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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 MCP (Model Context Protocol) servers that enable LLMs to interact with external services. Use when building MCP servers, integrating external APIs, implementing tool servers, or creating agent capabilities. Covers TypeScript/Python patterns, tool design, and evaluation creation.
This skill should be used when analyzing, profiling, or optimizing Telegram bots built with Python/Telethon, especially for performance bottlenecks, rate limits, caching, API usage, or when the user asks for a full repo review or best practices.
Use PROACTIVELY when creating Model Context Protocol servers for connecting AI applications to external data sources, tools, and workflows. Generates production-ready MCP servers with TypeScript/Python SDKs, configuration templates, and Claude Desktop integration. Includes testing workflow with MCP Inspector. Not for modifying existing MCP servers or non-MCP integrations.
Provide a reusable pattern for memoizing deterministic function calls to reduce latency and repeated computation. Backed by the `python` diskcache package. Use skill when updating or editing everything.
Master machine learning, data engineering, AI engineering, LLMs, prompt engineering, and MLOps. Build intelligent systems with Python.
Kailash Core SDK fundamentals including workflow creation, node patterns, connections, runtime execution, parameter passing, error handling, cyclic workflows, async patterns, MCP integration, and installation. Use when asking about 'workflow basics', 'core sdk', 'create workflow', 'workflow builder', 'node patterns', 'connections', 'runtime', 'parameters', 'imports', 'installation', 'getting started', 'workflow execution', 'async workflows', 'error handling', 'cyclic workflows', 'PythonCode node', 'SwitchNode', or 'MCP integration'.
Build MCP (Model Context Protocol) servers for Claude Code integration. Use when creating tools, resources, or prompts that extend Claude's capabilities. Supports Python FastMCP and TypeScript implementations.
Implement native Rust ML inference with Candle framework. Use when building GPU-accelerated ML pipelines without Python dependencies.
Python machine learning with scikit-learn, PyTorch, and TensorFlow
Master MongoDB integration in applications with Node.js, Python, and Java drivers. Learn connections, transactions, error handling, and best practices. Use when building applications with MongoDB.
Modern Python project architecture guide for 2025. Use when creating Python projects (APIs, CLI, data pipelines). Covers uv, Ruff, Pydantic, FastAPI, and async patterns.
Generates comprehensive implementation documentation for software development phases. Creates 7 professional documents including atomic commit plans, checklists, environment setup, review guides, and testing strategies. Use when the user mentions "generate phase documentation", "create implementation docs", "phase planning", "atomic commits documentation", "implementation guide", or needs structured documentation for a development phase with step-by-step implementation plans. Supports any tech stack (Next.js, Django, React, Python, etc.). Uses adaptive sizing (1-20+ commits) based on actual complexity rather than arbitrary limits.
Analyze codebases and generate Claude Code automation infrastructure including commands, scripts, and templates for systematic task execution. Use when the user wants to create reusable automation workflows, generate .claude/commands files, create supporting bash/python scripts, build markdown templates for structured outputs, or establish multi-step task execution frameworks that work across projects.
Provides KurrentDB (EventStoreDB) client code for event sourcing and CQRS. Generates correct package names, connection strings, and API patterns for Python, Node.js, .NET, F#, Go, Java, Rust. Triggers on "kurrentdb", "eventstore", "event sourcing", "append events", "read stream", "subscription", "aggregate", "CQRS".
Create and refactor Python dataclass business models and mappers following clean architecture patterns with proper separation of concerns.
