samber

🧑‍🎨 A collection of Golang agentic skills that works

15
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100% credibility
Found Mar 22, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Go
AI Summary

A repository of reusable expert guides that enhance AI coding assistants with specialized knowledge for building production-ready Golang projects.

How It Works

1
🕵️ Discover Go Coding Boost

You find a set of expert guides that supercharge your AI helper for writing top-notch Go programs.

2
🤖 Pick Your AI Buddy

You choose the AI coding assistant you already use every day for your projects.

3
✨ Add the Magic Guides

With one easy action, you load these smart guides into your AI so it knows all the pro tricks for Go.

4
đź’» Dive into Coding

You start working on your Go project and chat with your AI for ideas and fixes.

5
đź§  Unlock Expert Wisdom

Your AI lights up with precise advice on clean code, strong tests, speed, and safety tailored just for Go.

🚀 Build Pro-Level Apps

You effortlessly create reliable, high-quality Go software ready for real-world use.

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Star Growth

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AI-Generated Review

What is cc-skills-golang?

This is a collection of agentic skills tailored for Golang developers using AI coding assistants like Claude, Cursor, or Copilot. It delivers reusable prompt collections on Go best practices—covering code style, error handling, testing, security, performance (including garbage collection tuning), and CI setups—loaded on demand to boost AI accuracy without bloating context. Install via a simple CLI like `npx skills add` across tools, turning generic code gen into production-ready Golang output.

Why is it gaining traction?

Unlike scattered Go guides or generic prompts, this offers atomic, evaluated skills with proven wins: overall error rate jumps +43 percentage points, skills like testing cut gaps by 32%. Low token overhead means fast loading, cross-tool compatibility (Claude Code to Gemini CLI), and overrides for team conventions make it a practical golang collection library alternative to manual prompt engineering. Developers hook on the evals showing real reductions in bugs for concurrency, databases, and observability.

Who should use this?

Golang backend engineers building microservices or CLIs who rely on AI for boilerplate like structs, gRPC, or testify tests. Teams standardizing CI/CD pipelines or performance tweaks (force garbage collection, prometheus alerts) via agentic workflows. Solo devs prototyping with Cursor/Copilot wanting consistent, secure Go without deep expertise dives.

Verdict

Grab it if you're deep in AI-assisted Go dev—evals back the value despite 15 stars and 1.0% credibility score signaling early maturity. Solid docs and modular design outweigh thin adoption; test a few skills before full commit.

(187 words)

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