best-practices
Apply modern web development best practices for security, compatibility, and code quality. Use when asked to apply best practices, security audit, modernize code, code quality review, or check for vulnerabilities.
Security skills for audits, auth flows, vulnerability detection, and compliance checks in AI-assisted development.
This directory brings installable AI Agent skills into one place so you can filter by search, category, topic, and official source, then install them directly into Claude Code, Cursor, Windsurf, and other supported environments.
Apply modern web development best practices for security, compatibility, and code quality. Use when asked to apply best practices, security audit, modernize code, code quality review, or check for vulnerabilities.
Guides and best practices for working with Neon Serverless Postgres. Covers getting started, local development with Neon, choosing a connection method, Neon features, authentication (@neondatabase/...
O gws-chat é uma ferramenta de linha de comando para interagir com o Google Chat
This skill should be used when the user asks to pentest WordPress sites, scan WordPress for vulnerabilities, enumerate WordPress users, themes, or plugins, exploit WordPress vulnerabilities, or use WPScan. It provides comprehensive WordPress security assessment methodologies.
Deploy project to the Agentuity Cloud. Requires authentication. Use for Agentuity cloud platform operations
Autenticação é o processo de verificar a identidade de usuários e gerenciar acesso a recursos protegidos
O GitHub CLI (gh) é uma interface de linha de comando para interagir com o GitHub, versão 2.85.0.
Production-grade monorepo web application with authentication, built with Next.js, Hono, Flutter, and TypeScript
Research technical solutions, analyze architectures, gather requirements thoroughly. Use for technology evaluation, best practices research, solution design, scalability/security/maintainability analysis.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Use when reviewing a pull request - security-focused review following CLAUDE.md guidelines for breaking changes, malicious patterns, and backward compatibility
[CK] Research technical solutions, analyze architectures, gather requirements thoroughly. Use for technology evaluation, best practices research, solution design, scalability/security/maintainability analysis.