Is the generated code ready for production use?

Yes, implementations include Python type hints, explicit error handling (such as negative weight detection in Dijkstra), and use efficient data structures like deques and heaps.

How does it handle performance and scalability?

The skill includes Big O complexity annotations for every algorithm, ensuring you can choose the right approach for your data size, and utilizes path compression in Union-Find for nearly constant time operations.

What algorithms are included in this skill?

It includes Depth-First Search (DFS), Breadth-First Search (BFS), Dijkstra's shortest path, Union-Find (Disjoint Set Union), and Kahn's algorithm for topological sorting.

Does it support weighted and unweighted graphs?

Yes, it provides BFS-based shortest path logic for unweighted graphs and Dijkstra's algorithm for weighted graphs.

Graph Algorithms Skill

Name: Graph Algorithms Skill
Author: pluginagentmarketplace

bypluginagentmarketplace

•

Developer Tools

Implements production-ready graph algorithms including traversals, shortest pathfinding, and disjoint set structures.

The Graph Algorithms skill equips Claude with a robust library of optimized graph-based patterns, ranging from basic depth-first and breadth-first searches to complex pathfinding and connectivity logic. It features production-grade Python implementations of Dijkstra’s shortest path, Union-Find (DSU) with path compression, and Kahn’s topological sort. Designed for developers building everything from social networks to dependency resolvers, this skill ensures that generated code is type-safe, performance-conscious, and resilient against edge cases like cycles or disconnected nodes.

Key Features

01Shortest path calculation using Dijkstra’s algorithm with path reconstruction

022 GitHub stars

03Topological sorting for dependency resolution and cycle detection

04High-performance Union-Find (DSU) with path compression and rank optimization

05Optimized implementations of DFS and BFS with iterative and recursive options

06Detailed time and space complexity annotations for performance tracking

Use Cases

01Building navigation and routing features for mapping or logistics software

02Analyzing connectivity and clustering within social networks or data models

03Managing task dependencies and scheduling in build systems or project management tools

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pluginagentmarketplace/custom-plugin-data-structures-algorithms graphs

For use in Claude.ai and ChatGPT

Download Skill

Key Features

01Shortest path calculation using Dijkstra’s algorithm with path reconstruction

022 GitHub stars

03Topological sorting for dependency resolution and cycle detection

04High-performance Union-Find (DSU) with path compression and rank optimization

05Optimized implementations of DFS and BFS with iterative and recursive options

06Detailed time and space complexity annotations for performance tracking

Use Cases

01Building navigation and routing features for mapping or logistics software

02Analyzing connectivity and clustering within social networks or data models

03Managing task dependencies and scheduling in build systems or project management tools

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pluginagentmarketplace/custom-plugin-data-structures-algorithms graphs

For use in Claude.ai and ChatGPT

Download Skill