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affaan-m

ai-first-engineering is a skill that enables teams to effectively integrate AI agents into their development workflow, focusing on agent-friendly architectures and rigorous testing.

google-labs-code

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

HeadyMe

Multi-model code generation, refactoring, and inline suggestions using Heady™Coder, HeadyCodex, HeadyCopilot, and HeadyRefactor.

ksmuvva

Code-generation is a skill that generates production-quality code following clean code principles and security-first approach.

ThiagoGuislotti

Curated collection of GitHub Copilot instructions, templates, and best practices for consistent code generation

yelmuratoff

Generate-all AI agent skill is a technology for automatically generating analytics events for Dart packages from YAML configuration

catlog22

Universal team coordination skill with dynamic role generation. Uses team-worker agent architecture with role-spec files. Only coordinator is built-in -- all worker roles are generated at runtime as r

uehlbran

Open-source TypeScript libraries for Pokemon battles — pluggable engine, per-generation rulesets (Gen 1-9), and complete standalone data. Zero dependencies on game engines.

majiayu000

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

bdarcus

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

renpereiradx

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

ksolomon68

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.