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Found 2,396 Skills
Converts an arxiv paper into a minimal, citation-anchored Python implementation. Trigger when user runs /paper2code with an arxiv URL or paper ID, says "implement this paper", or pastes an arxiv link asking for implementation. Flags all ambiguities honestly. Never invents implementation details not stated in the paper.
Multi-language Workers development with Rust, Python, and WebAssembly. Use when building Workers in languages other than JavaScript/TypeScript, or when integrating WASM modules for performance-critical code.
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.
This skill should be used when the user requests to create professional business documents (proposals, business plans, or budgets) from templates. It provides PDF templates and a Python script for generating filled documents from user data.
Debugging techniques for Python, JavaScript, and distributed systems. Activate for troubleshooting, error analysis, log investigation, and performance debugging. Includes extended thinking integration for complex debugging scenarios.
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.
Reverse engineer web APIs by capturing browser traffic (HAR files) and generating production-ready Python API clients. Use when the user wants to create an API client for a website, automate web interactions, or understand undocumented APIs. Activate on tasks mentioning "reverse engineer", "API client", "HAR file", "capture traffic", or "automate website".
Debugs and resolves common uv issues. Learn to diagnose dependency resolution failures, handle version conflicts, fix cache problems, troubleshoot Python environment issues, optimize performance, and solve platform-specific problems. Use when uv commands fail, dependencies won't resolve, cache is corrupted, Python installation issues occur, or performance is slow.
Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like "Wrong output type returned", "No execution data available", "The response property should be a string, but it is an object", "Cannot assign to read only property 'name'", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead.
Python code-quality anti-patterns and review checks: exception-hierarchy correctness, singleton identity comparison, narrow exception handling, wildcard-import avoidance, magic-number naming, and dead-local removal. Use when reviewing or self-reviewing Python code for correctness and readability defects that linters and reviewers should catch.
Expert in high-performance CSV processing, parsing, and data cleaning using Python, DuckDB, and command-line tools. Use when working with CSV files, cleaning data, transforming datasets, or processing large tabular data files.
Develop ComfyUI server-side V3 custom nodes (Python) using Comfy API v0_0_2/latest, schema-based inputs/outputs, ComfyExtension entrypoints, and UI preview helpers. Use when asked to create or update ComfyUI custom_nodes, V3 nodes, or Comfy API-based nodepacks.