Skills real projects publish on GitHub, most starred first. Each one says what it will make an agent do before you copy it.
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Hugging FaceSkillhuggingface/transformers-mlinter/.ai/skills/release/SKILL.md
Cut a new transformers-mlinter release. Bumps the version across all pinned locations, updates the CHANGELOG, runs local checks and a packaged smoke test, drives the tag-based GitHub Actions publish to PyPI, then opens the next development version on main. Use when asked to release, cut a version, or ship X.Y.Z.
Often used withcreate-agent-adapterdocumentation-consistency
Hugging FaceSkillhuggingface/transformers-mlinter/.ai/skills/remove-mlinter-rule/SKILL.md
Retire a TRF rule from the mlinter. Marks the rule deprecated in rules.toml, deletes its module and tests, and records the removal in the CHANGELOG. Use when asked to remove, retire, drop, or delete a rule.
Hugging FaceSkillhuggingface/harbor-hf/.agents/skills/harbor-hf/SKILL.md
Submit, monitor, pause, resume, cancel, and inspect Harbor benchmark runs through the hosted Harbor-HF control service and Hugging Face Jobs.
Hugging FaceSkillhuggingface/harbor-hf/.agents/skills/project-authorization/SKILL.md
Ask for project approval before starting repository work, record the approved scope in the control-plane project file indexed by canonical repository slug, and recover authorization after compaction or session changes. Use before implementing, deploying, publishing, merging, spending, moving credentials, cutting over, or retiring resources for a repository.
Hugging FaceReads credentialsSkillhuggingface/mlclaw/.agents/skills/mlclaw/SKILL.md
Use when setting up, operating, migrating, repairing, or explaining an OpenClaw deployment on Hugging Face with the ML Claw `mlclaw` CLI. Covers the browser Space gateway, Hugging Face OAuth, local gateway mode, private Storage Buckets, Telegram as an optional connector, Docker context pinning, model selection through the Hugging Face Router, OpenAI API key setup, costs, diagnostics, and state safety.
Hugging FaceSkillhuggingface/mlclaw/assets/hf-tooling/skills/hf-broker/SKILL.md
Use ML Claw's HF Broker for protected Hugging Face repository and bucket reads, writes, temporary grants, recovery, and revocation. Use instead of asking for or exposing a Hugging Face access token.
Hugging FacePipes a download into a shellSkillhuggingface/mlclaw/assets/hf-tooling/skills/hf-cli/SKILL.md
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`.
Often used withhuggingface-local-models
Hugging FaceSkillhuggingface/mlclaw/assets/hf-tooling/skills/huggingface-best/SKILL.md
Use 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]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.
Hugging FaceSkillhuggingface/mlclaw/assets/hf-tooling/skills/huggingface-spaces/SKILL.md
Build, 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 Hugging Face, port code onto ZeroGPU, fix a Space that won't build or run, or otherwise work with `hf spaces …`, `@spaces.GPU`, Space README frontmatter, or the `spaces` Python package.
Hugging FaceSkillhuggingface/transformers-mic/.ai/skills/release/SKILL.md
Cut a transformers-mic (tmic) release to PyPI. Updates CHANGELOG.md and the single pyproject version, runs the tests and a packaged smoke test, pushes the vX.Y-release branch and, after confirmation, the vX.Y.Z tag that publishes through GitHub OIDC, then opens the next version on main. Use when asked to release tmic, cut a version, or ship X.Y.Z.
Often used withcreate-agent-adapterdocumentation-consistency
Hugging FaceReads credentialsSkillhuggingface/research-agent/.fast-agent/skills/hf-space-deployer/SKILL.md
Deploy fast-agent MCP Servers to Hugging Face Spaces using Docker. Use when the user wants to deploy an "agent card" as an MCP Server. Includes templates and CLI commands for deploying agent cards with custom tools to HF Spaces.
Hugging FaceSkillhuggingface/research-agent/research/skills/birch-html/SKILL.md
Use this skill when the user wants a polished, shareable, source-grounded, self-contained HTML artifact in the Birch visual system for engineering, product, planning, review, status, incident, process, codebase, data, or benchmark communication. Trigger for one-pagers, visual summaries, reports, dashboards, module/process explainers, implementation plans, design-direction comparisons, PR/change writeups, findings-first code reviews, incident/status reports, briefing decks, flow diagrams, numeric/data briefs, model/run/token/ time/cost reports, and design-system references. Do not use it for editing production web apps, React/Vue components, or ordinary chat answers.
Hugging FaceSkillhuggingface/swarmlab/skill/SKILL.md
Run a swarmlab multi-agent experiment end to end with the swarmlab CLI. Use when asked to design, smoke, launch (locally or on HF Jobs), analyse, report on, or publish a swarmlab experiment, or to resume or fork a swarmlab run.
Hugging FaceReads credentialsSkillhuggingface/swarm-sweeper/skills/farmer-setup/SKILL.md
Set up slop-farmer for a GitHub repository end-to-end. Use this whenever the user mentions slop-farmer setup, creating a repo config, choosing scrape limits, checking GitHub rate limits, cleaning PR template boilerplate, inspecting issue/PR title patterns with gh, installing or authenticating the Hugging Face hf CLI, publishing datasets, reproducing dashboards, or deploying the static dashboard to a Hugging Face Space. Be proactive even if the user only asks for one piece of the setup, because config, auth, dataset publishing, and dashboard deployment are tightly coupled here.
Hugging FaceSkillhuggingface/funes-integrations/claude/claude-plugin/funes/skills/funes/SKILL.md
Persistent memory over the user's past AI coding sessions, searched and read through the funes MCP tools. Use when the user refers to earlier work, asks what memory is available, or when a past session may already have settled the question.
Hugging FaceSkillhuggingface/space-demo-kit/skills/space-demo-video/SKILL.md
Create a polished social demo video (MP4, 4:3, ~10s) for any Hugging Face Space with the space-demo-kit renderer. Use whenever the user asks for a demo, promo, showcase, or social video of a HF Space or model. Covers template selection (i2v, t2v, edit, avatar, a2a, gallery, vqa), manifest schema, live asset capture, rendering, verification, and delivery.
Hugging FaceSkillhuggingface/ipyh-optimization/.claude/skills/optimize-harness/SKILL.md
Optimize an ipython-harness (ipyh) harness for a suite of tasks (e.g. Harbor tasks) with ipyh-optimize, Harness²-style and without rollouts, playing the INV editor, DOM editor, composer and reflector roles in this session. Use when asked to optimize, tune or improve a harness for a set of tasks or a benchmark, or to build an ipyh harness folder for one.
A folder with a SKILL.md file: a name, a description of when to use it, and instructions. Claude loads a skill only when the task matches its description.
Copy the folder into your project's .claude/skills/ directory, or into your own skills folder to use it everywhere.
We read each file for commands that read secrets, delete things or pipe downloads into a shell, and say so before you copy it. No warning is not a promise that a file is safe.
Open a skill to see its discussion. Reports from people and their agents are coming.
