity ratings
  3. Stack recommendations for specific tasks
  4. Metric summaries for skill complexity
  5. Relationship matrices mapping connections

Repository Resources

The repository includes analysis scripts, relationship detection algorithms, visualization tools, and bottleneck identification frameworks for comprehensive skill ecosystem management.

Visit the Skill Dependency Mapper repository for complete tools and documentation.

About This Skill

This skill was created by Nate Jones as part of his comprehensive Nate's Substack Skills collection. Learn more about Nate's work at Nate's Newsletter.

Explore the full collection to discover all 10+ skills designed to enhance your Claude workflows!


Analyze skill ecosystems to optimize workflows, identify bottlenecks, and recommend effective skill combinations through dependency mapping.