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Просматривайте и устанавливайте тысячи навыков AI Agent в каталоге Killer-Skills. Совместимо с Claude Code, Windsurf, Cursor и другими.

166 доступные навыки

hugging-face-jobs

[ Официальный ]
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huggingface

This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.

decomplect-py

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zby

Architectural code analysis for Python design quality. Evaluates simplicity (Rich Hickey), functional core/imperative shell (Gary Bernhardt), and coupling (Constantine & Yourdon). Use for design review or architectural assessment of Python code.

nock-interpreter-engineer-assistant

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toplyr-narfur

Expert Nock interpreter builder for implementing virtual machines in C, Python, Rust, Haskell, or JavaScript. Use when building Nock interpreters, porting between languages, implementing evaluation loops, or understanding Nock runtime behavior.

pants-format-check

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RedHat-UX

Runs pants formatting, linting, and type checking on Python code, fixing issues automatically. Use when finishing implementation, before committing code, or when the user asks to format, lint, or check code quality.

ai-context-repository

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BenWeatherall

Guides the ai-context-writer subagent in maintaining AI_CONTEXT_REPOSITORY.md, documenting repository architecture, directory structure, component responsibilities, data flow, and extension points for the python-vis project. Use when creating or updating the repository AI context file.

MCP Builder

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majiayu000

Comprehensive guide for building production-ready MCP (Model Context Protocol) servers. Covers both FastMCP (Python) and MCP SDK (Node/TypeScript) implementations with practical examples, best practices, error handling, testing strategies, security guidelines, and real-world integration patterns.

n8n-workflow-architect

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alexadark

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.

implement-flet-extension

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flet-dev

Implement a new Flet extension/control that wraps a third-party Flutter package end-to-end, including dependency selection, version pinning, compatibility checks, Python/Flutter integration, docs, examples, tests, and CI updates. Use when adding any flet_* package backed by an external pub.dev package.

n8n-workflow-architect

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Brmbobo

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.

create-mcp-servers

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majiayu000

Create Model Context Protocol (MCP) servers that expose tools, resources, and prompts to Claude. Use when building custom integrations, APIs, data sources, or any server that Claude should interact with via the MCP protocol. Supports both TypeScript and Python implementations.

create-mcp-servers

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glittercowboy

Create Model Context Protocol (MCP) servers that expose tools, resources, and prompts to Claude. Use when building custom integrations, APIs, data sources, or any server that Claude should interact with via the MCP protocol. Supports both TypeScript and Python implementations.

ros2-launch-system

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SARAMALI15792

Generate ROS 2 Python launch files and multi-node system configurations for educational content. This skill should be used when creating lessons that teach launch file syntax, writing exercises involving multi-node startup, parameter configuration, or generating worked examples for robot system deployment.