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Agent skill

Models

by guaardvark in guaardvark/guaardvark

Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request.

MITAuto-check passedAI & LLM Engineering

Install Models

skills CLI
$ npx skills add guaardvark/guaardvark --skill models -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install guaardvark/guaardvark models --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/guaardvark/guaardvark.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/models .claude/skills/models && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
models
GitHub stars
255
Token cost
~782 tokens
SKILL.md length
349 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request.

  • Works in 4 steps: Inspect: POST… → Show that to the user: which file(s),… → Register (and optionally install) with… → …
  • The user pastes a huggingface.co link
  • SKILL.md covers What is there, Add from a Hugging Face URL…, Using a user LoRA and Rules
  • Reaches huggingface.co; needs HF_TOKEN

What it does

Models is an agent skill from guaardvark/guaardvark. Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request. Use when the user pastes a huggingface.co link or a .safetensors URL, asks "can it run <model", or wants a new LoRA or checkpoint available in the Studio.

Its SKILL.md is about 780 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Model hubs and datasets, Fine-tuning and Diffusion and image models. It works with Hugging Face and Model Context Protocol. The repository describes itself as: The self-hosted AI studio: local video, image, music, voice, LoRA training, coding swarms, RAG and screen agents on one GPU, driven from the Studio or by your coding agent… The licence is MIT.

When your agent uses it

  • The user pastes a huggingface.co link
  • A .safetensors URL
  • Asks can it run <model
  • Wants a new LoRA

Example prompts

  • “can it run <model”
  • “/models”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Inspect: POST $B/api/batch-video/models/from-hf {"url": "https://huggingface.co//"}
  2. Show that to the user: which file(s), role, family, size, licence.
  3. Register (and optionally install) with POST $B/api/batch-video/models/user (or batch-image)
  4. Remove: DELETE .../models/user/ with {"delete_files": true|false}.

What it can do on your machine

Read from SKILL.md and the folder at commit f022ceb. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • huggingface.co

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • HF_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Models loads about 782 tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 349 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~782

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from guaardvark/guaardvark at commit f022ceb, republished under its MIT licence (© guaardvark). 349 words, ~782 tokens.

Download SKILL.mdSave it as .claude/skills/models/SKILL.md (or your agent's skills folder).
name
models
description
Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request. Use when the user pastes a huggingface.co link or a .safetensors URL, asks "can it run <model>", or wants a new LoRA or checkpoint available in the Studio.

Models and LoRAs with Guaardvark

B=${GUAARDVARK_URL:-http://localhost:5000}. Nothing downloads without an explicit Install; the product never phones home on its own. Always confirm the size and the licence with the user first.

What is there

  • Video: GET $B/api/batch-video/models (registry + user catalog, with is_downloaded / is_ready, missing_files, capabilities).
  • Image: GET $B/api/batch-image/models.
  • Download a registry model: POST $B/api/batch-video/models/download {"model_id": "wan22-14b"} / POST $B/api/batch-image/models/download {"model_path": "<id>"}; progress at GET .../models/download-status.
  • Chat photo-tool packs install from Manage Image Models → Image editing: qwen-image-edit (~28 GB with its encoder and VAE), flux-kontext-dev, pulid-flux (with its face files, EVA02-CLIP and flux-dev), bgremove-birefnet / bgremove-u2net. The rows come back as editing in GET $B/api/batch-image/models; Install with POST $B/api/batch-image/models/download {"model_path": "comfy:<pack id>"}. Confirm size and licence; never start those downloads unless the user asked.
  1. Inspect: POST $B/api/batch-video/models/from-hf {"url": "https://huggingface.co/<org>/<repo>"} (or the batch-image twin). The server reads the repo and returns what it found: files, revision, the likely role (checkpoint, LoRA, VAE, text encoder), family, whether a model_index exists, and a proposed catalog entry.
  2. Show that to the user: which file(s), role, family, size, licence.
  3. Register (and optionally install) with POST $B/api/batch-video/models/user (or batch-image) sending the entry back. role and family (image) or like (video) decide where the Studio offers it. The server re-inspects the repo; do not send has_model_index from the client. Gated repos need HF_TOKEN; confirm size and licence from the Look-up response first.
  4. Remove: DELETE .../models/user/<model_id> with {"delete_files": true|false}.

Using a user LoRA

  • Batch image: adapters: [{"id": "<user model id>", "scale": 0.8}] on /generate/prompts.
  • Batch video: lora_name + lora_strength, or adapters on /generate/text.
  • A trained Cast LoRA is different: it rides on subject_ids (the cast skill).

Rules

  • A direct .safetensors URL works when it lives on huggingface.co; the inspector needs the repo to read the file list. For other hosts, ask the user to download the file and drop it in the Studio's model folder instead.
  • Declared limits (min steps, max frames) come from the registry entry; a user model inherits them from like/family. Do not invent numbers for a model the registry does not know.

© guaardvark, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/models of guaardvark/guaardvark.

Open the folder on GitHubat commit f022ceb

Compare with similar skills

Models next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Models compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Models this skillguaardvark/guaardvark255—~782Automated safety check: PassMIT
Hugging Face LLM Trainerhuggingface/skills11k3 repos~7.2kAutomated safety check: PassApache-2.0
Discover MLrand/cc-polymath1811 repos~574Automated safety check: PassMIT
Model Registryartokun/comfyui-mcp795—~2.1kAutomated safety check: PassMIT
Dataset Transformationawslabs/agent-plugins9152 repos~3.5kAutomated safety check: PassApache-2.0
Hugging Face Vision Trainerhuggingface/skills11k1 repos~7.5kAutomated safety check: PassApache-2.0

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  • Cast

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  • Image

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  • Music

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  • Ops

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Works with

Categories

Questions about Models

What does Models do?

Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request. Models is an agent skill from guaardvark/guaardvark. Add any Hugging Face image or video model, checkpoint or LoRA to Guaardvark from a URL, list what is installed, and download registry models on request.

When should I use Models?

Models fits situations like: the user pastes a huggingface.co link; A .safetensors URL; asks can it run <model; wants a new LoRA.

How do I install Models in Claude Code?

Run `npx skills add guaardvark/guaardvark --skill models -a claude-code`. Or copy the skill folder (.agents/skills/models in guaardvark/guaardvark) into .claude/skills/models in your project. Claude Code loads it when a task matches its description.

How do I install Models in Codex?

Run `npx skills add guaardvark/guaardvark --skill models -a codex`. Or copy the skill folder (.agents/skills/models in guaardvark/guaardvark) into .agents/skills/models in your project. Codex loads it when a task matches its description.

Can I use Models in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add guaardvark/guaardvark --skill models -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/models, .gemini/skills/models, .github/skills/models and .opencode/skills/models in your project.

What does Models need to run?

Going by SKILL.md and its folder, Models needs credentials named HF_TOKEN.

Does Models access the network?

SKILL.md names 1 domain. In commands or code: huggingface.co; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Models safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Models use?

Models is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Models use?

About 782 tokens (SKILL.md is roughly 3.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Models?

Skills that share tags, products or a category with Models: Hugging Face LLM Trainer (huggingface/skills, 11k stars), Discover ML (rand/cc-polymath, 181 stars), Model Registry (artokun/comfyui-mcp, 795 stars) and Dataset Transformation (awslabs/agent-plugins, 915 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Models?

guaardvark (a GitHub user) maintains it in guaardvark/guaardvark, which has 255 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 7, 2026.

Source: guaardvark/guaardvark on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.