By merveenoyan
Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub
Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
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.
External network access
Connects to servers outside your machine
Uses power tools
Uses Bash, Write, or Edit tools
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Hugging Face Skills are definitions for AI/ML tasks like dataset creation, model training, and evaluation. They are interoperable with all major coding agent tools like OpenAI Codex, Anthropic's Claude Code, Google DeepMind's Gemini CLI, and Cursor.
The Skills in this repository follow the standardized format Agent Skill format.
In practice, skills are self-contained folders that package instructions, scripts, and resources together for an AI agent to use on a specific use case. Each folder includes a SKILL.md file with YAML frontmatter (name and description) followed by the guidance your coding agent follows while the skill is active.
[!NOTE] 'Skills' is actually an Anthropic term used within Claude AI and Claude Code and not adopted by other agent tools, but we love it! OpenAI Codex uses the open Agent Skills format, where each skill is a directory with a
SKILL.mdfile that Codex discovers from standard.agents/skillslocations documented in the Codex Skills guide. Codex can also work with anAGENTS.mdfile. Google Gemini uses 'extensions' to define the instructions for your coding agent in agemini-extension.jsonfile. This repo is compatible with all of them, and more!
[!TIP] If your agent doesn't support skills, you can use
agents/AGENTS.mddirectly as a fallback.
Hugging Face skills are compatible with Claude Code, Codex, Gemini CLI, and Cursor.
/plugin marketplace add huggingface/skills
/plugin install <skill-name>@huggingface/skills
For example:
/plugin install hugging-face-cli@huggingface/skills
Copy or symlink any skills you want to use from this repository's skills/ directory into one of Codex's standard .agents/skills locations (for example, $REPO_ROOT/.agents/skills or $HOME/.agents/skills) as described in the Codex Skills guide.
Once a skill is available in one of those locations, Codex will discover it using the Agent Skills standard and load the SKILL.md instructions when it decides to use that skill or when you explicitly invoke it.
If your Codex setup still relies on AGENTS.md, you can use the generated agents/AGENTS.md file in this repo as a fallback bundle of instructions.
This repo includes gemini-extension.json to integrate with the Gemini CLI.
Install locally:
gemini extensions install . --consent
or use the GitHub URL:
gemini extensions install https://github.com/huggingface/skills.git --consent
This repository includes Cursor plugin manifests:
.cursor-plugin/plugin.json.mcp.json (configured with the Hugging Face MCP server URL)Install from repository URL (or local checkout) via the Cursor plugin flow.
For contributors, regenerate manifests with:
./scripts/publish.sh
This repository contains a few skills to get you started. You can also contribute your own skills to the repository.
npx claudepluginhub merveenoyan/skillsCore Hugging Face Hub operations through the hf CLI, including skill installation, repo management, jobs, datasets, models, Spaces, and discovery.
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