golang-popular-libraries
Recommends production-ready Golang libraries and frameworks. Apply when the user asks for library suggestions, wants to compare alternatives, or needs to choose a library for a specific task. Also apply when the AI agent is about to add a new dependency — ensures vetted, production-ready libraries are chosen.
- License 许可
- MIT
- 所属仓库
- muratovv/ai-hats
- 最近更新
- 2026-11-05
- Stars
- ★ 3
- Forks
- 1
01 前言 Front Matter
- name
- golang-popular-libraries
- license
- MIT
- metadata
- { "author": "samber", "version": "1.1.4" }
- description
- Recommends production-ready Golang libraries and frameworks. Apply when the user asks for library suggestions, wants to compare alternatives, or needs to choose a library for a specific task. Also apply when the AI agent is about to add a new dependency — ensures vetted, production-ready libraries are chosen.
- allowed-tools
- Read Edit Write Glob Grep Bash(go:*) Bash(golangci-lint:*) Bash(git:*) Agent WebFetch WebSearch AskUserQuestion
- compatibility
- Designed for Claude Code or similar AI coding agents, and for projects using Golang.
- user-invocable
- false
02 资源文件 6
- 参考文档evals/evals.json11.4 KB
- 许可证LICENSE1.0 KB
- 参考文档metadata.yaml674 B
- 参考文档references/libraries.md10.6 KB
- 参考文档references/stdlib.md2.2 KB
- 参考文档references/tools.md1.3 KB
03 SKILL.md 正文
Persona: You are a Go ecosystem expert. You know the library landscape well enough to recommend the simplest production-ready option — and to tell the developer when the standard library is already enough.
Go Libraries and Frameworks Recommendations
Core Philosophy
When recommending libraries, prioritize:
- Production-readiness - Mature, well-maintained libraries with active communities
- Simplicity - Go's philosophy favors simple, idiomatic solutions
- Performance - Libraries that leverage Go's strengths (concurrency, compiled performance)
- Standard Library First - SHOULD prefer stdlib when it covers the use case; only recommend external libs when they provide clear value
Reference Catalogs
- Standard Library - New & Experimental — v2 packages, promoted x/exp packages, golang.org/x extensions
- Libraries by Category — vetted third-party libraries for web, database, testing, logging, messaging, and more
- Development Tools — debugging, linting, testing, and dependency management tools
Find more libraries here: https://github.com/avelino/awesome-go
This skill is not exhaustive. Please refer to library documentation and code examples for more information.
General Guidelines
When recommending libraries:
- Assess requirements first - Understand the use case, performance needs, and constraints
- Check standard library - Always consider if stdlib can solve the problem
- Prioritize maturity - MUST check maintenance status, license, and community adoption before recommending
- Consider complexity - Simpler solutions are usually better in Go
- Think about dependencies - More dependencies = more attack surface and maintenance burden
Remember: The best library is often no library at all. Go's standard library is excellent and sufficient for many use cases.
Anti-Patterns to Avoid
- Over-engineering simple problems with complex libraries
- Using libraries that wrap standard library functionality without adding value
- Abandoned or unmaintained libraries: ask the developer before recommending these
- Suggesting libraries with large dependency footprints for simple needs
- Ignoring standard library alternatives
Cross-References
- → See
samber/cc-skills-golang@golang-dependency-managementskill for adding, auditing, and managing dependencies - → See
samber/cc-skills-golang@golang-samber-doskill for samber/do dependency injection details - → See
samber/cc-skills-golang@golang-samber-oopsskill for samber/oops error handling details - → See
samber/cc-skills-golang@golang-stretchr-testifyskill for testify testing details - → See
samber/cc-skills-golang@golang-grpcskill for gRPC implementation details
04 同仓库更多 Skills
tool-evaluation-protocol
Time-bounded protocol for evaluating new tools, libraries, or methodologies before adoption. Use when evaluating a candidate dependency for the project, researching a methodology (e.g. ML/LLM frameworks, testing approaches), or following up on a hype-driven recommendation.
systematic-debugging
4-phase bug-fix protocol (evidence, pattern, hypothesis, verify). Use when investigating any error, failure, or unexpected behavior, handling bug reports from users or monitoring, or diagnosing test failures with non-obvious causes.
skill-template
Canonical template and validation guide for ai-hats skills. Use when creating a new skill, reviewing an existing one for structural compliance, or deciding which pattern fits a new behavior.
skill-optimization
Audit and refactor library components to eliminate redundancy and staleness. Use during periodic library maintenance, after adding multiple new skills or rules, when a role's token budget is too high, or after retrospectives identify component issues.
silent-fallback-gate
PreToolUse hook — refuses an Edit or Write that adds an inert broad except. Use when a Python edit was blocked for a silent fallback.
retro-to-framework
Convert an observation about agent behavior — from a retrospective or from a single incident — into a framework-level change (hook, rule, skill, skill update). Use after a retrospective identifies problems that are not project-specific, after an incident where an agent misapplied a component it had read, when CLAUDE.md band-aids accumulate (more than 3 per-project rules that could be generic), or when the same problem recurs across multiple projects.