golang-dsa

Provide data structures and algorithms implementations using Go standard libraries.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/ep0ll/bons-ci --skill golang-dsa
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: golang-dsa
Source: https://github.com/ep0ll/bons-ci/tree/main/.agents/skills/dsa
Command: npx skills add https://github.com/ep0ll/bons-ci --skill golang-dsa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides comprehensive tutorials and implementations for data structures and algorithms essential for writing efficient and optimized code.

Core Features & Use Cases

  • Educational Resources: In-depth explanations of data structures like trie, bloom filter, and graphs, with practical code examples.
  • Algorithm Implementations: Ready-to-use code for shortest path algorithms, sorting, searching, and more.
  • Use Case: A software engineer optimizing a backend service can utilize these data structures to enhance performance and scalability.

Quick Start

Use the data structures and algorithms provided to implement a custom cache or process complex graph data.

Frequently Asked Questions about golang-dsa

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement graph data structures and shortest path algorithms in Go?

Implement graph data structures and shortest path algorithms in Go by utilizing ready-to-use code examples that require only the standard library. These implementations provide detailed logic for processing complex graph data efficiently.

When should I use a bloom filter or trie for performance optimization in Go?

Use a bloom filter or trie for performance optimization in Go when building custom caches or handling high-volume lookups. These data structures minimize memory usage while accelerating search operations in backend services.

Can I build a custom cache using Go data structures without external dependencies?

You can build a custom cache using Go data structures without external dependencies by relying solely on the standard library. Provided implementations cover core structures like heaps and bloom filters for scalable caching.

What is the best way to process complex graph data for backend scalability in Go?

The best way to process complex graph data for backend scalability in Go is applying provided shortest path algorithms and graph structures. This approach enhances performance and handles high-throughput routing efficiently.

Does this approach require any specific Go frameworks or third-party libraries to run?

This approach requires no specific Go frameworks or third-party libraries to run. All data structures and algorithm implementations depend exclusively on the native standard library, ensuring zero external dependencies.