Find the perfect capability for your agent.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Expert backend development guidance covering Node.js, Python, Java, Go, API design (REST/GraphQL/gRPC), database patterns, authentication, caching, message queues, microservices, and testing. Produces production-ready, scalable, and secure backend code with industry best practices. Use when building APIs, implementing business logic, designing data models, integrating services, or when users mention backend development, server-side code, APIs, databases, or microservices.
LLM이 잘 설계된 도구를 통해 외부 서비스와 상호작용할 수 있게 하는 고품질 MCP(Model Context Protocol) 서버 생성 가이드. Python(FastMCP)이나 Node/TypeScript(MCP SDK)로 외부 API나 서비스를 통합하는 MCP 서버를 구축할 때 사용한다.
Executes Perplexity AI queries via unified Python CLI. Use when conducting web research, asking questions with citations, deep research tasks, reasoning problems, or searching for up-to-date information.
Integrate and embed OpenAI ChatKit UI into TypeScript/JavaScript frontends (Next.js, React, or vanilla) using either hosted workflows or a custom backend (e.g. Python with the Agents SDK). Use this Skill whenever the user wants to add a ChatKit chat UI to a website or app, configure api.url, auth, domain keys, uploadStrategy, or debug blank/buggy ChatKit widgets.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
This skill should be used when the user asks about "creating a new ADK project", "initializing ADK", "setting up Google ADK", "adk create command", "ADK project structure", "YAML agent configuration", "creating an agent", "LlmAgent", "BaseAgent", "custom agent", "agent with different model", "Claude with ADK", "OpenAI with ADK", "LiteLLM", "multi-model agent", or needs guidance on bootstrapping an ADK development environment, authentication setup, choosing between Python code and YAML-based agent definitions, agent configuration, model selection, system instructions, or extending the base agent class for non-LLM logic.
Build production-ready Python CLI tools, utilities, and automation scripts with strict typing, performance optimization, and zero external dependencies (stdlib-only by default). Triggers on "Create a CLI tool for", "Build a Python utility that", "Write a script to", or any request for Python automation/file processing/system utilities. Enforces user preferences (PEP 8, slots=True dataclasses, typed returns, O(n) complexity, security-first, no external libs unless essential).
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK). | Sử dụng khi: tạo MCP server, xây dựng tool server.
Expert guide for building command-line interfaces with Node.js (Commander, Inquirer, Ora) or Python (Click, Typer, Rich). Use when creating CLI tools, terminal UX, argument parsing, or interactive prompts.
Build AI agents with Google's Agent Development Kit (ADK) Python. Use when building AI agents with tool integration, multi-agent systems, workflow agents (sequential, parallel, loop), or deploying to Vertex AI.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Use this if the user wants to connect to Ollama or leverage Ollama in any shape or form inside their project. Guide users integrating Ollama into their projects for local AI inference. Covers installation, connection setup, model management, and API usage for both Python and Node.js. Helps with text generation, chat interfaces, embeddings, streaming responses, and building AI-powered applications using local LLMs.
[Extends backend-developer] Python FastAPI specialist. Use for FastAPI apps, async endpoints, Pydantic v2, SQLAlchemy async, dependency injection. Invoke alongside backend-developer for Python API projects.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK). | 適切に設計されたツールを通じてLLMが外部サービスと対話できるようにする高品質MCP（Model Context Protocol）サーバーを作成するためのガイド。Python（FastMCP）またはNode/TypeScript（MCP SDK）で外部APIやサービスを統合するMCPサーバーを構築する際に使用
Build AI agents with Google's Agent Development Kit (ADK) Python - an open-source toolkit for building, evaluating, and deploying AI agents. Features LlmAgent, workflow agents (sequential, parallel, loop), tool integration, multi-agent systems, and deployment to Vertex AI or Cloud Run.
Design, implement, and debug a custom ChatKit backend in Python that powers the ChatKit UI without Agent Builder, using the OpenAI Agents SDK (and optionally Gemini via an OpenAI-compatible endpoint). Use this Skill whenever the user wants to run ChatKit on their own backend, connect it to agents, or integrate ChatKit with a Python web framework (FastAPI, Django, etc.).
Creates and edits Claude Code skills with YAML frontmatter, folder structure, and depth-scaled content. Use when building new skills, updating existing skills, designing SKILL.md metadata, organizing skill folders, validating skill structure, or adding Python and TypeScript scripts for deterministic operations.
