How do I install the Ryu Local Model skill?

Run npx skillmds@latest add amajorai/ryu-local-model in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Who published Ryu Local Model?

amajorai (@amajorai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Ryu Local Model by amajorai — Agent Skill

Name: Ryu Local Model
Author: amajorai

Ryu Local Model

Search, download, and serve a local GGUF model on a Ryu node via Core's models and engines REST surface. Covers catalog search and device-fit, installing a specific quantization, activating a model, and listing engines (the engine is derived from the model format). Use when a user wants to get a local model running on their node.

amajorai Updated Sep 21, 2026

File contents

Local models on Ryu

This skill manages local models on a Ryu node. If Ryu is not running, do [[setup-ryu]] first. Over MCP the same actions are ryu_search_models, ryu_get_active_model, ryu_set_active_model, and ryu_list_engines from [[ryu-mcp]].

Base URL is the Core node, default http://127.0.0.1:7980. The catalog is Hugging Face GGUF by default. The engine is derived from the model format, so for GGUF you normally just pick a model and Core runs it on the matching engine.

Search the catalog

GET /api/models/catalog with query params:

query - free-text search.
format - gguf (default), safetensors, or mlx.
sort - trending, downloads, likes, or recent.
limit - max results.
task - Hugging Face pipeline tag (for example text-generation, image-text-to-text).
author - filter by org.
installed_only - true to show only installed models.
cursor - pagination cursor for the next page.

curl -s "http://127.0.0.1:7980/api/models/catalog?query=llama&format=gguf&sort=trending&limit=10"

Each card carries compatible, needsEngine, params, context length, and tags so you can tell what will run on this node.

Inspect quantizations and device-fit

curl -s "http://127.0.0.1:7980/api/models/catalog/detail?id=<repo_id>&format=gguf"

This returns each downloadable GGUF file with a fit verdict (too_big, cpu, partial, ok, great, or unknown), human size, and quant label, computed against the node's detected hardware. Prefer ok or great for a responsive local experience.

Install a model file

Download one specific GGUF quantization through Core's verified downloader:

curl -s -X POST http://127.0.0.1:7980/api/models/catalog/install \
  -H 'content-type: application/json' \
  -d '{"id":"<repo_id>","file":"<filename.gguf>","format":"gguf"}'

To remove a downloaded file:

curl -s -X POST http://127.0.0.1:7980/api/models/catalog/uninstall \
  -H 'content-type: application/json' \
  -d '{"id":"<repo_id>","file":"<filename.gguf>"}'

Activate (serve) a model

POST /api/models/active switches the model the local chat stack serves. id is the local stem or HF repo id of an already-installed model; pass engine only to override the format-derived engine.

curl -s -X POST http://127.0.0.1:7980/api/models/active \
  -H 'content-type: application/json' \
  -d '{"id":"<repo_id_or_stem>"}'

Read the current selection:

curl -s http://127.0.0.1:7980/api/models/active

Engines

GET /api/engines - list runnable engines on this node.
GET /api/engine/active - the active engine.
GET /api/models/engines - engine availability keyed for the catalog.

Because the engine is derived from the model format, you rarely set it by hand: GGUF runs on the llama.cpp-class engine, while safetensors and MLX map to their own engines and may show compatible: false with a needsEngine label if that engine is not runnable here.

End-to-end

GET /api/models/catalog?query=...&format=gguf to find a model.
GET /api/models/catalog/detail?id=...&format=gguf to pick a quant that fits.
POST /api/models/catalog/install with that file.
POST /api/models/active with the model id.
Confirm with GET /api/models/active.

---name: ryu-local-modeldescription: Search, download, and serve a local GGUF model on a Ryu node via Core's models and engines REST surface. Covers catalog search and device-fit, installing a specific quantization, activating a model, and listing engines (the engine is derived from the model format). Use when a user wants to get a local model running on their node.---# Local models on RyuThis skill manages local models on a Ryu node. If Ryu is not running, do [[setup-ryu]] first. Over MCP the same actions are `ryu_search_models`, `ryu_get_active_model`, `ryu_set_active_model`, and `ryu_list_engines` from [[ryu-mcp]].Base URL is the Core node, default `http://127.0.0.1:7980`. The catalog is Hugging Face GGUF by default. The engine is derived from the model format, so for GGUF you normally just pick a model and Core runs it on the matching engine.## Search the catalog`GET /api/models/catalog` with query params:- `query` - free-text search.- `format` - `gguf` (default), `safetensors`, or `mlx`.- `sort` - `trending`, `downloads`, `likes`, or `recent`.- `limit` - max results.- `task` - Hugging Face pipeline tag (for example `text-generation`, `image-text-to-text`).- `author` - filter by org.- `installed_only` - `true` to show only installed models.- `cursor` - pagination cursor for the next page.```shcurl -s "http://127.0.0.1:7980/api/models/catalog?query=llama&format=gguf&sort=trending&limit=10"```Each card carries `compatible`, `needsEngine`, params, context length, and tags so you can tell what will run on this node.## Inspect quantizations and device-fit```shcurl -s "http://127.0.0.1:7980/api/models/catalog/detail?id=<repo_id>&format=gguf"```This returns each downloadable GGUF file with a fit verdict (`too_big`, `cpu`, `partial`, `ok`, `great`, or `unknown`), human size, and quant label, computed against the node's detected hardware. Prefer `ok` or `great` for a responsive local experience.## Install a model fileDownload one specific GGUF quantization through Core's verified downloader:```shcurl -s -X POST http://127.0.0.1:7980/api/models/catalog/install \ -H 'content-type: application/json' \ -d '{"id":"<repo_id>","file":"<filename.gguf>","format":"gguf"}'```To remove a downloaded file:```shcurl -s -X POST http://127.0.0.1:7980/api/models/catalog/uninstall \ -H 'content-type: application/json' \ -d '{"id":"<repo_id>","file":"<filename.gguf>"}'```## Activate (serve) a model`POST /api/models/active` switches the model the local chat stack serves. `id` is the local stem or HF repo id of an already-installed model; pass `engine` only to override the format-derived engine.```shcurl -s -X POST http://127.0.0.1:7980/api/models/active \ -H 'content-type: application/json' \ -d '{"id":"<repo_id_or_stem>"}'```Read the current selection:```shcurl -s http://127.0.0.1:7980/api/models/active```## Engines- `GET /api/engines` - list runnable engines on this node.- `GET /api/engine/active` - the active engine.- `GET /api/models/engines` - engine availability keyed for the catalog.Because the engine is derived from the model format, you rarely set it by hand: GGUF runs on the llama.cpp-class engine, while safetensors and MLX map to their own engines and may show `compatible: false` with a `needsEngine` label if that engine is not runnable here.## End-to-end1. `GET /api/models/catalog?query=...&format=gguf` to find a model.2. `GET /api/models/catalog/detail?id=...&format=gguf` to pick a quant that fits.3. `POST /api/models/catalog/install` with that file.4. `POST /api/models/active` with the model id.5. Confirm with `GET /api/models/active`.

Frequently asked questions