antigravity-awesome-skills
A curated collection of reusable "skills" (structured prompt/instruction modules) for AI coding agents like Claude Code, Cursor, Codex CLI, and Gemini CLI. It packages templates, bundles, and workflows that extend agent capabilities, along with quality and security guidelines for contributors.
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[](https://opensources.dev/resource/antigravity-awesome-skills)MITPermissive — free to use in commercial and proprietary software, with attribution.View license →
Production readiness
5/5- Actively maintainedCommits in the last 6 months
- No known vulnerabilitiesNo OSV advisories
- Clear, usable licenseMIT (permissive)
- Proven adoptionWidely used
- Has documentationDocumentation indexed
pip install antigravity-awesome-skillsOur analysis
A community-maintained, awesome-style index of portable 'skills' — markdown-based instruction/prompt modules that give AI coding agents specialized, repeatable capabilities. It supports multiple agent runtimes (Claude Code, Cursor, Codex CLI, Gemini CLI, Kiro) and provides bundles, workflows, and contribution standards.
When to use antigravity-awesome-skills
Use it when you want ready-made, vetted prompt/skill packs to drop into a coding agent rather than authoring instructions from scratch, or when you want a template and quality bar for writing your own portable skills that work across multiple agents.
When not to
Not relevant if you need an actual runtime/SDK to build agents, a single-vendor official skill registry, or programmatic tooling — this is a curated content repository, not a library or framework you import.
Strengths
- Cross-agent coverage (Claude, Cursor, Codex, Gemini, Kiro) rather than locking to one tool
- Strong governance signals: contribution templates, quality bar, security guardrails, and audit/release docs
- Large community traction (tens of thousands of stars) and bundles/workflows for common tasks
- Well-organized documentation split across users, contributors, and maintainers
Trade-offs
- Value depends on individual skill quality, which can vary across community submissions
- Skills are prompt text, so effectiveness is model- and version-sensitive and can drift
- Heavy SEO/marketing-oriented docs suggest some focus on discoverability over substance
- No executable code or guarantees — users must vet skills for security despite guardrail docs
Maturity
Very high visibility (40k+ stars) with structured maintainer processes (release, rollback, audit, CI drift) indicating active curation. As a content/awesome-list repo, 'production-readiness' means content freshness and review rigor rather than software stability.