Documentation AI Agent Skills

GenAI Agent Framework, the Pydantic way Documentation: ai.pydantic.dev FastAPI revolutionized web development by offering an innovative and ergonomic design, built on the foundation of Pydantic Validation and modern Python features like type hints. Yet despite virtually every Python agent framework and LLM library using Pydantic Validation, when we began to use LLMs in Pydantic Logfire, we couldn'

you are an expert in coding with swift, swift ui. you always write maintainable code and clean code.

Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.

Persona

You are an AI assistant specialized in Python development.

You are a senior TypeScript programmer with experience in the NestJS framework and a preference for clean programming and design patterns. Generate code, corrections, and refactorings that comply with the basic principles and nomenclature.

You are an expert in TypeScript, Node.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

- 🎯 Quick Start - Become an x402 Champion - 📚 Official Resources - 📖 Protocol Documentation - 🚀 Quickstart Guides - ⚙️ Protocol Implementations - 🏭 Production Implementations - 🛠️ SDKs & Client Libraries - 🔧 Server Frameworks & Middleware - 🏗️ Facilitators - 💡 Example Applications - 🎨 Use Cases & Patterns - 🤖 AI Agent Integration - 🔨 Tools & Utilities - 🧪 Testing & Development - 📚 Tu

Draft privacy policies, terms of service, disclaimers, and legal

A Model Context Protocol (MCP) server that provides AWS EC2 instance pricing data. This project includes both a traditional server implementation and a serverless Lambda function. The Lambda function provides the same functionality as the server but with serverless benefits: For detailed Lambda documentation, see LAMBDA.md. - EC2 Pricing Data: Find the cheapest EC2 instances based on specification

Generates two complementary onboarding guides — a Principal-Level architectural deep-dive and a Zero-to-Hero contributor walkthrough. Use when the user wants onboarding documentation for a codebase.

Documentation Try with Claude Try with Goose A Model Context Protocol (MCP) server that enables AI models to interact with Bitcoin and Lightning Network, allowing them to generate keys, validate addresses, decode transactions, query the blockchain, and more. - ₿itcoin \& Lightning Network MCP Server - 💼 Table of Contents - 🔧 Features - 🔑 Claude Desktop Integration - Testing the Claude Desktop I

MCP Server for the Bitrise API, enabling app management, build operations, artifact management, and more. - Comprehensive API Access: Access to Bitrise APIs including apps, builds, artifacts, and more. - Authentication Support: Secure API token-based access to Bitrise resources. - Detailed Documentation: Well-documented tools with parameter descriptions. - VS Code - Installation for VS Code IDE -

This MCP (Model Context Protocol) server provides various tools to interact with dbt. You can use this MCP server to provide AI agents with context of your project in dbt Core, dbt Fusion, and dbt Platform. Read our documentation here to learn more. This blog post provides more details for what is possible with the dbt MCP server. We publish an experimental Model Context Protocol Bundle (dbt-mcp.m

mcp-name: io.github.aikts/yandex-tracker-mcp A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with Yandex Tracker APIs. This server provides secure, authenticated access to Yandex Tracker issues, queues, comments, worklogs, and search functionality with optional Redis caching for improved performance. Documentation in Russian is available here / Документац

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Master on-call shift handoffs with context transfer, escalation procedures, and documentation. Use when transitioning on-call responsibilities, documenting shift summaries, or improving on-call processes.

A Model Context Protocol (MCP) server that exposes FinBrain datasets to AI clients (Claude Desktop, VS Code MCP extensions, etc.) via simple tools. Backed by the official finbrain-python SDK. - Package name: finbrain-mcp - CLI entrypoint: finbrain-mcp - Documentation: finbrain.tech/integrations/mcp Access FinBrain's machine learning price forecasts with daily (10-day) and monthly (12-month) horizo

Find papers and preprints that cite a given URL, especially blogs, docs pages, project pages, or other web content that standard citation indexes often miss. Use when the user provides a URL and wants confirmed citing works, evidence from PDF or HTML references, DOI or arXiv links, BibTeX, or a deduplicated citation report.

Anyquery is a SQL query engine that allows you to run SQL queries on pretty much anything. It supports querying files, databases, and apps (e.g. Apple Notes, Notion, Chrome, Todoist, etc.). It's built on top of SQLite and uses plugins to extend its functionality. It can also connect to LLMs (e.g. ChatGPT, Claude, Cursor, TypingMind, etc.) to allow them to access your data. Finally, it can act as a

Work with a user's Semantic Scholar account to read Research Feeds, inspect private Library folders, add papers to folders, and resolve Semantic Scholar paper records from identifiers such as arXiv IDs.

Use when developing WordPress (Gutenberg) blocks: block.json metadata, register_block_type(_from_metadata), attributes/serialization, supports, dynamic rendering (render.php/render_callback), deprecations/migrations, viewScript vs viewScriptModule, and @wordpress/scripts/@wordpress/create-block build and test workflows.

The Mermaid MCP Server enables AI assistants like GitHub Copilot, Claude, and custom LLM applications to generate professional architecture diagrams, flowcharts, sequence diagrams, and more using natural language. It provides a Model Context Protocol interface for seamless integration with AI coding assistants. - 🤖 AI-Powered Generation: Create diagrams using natural language with GitHub Copilot