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Found 19 Skills
Use this if the user wants to connect to Home Assistant or leverage Home Assistant in any shape or form inside their project. Guide users integrating Home Assistant into projects for home automation control or data ingestion. Collects and validates connection credentials (URL and Long-Lived Access Token), provides API reference documentation for Python and Node.js implementations, and helps integrate Home Assistant APIs into user projects.
Run vLLM performance benchmark using synthetic random data to measure throughput, TTFT (Time to First Token), TPOT (Time per Output Token), and other key performance metrics. Use when the user wants to quickly test vLLM serving performance without downloading external datasets.
This is a skill for benchmarking the efficiency of automatic prefix caching in vLLM using fixed prompts, real-world datasets, or synthetic prefix/suffix patterns. Use when the user asks to benchmark prefix caching hit rate, caching efficiency, or repeated-prompt performance in vLLM.
Deploy vLLM using Docker (pre-built images or build-from-source) with NVIDIA GPU support and run the OpenAI-compatible server.
Deploy vLLM to Kubernetes (K8s) with GPU support, health probes, and OpenAI-compatible API endpoint. Use this skill whenever the user wants to deploy, run, or serve vLLM on a Kubernetes cluster, including creating deployments, services, checking existing deployments, or managing vLLM on K8s.
Orienta sobre a Lei Geral de Proteção de Dados (LGPD – Lei 13.709/2018) do Brasil. Use quando o usuário mencionar LGPD, proteção de dados no Brasil, privacidade de dados, bases legais, direitos do titular, ANPD, dados sensíveis, consentimento ou conformidade com a lei brasileira de dados.
Quick install and deploy vLLM, start serving with a simple LLM, and test OpenAI API.
Benchmark vLLM or OpenAI-compatible serving endpoints using vllm bench serve. Supports multiple datasets (random, sharegpt, sonnet, HF), backends (openai, openai-chat, vllm-pooling, embeddings), throughput/latency testing with request-rate control, and result saving. Use when benchmarking LLM serving performance, measuring TTFT/TPOT, or load testing inference APIs.
Facilitates structured brainstorming sessions, conducts comprehensive research, and generates creative solutions using proven frameworks. Trigger keywords - brainstorm, ideate, research, SCAMPER, SWOT, mind map, creative, explore ideas, market research, competitive analysis, innovation, problem solving, feature generation
Coin comparison. Use this skill whenever the user asks to compare two or more coins. Trigger phrases include: compare, versus, vs, which is better, difference. MCP tools: info_marketsnapshot_get_market_snapshot, info_coin_get_coin_info per coin (or batch/search when available).
Teaches how to interact with the Ray application. This skill should be used when users want to interact with Ray through a coding agent or LLM with skills capabilities.
Use when synthesizing multiple sources into coherent knowledge bases, performing multi-source analysis, or creating topic expertise from URLs and files. Also use when encountering content integration tasks requiring connections across disparate materials.