Python AI Agent Skills

An MCP server that enables AI agents to control web browsers using browser-use. - uv - Fast Python package manager - Playwright - Browser automation - mcp-proxy - Required for stdio mode Create a .env file: - [x] Browser Automation: Control browsers through AI agents - [x] Dual Transport: Support for both SSE and stdio protocols - [x] VNC Streaming: Watch browser automation in real-time - [x] Asyn

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

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), Node/TypeScript (MCP SDK), or C#/.NET (Microsoft MCP SDK).

Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.

Performance profiling principles. Measurement, analysis, and optimization techniques.

"language": "Python",

A Python implementation of the Model Context Protocol (MCP) for ROS 2. This server enables AI tooling to connect with ROS 2 nodes, topics, and services using the MCP standard over stdio. Designed to be the easiest ROS 2 MCP server to configure. - List available topics - List available services - Lists available actions with their types and request fields - Call services - Subscribe to topics to co

Design system MCP server for creating high-performing LinkedIn content Quick Start • Installation • Documentation • A professional Model Context Protocol (MCP) server for LinkedIn content creation, featuring a shadcn-inspired component system, 10 performance-tuned themes, and data-driven optimization based on 1M+ post analysis. Built on ChukMCPServer — a modular, zero-configuration MCP server fram

A Model Context Protocol (MCP) server that provides access to Fantasy Premier League (FPL) data and tools. This server allows you to interact with FPL data in Claude for Desktop and other MCP-compatible clients. Demo of the Fantasy Premier League MCP Server in action - Claude Desktop - Other MCP Compatible Desktop LLMs Mobile is currently not supported. - Rich Player Data: Access comprehensive pla

An open source MCP (Model Context Protocol) server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments. - Quick Start - Prerequisites - Installation - Usage Examples - Configuration - Available Tools - Architecture - How It Works - MCP Client Integration - Performance Considerations - Troubleshooting -

Holistic understanding of requirements & stack

You are an expert in Python, FastAPI, and scalable API development.

Project Synopsis

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Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

FastAPI best practices and patterns for building modern Python web APIs

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You are an expert in data analysis, visualization, and Jupyter Notebook development, with a focus on Python libraries such as pandas, matplotlib, seaborn, and numpy.

Role Definition

Python FastAPI .cursorrules

Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.

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Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.