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Found 69 Skills
Entry point for 9Router — local/remote AI gateway with OpenAI-compatible REST for chat, image, TTS, embeddings, web search, web fetch. Use when the user mentions 9Router, NINEROUTER_URL, or wants AI without writing provider boilerplate. This skill covers setup + indexes capability skills; fetch the relevant capability SKILL.md from the URLs below when needed.
Transcribe audio and video files to text using a remote ASR service (Qwen3-ASR or OpenAI-compatible endpoint). Extracts audio from video, sends to configurable ASR endpoint, outputs clean text. Use when the user wants to transcribe recordings, convert audio/video to text, do speech-to-text, or mentions ASR, Qwen ASR, 转录, 语音转文字, 录音转文字, or has a meeting recording, lecture, interview, or screen recording to transcribe.
Generate images with Venice. Covers POST /image/generate (Venice-native), POST /images/generations (OpenAI-compatible), GET /image/styles (style presets), request fields (prompt, dimensions, cfg_scale, seed, variants, style_preset, aspect_ratio, resolution, safe_mode, watermark), and response formats.
Use Claude Code's full tool system with any OpenAI-compatible LLM — GPT-4o, DeepSeek, Gemini, Ollama, and 200+ models via environment variable configuration.
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.
Operate LM Studio's `lms` CLI and local/remote LM Studio servers for model discovery, server status checks, model loading, endpoint smoke tests, and downstream OpenAI-compatible wiring. Use when the user mentions LM Studio, `lms`, a local model server, `/v1/models`, a remote LM Studio host, or wants to connect another tool to LM Studio; even if they only ask to test a local OpenAI-compatible endpoint or choose the correct loaded-model identifier. Triggers on: lmstudio, lm studio, lms, local model server, LM Studio API, LM Studio endpoint, /v1/models, connect Strix to LM Studio, load model in LM Studio.
Serve a quantized or unquantized LLM checkpoint as an OpenAI-compatible API endpoint using vLLM, SGLang, or TRT-LLM. Use when user says "deploy model", "serve model", "start vLLM server", "launch SGLang", "TRT-LLM deploy", "AutoDeploy", "benchmark throughput", "serve checkpoint", or needs an inference endpoint from a HuggingFace or ModelOpt-quantized checkpoint. Do NOT use for quantizing models (use ptq) or evaluating accuracy (use evaluation).
Deploy and manage vLLM for high-throughput LLM inference. Configure continuous batching, tensor parallelism, quantization, and OpenAI-compatible API endpoints for production LLM serving.
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.
Serve a model with MAX's `max serve` command: set up the environment (pixi or uv with the max-nightly conda channel / nightly wheel index), point the server at a Hugging Face repo or local checkpoint, target a custom architecture with `--custom-architectures`, and pick the right serve flags for the model. Use this whenever the user wants to run, launch, start, or host a model on MAX, bring up an OpenAI-compatible endpoint, serve a custom/ported architecture, debug a `max serve` startup failure, or figure out which serve flags (devices, quantization-encoding, max-length, task, trust-remote-code) a given model needs, even if they don't say "max serve" by name.
Guide users through obtaining and configuring free API keys for LLM providers. Use when the user wants to set up a free LLM API, get a free API key, connect to a free model provider, configure an OpenAI-compatible endpoint at no cost, or asks about free tiers for AI models. Triggers on "free API key", "free LLM", "set up Gemini/Groq/Mistral/etc.", "which free provider", "how to get an API key", "free model access", "configure LLM for free".
See and understand images when you (the current model) have no native vision. Use this WHENEVER you need to look at, read, describe, OCR, or reason about the contents of an image, screenshot, photo, diagram, chart, UI mockup, or scanned page — including when the user references a local image file or an image URL and you cannot view it yourself. Also triggers on: 看图 / 识图 / 截图 / 图片内容 / OCR 文字识别 / 这张图是什么. Delegates the actual seeing to a configurable OpenAI-compatible vision model via a small script.