New Checked the same way as MCP servers
Agent Skills, and what they let an agent do
Read straight from each publisher's repository. For every skill: what it allows the agent to do, the scripts it ships, and what fixed checks matched. Nothing is run.
Skills from Hugging Face11
Clear filters- hf-cloud-aws-context-discoveryHugging FaceDiscover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS a…OfficialInstructions only1 finding
- hf-cloud-sagemaker-deployment-plannerHugging FacePlan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding …OfficialInstructions only
- hf-mcpHugging FaceUse Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.OfficialInstructions only
- hf-memHugging FaceHugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face HubOfficialInstructions only
- huggingface-bestHugging FaceUse when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "w…OfficialInstructions only
- huggingface-gradioHugging FaceBuild Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.OfficialInstructions only
- huggingface-spacesHugging FaceBuild, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hu…OfficialInstructions only
- huggingface-trackioHugging FaceTrack and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webho…OfficialInstructions only
- huggingface-zerogpuHugging FaceAI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pic…OfficialInstructions only
- transformers-jsHugging FaceUse Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio cl…OfficialInstructions only1 high finding
- trl-trainingHugging FacePost-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python API or the trl CLI.OfficialInstructions only
Labels come from the skill's own files, read on the date shown: the tools its frontmatter allows and the scripts it ships. They are not a safety rating, and no finding is not a safety guarantee. How skills are checked.