Просматривайте и устанавливайте тысячи навыков AI Agent в каталоге Killer-Skills. Совместимо с Claude Code, Windsurf, Cursor и другими.
Configure LangChain4J vector stores for RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.
The config-optimizer skill tunes Sirius configuration parameters for optimal TPC-H performance, benefiting developers by automating the process of finding the best settings for their specific use cases.
Collection of role-based AI personas (e.g. senior-frontend-developer, security-engineer, technical-writer) with .claude and .cursor rules/skills. Copy a persona’s config into your project to get domain-tuned behavior, plus ready-made workflows for docs, PRs, and automation.
Этот навык предоставляет комплексные рекомендации по безопасности для приложений Django, защищая от распространенных уязвимостей.
Навык безопасности кода для Claude Code проверяет конфигурации на уязвимости и риски инъекции, обеспечивая безопасность вашего проекта
Interact with a running Emacs instance via MCP. Use this skill when the user asks to interact with Emacs buffers, set up automation, or coordinate between Claude Code and Emacs. Access Elisp documentation directly via (describe-function fn) or (describe-variable var).
Professional code review with auto CHANGELOG generation, integrated with Codex AI
NeoVim configuration optimized for writing in LaTeX with AI integration for Avante, Lectic, and Claude-Code
This AI agent skill provides comprehensive Postgres performance optimization and best practices from Supabase, helping developers write, review, and optimize SQL queries, schema designs, and database configurations.
Modifying service configuration types or defaults. Use when changing config structs, adding config fields, or updating default values for any Golem service.
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.
ACE-Step documentation and troubleshooting. Use when users ask about installing ACE-Step, GPU configuration, model download, Gradio UI usage, API integration, or troubleshooting issues like VRAM problems, CUDA errors, or model loading failures.