By JohnyGer
Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub
Track 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 webhooks, HF Space syncing, and JSON output for automation.
Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.
Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.
Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.
Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.
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 Agent Skills 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 hf-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 johnyger/skills --plugin huggingface-vision-trainerCore Hugging Face Hub operations through the hf CLI, including skill installation, repo management, jobs, datasets, models, Spaces, and discovery.
Open-source, local-first Claude Code plugin for token reduction, context compression, and cost optimization using hybrid RAG retrieval (BM25 + vector search), reranking, AST-aware chunking, and compact context packets.
Intelligent draw.io diagramming plugin with AI-powered diagram generation, multi-platform embedding (GitHub, Confluence, Azure DevOps, Notion, Teams, Harness), conditional formatting, live data binding, and MCP server integration for programmatic diagram creation and management.
Complete creative writing suite with 10 specialized agents covering the full writing process: research gathering, character development, story architecture, world-building, dialogue coaching, editing/review, outlining, content strategy, believability auditing, and prose style/voice analysis. Includes genre-specific guides, templates, and quality checklists.
TypeScript/JavaScript full-stack development with NestJS, React, and React Native
Write SQL, explore datasets, and generate insights faster. Build visualizations and dashboards, and turn raw data into clear stories for stakeholders.