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Found 2,136 Skills
Install, configure, and operate Scrapling for adaptive web scraping with parser-first HTML extraction, fast HTTP fetchers, browser rendering, stealth anti-bot options, CLI extraction, and optional MCP or spider workflows. Use when you need to scrape or crawl websites, choose between static, JavaScript-rendered, or protected targets, parse HTML with CSS or XPath, write Python scrapers, or run Scrapling from the terminal. Triggers on: scrapling, scrape website, crawl site, adaptive scraping, stealthy fetch, cloudflare scraping, mcp scraping server, browser scraping cli, scrapling spider.
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).
Configures structured logging (Serilog/.NET, structlog/Python)
Professional-grade Python development with Ruff (v0.14.10) - an extremely fast Python linter and formatter. Use when working with Python codebases for (1) linting and fixing code quality issues, (2) formatting Python code, (3) configuring Ruff settings, (4) understanding and resolving specific rule violations, (5) integrating Ruff into projects or editors, (6) migrating from other tools (Black, Flake8, isort, etc.), or (7) any Ruff-related development tasks. Includes complete documentation for 937+ lint rules, formatter settings, configuration options, and editor integrations.
Review Python code for quality, security, and best practices
Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers). For Prowler-specific API/SDK testing conventions, also use prowler-test-api or prowler-test-sdk.
Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Use when creating test data, building mock datasets, or generating sample data for development and demos.
Instrument Python LLM apps, build golden datasets, write eval-based tests, run them, and root-cause failures — covering the full eval-driven development cycle. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM, even if they don't say "evals" explicitly. Use for making sure an AI app works correctly, catching regressions after prompt changes, debugging why an agent started behaving differently, or validating output quality before shipping.
Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.
Guide for building high-quality MCP (Model Context Protocol) servers in Python or Node/TypeScript to integrate external APIs/services.
Use when adding login, logout, and user profile to a Flask web application using session-based authentication - integrates auth0-server-python for server-rendered apps with login/callback/profile/logout flows.
Build MCP servers in Python with FastMCP to expose tools, resources, and prompts to LLMs. Supports storage backends, middleware, OAuth Proxy, OpenAPI integration, and FastMCP Cloud deployment. Prevents 30+ errors. Use when: creating MCP servers, or troubleshooting module-level server, storage, lifespan, middleware, OAuth, background tasks, or FastAPI mount errors.