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Found 1,567 Skills
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.
Validate Python code quality with formatting, type checking, linting, and security analysis. Use for Python codebases to ensure PEP 8 compliance, type safety, and code quality.
Expert-level Django development for robust Python web applications with ORM, admin, and authentication
Expert-level Python development with Python 3.12+ features, async/await, type hints, and modern best practices
Strategic automation architecture advisor. Use when users want to plan automation solutions, evaluate their tech stack (Shopify, Zoho, HubSpot, etc.), decide between n8n vs Python/Claude Code, or need guidance on production-ready automation design. Invokes plan mode for complex architectural decisions.
Invoke IMMEDIATELY via python script when user requests refactoring analysis, technical debt review, or code quality improvement. Do NOT explore first - the script orchestrates exploration.
Analyze animated GIF files by extracting and viewing frames as sequential video. Use when: - User mentions a GIF file path (e.g., "./demo.gif", "~/Downloads/animation.gif") - User wants to analyze or understand a GIF animation - User asks about motion, changes, or content in a GIF - User attaches or references a .gif file for analysis - User wants to examine a screen recording in GIF format - User invokes /gif slash command Keywords: "GIF", ".gif", "animation", "animated", "frames", "screen recording", "analyze gif", "gif analysis", "view gif", "gif content", "gif motion" Trigger patterns: - Natural language: "Analyze this GIF: ./demo.gif" - Slash command: `/gif <path>` or `/gif <path> <message>` When triggered, extract frames using the Python script, view frames in order, and interpret as continuous video sequence.
Apply production-ready Databricks SDK patterns for Python and REST API. Use when implementing Databricks integrations, refactoring SDK usage, or establishing team coding standards for Databricks. Trigger with phrases like "databricks SDK patterns", "databricks best practices", "databricks code patterns", "idiomatic databricks".
Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.
Setup and validate Python virtual environments (venv, virtualenv, conda). Use to ensure isolated dependencies and correct Python versions for projects.
Production-grade Docker containerization for Python and Node.js applications. This skill should be used when users ask to containerize applications, create Dockerfiles, dockerize projects, or set up Docker Compose. Auto-detects project structure, analyzes .env for secrets, validates security, and generates tested Dockerfiles.
Build AI copilots, chatbots, and agentic UIs in React and Next.js using CopilotKit. Use this skill when the user wants to add an AI assistant, copilot, chat interface, AI-powered textarea, or agentic UI to their app. Covers setup, hooks (useCopilotAction, useCopilotReadable, useCoAgent, useAgent), chat components (CopilotPopup, CopilotSidebar, CopilotChat), generative UI, human-in-the-loop, CoAgents with LangGraph, AG-UI protocol, MCP Apps, and Python SDK integration. Triggers on CopilotKit, copilotkit, useCopilotAction, useCopilotReadable, useCoAgent, useAgent, CopilotRuntime, CopilotChat, CopilotSidebar, CopilotPopup, CopilotTextarea, AG-UI, agentic frontend, in-app AI copilot, AI assistant React, chatbot React, useFrontendTool, useRenderToolCall, useDefaultTool, useCoAgentStateRender, useLangGraphInterrupt, useCopilotChat, useCopilotAdditionalInstructions, useCopilotChatSuggestions, useHumanInTheLoop, CopilotTask, copilot runtime, LangGraphAgent, BasicAgent, BuiltInAgent, CopilotKitRemoteEndpoint, A2UI, MCP Apps, AI textarea, AI form completion, add AI to React app.