Skill UI

Manages branching strategies, conventional commits, PR checklists, and daily Git commands so you stay disciplined when creating features, resolving conflicts, and collaborating through pull requests.

This comprehensive guide details the workflow, core invariants, and guardrails for developing, modifying, and verifying TypeScript MCP servers and applications using the mcp-use package. It covers everything from project scaffolding and tool referencing to advanced features like authentication and skills over MCP, ensuring developers adhere to the latest architectural best practices.

Automate the validation and testing of prompts and AI responses within your CI/CD pipeline using Mistral AI. This integration provides robust prompt regression testing, model quality checks, automatic cost estimation for API usage, and deployment gates, ensuring the stability and reliability of your AI features upon every pull request.

This comprehensive workflow guide covers all production-ready patterns for Mistral AI chat completions. It demonstrates critical advanced features including multi-turn conversation management, real-time streaming responses, structured JSON output using schemas, and implementing robust guardrails and moderation. Ideal for building scalable, production-grade conversational AI applications and advanced chat interfaces.

This skill provides comprehensive patterns for handling sensitive data when integrating with Mistral AI. It covers PII redaction (emails, phone numbers, etc.), implementing data retention policies, and enforcing compliance with global privacy regulations like GDPR and CCPA. Key features include safe API wrappers, dataset sanitization for fine-tuning, and conversation history management with TTL and user erasure rights.

Automatically generates robust, schema-compliant mock API servers directly from OpenAPI specifications. This tool supports advanced testing features, including stateful CRUD operations, Faker-driven dynamic data generation, configurable latency simulation, and detailed request recording for contract testing. Ideal for frontend parallel development and isolated integration testing.

This comprehensive workflow guides the process of building and deploying new features that must maintain consistent functionality and design across multiple operating systems (web, mobile, and desktop). It strictly follows an API-first architecture, starting with defining shared API contracts (OpenAPI/GraphQL) and a unified design system. The process then guides parallel implementation across specialized stacks like React/Next.js, SwiftUI, and Jetpack Compose, ensuring high code consistency and faster time-to-market.

This skill provides comprehensive guides and best practices for working with Neon Serverless Postgres. It covers initial setup, various connection methods (TCP, WebSockets), and advanced features like branching, autoscaling, and connection pooling. It offers detailed integration advice for Python, TypeScript, and other languages, making it essential for building scalable, modern database applications.

A comprehensive guide providing best practices and architectural patterns for modern full-stack development using Next.js 14+ App Router. Covers advanced topics like Server Components, efficient data fetching, handling parallel routes, and implementing full-stack features with Server Actions for scalable React applications.

This skill provides comprehensive guides and code templates for implementing major NFT standards, including ERC-721 and ERC-1155. It covers best practices for metadata (on-chain and IPFS), managing token supply, implementing complex features like royalties, and building various types of digital collectibles and gaming assets on the blockchain.

This skill provides deep integration with Google NotebookLM, enabling users to query uploaded documentation using Gemini. It ensures source-grounded, citation-backed answers, significantly reducing hallucinations. Features include managing the notebook library (add, list, search), handling authentication, and implementing a structured follow-up mechanism for comprehensive research.

Guides Nx generator usage in monorepos, covering discovery, schema inspection, context analysis, dry runs, and execution with --no-interactive to scaffold projects, libraries, and features while preferring workspace plugins.