docker-model

docker-model is a skill for Claude Code from siva01c/claude-plugins. It costs 97 tokens per session (1,204 once invoked), scanned A, original, MIT.

A guide for running AI models on your own computer through Docker Model Runner, a Docker feature that downloads and serves models locally. It can provide an OpenAI-compatible connection for applications such as Drupal's AI module.

In plain words
What is it for?
Use it to download models from Docker Hub, other OCI registries, or Hugging Face; start interactive or one-off prompts; and connect local models to an application or Drupal.
Why use it?
It lets you develop with a local AI service without a remote API key or sending requests to an external provider. It also gives you commands for downloading, checking, and testing models.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the docker-tools plugin — 2 skills shipped together

Good fit Use it to download models from Docker Hub, other OCI registries, or Hugging Face; start interactive or one-off prompts; and connect local models to an application or Drupal.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/siva01c/claude-plugins/docker-model
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add siva01c/claude-plugins --skill docker-model
Clone the repo
git clone --depth 1 https://github.com/siva01c/claude-plugins

Made for: Claude Code.

Or install docker-tools, the plugin that ships this one along with the rest of its 2 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for docker-model

README.md
[![agentmods](https://agentmods.dev/badge/skills/siva01c/claude-plugins/docker-model/github.svg)](https://agentmods.dev/skills/siva01c/claude-plugins/docker-model)
Your own site
<a href="https://agentmods.dev/skills/siva01c/claude-plugins/docker-model"><img src="https://agentmods.dev/badge/skills/siva01c/claude-plugins/docker-model/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for docker-model

Your own site · 80×15
<a href="https://agentmods.dev/skills/siva01c/claude-plugins/docker-model"><img src="https://agentmods.dev/badge/skills/siva01c/claude-plugins/docker-model.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,204 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00097 $0.01204
Opus 5.5 $0.00039 $0.00482
Sonnet 5.5 $0.00019 $0.00241
Haiku 4.5 $0.00010 $0.00120

Measured 1mo ago against content hash c1a209276642, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

docker-model scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl http://localhost:12434/engines/v1/chat/completions \
docker-tools/skills/docker-model/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Docker Model Runner Skill

Docker Model Runner (DMR) manages and serves AI models through Docker Desktop or Docker Engine, exposing OpenAI-compatible APIs. Models are pulled as OCI artifacts from Docker Hub (ai/ namespace), any OCI registry, or Hugging Face, and stored locally. For Drupal work it provides a free, local, keyless backend for the AI module ecosystem during development.


Enabling

  • Docker Desktop: Settings → enable Docker Model Runner (Beta features).
  • Docker Engine (Linux): supported without Desktop; models are served on the host. GPU support: NVIDIA (CUDA), AMD (ROCm), Vulkan; Apple Silicon on macOS; CPU everywhere.

Core CLI

docker model status                      # is the runner active?
docker model pull ai/smollm2             # fetch a model (Docker Hub ai/ namespace)
docker model pull hf.co/bartowski/Llama-3.2-1B-Instruct-GGUF  # from Hugging Face
docker model list                        # local models
docker model run ai/smollm2 "Hello"      # one-shot prompt
docker model run ai/smollm2              # interactive chat (exit with /bye)
docker model configure --context-size 8192 ai/smollm2   # adjust context window
docker model inspect ai/smollm2          # model metadata
docker model logs                        # runner logs
docker model rm ai/smollm2               # delete local model

Run docker model --help for the full, current command list — the CLI is still evolving.


OpenAI-compatible API

Endpoint Method
/engines/v1/models GET
/engines/v1/chat/completions POST
/engines/v1/completions POST
/engines/v1/embeddings POST

Base URLs:

  • From the host: http://localhost:12434 (default TCP port)
  • From containers (Docker Desktop): http://model-runner.docker.internal
  • From containers (Docker Engine): http://172.17.0.1:12434
curl http://localhost:12434/engines/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model": "ai/smollm2", "messages": [{"role": "user", "content": "Hi"}]}'

Read the full file on GitHub · 138 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 138 lines · 97 tokens per session scan A c1a209276642

Subscribe to this mod's changes

docker-model is a skill published in the GitHub repository siva01c/claude-plugins (16 stars, last pushed 28d ago), licensed MIT. It adds 97 tokens to every session and 1,204 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

iflytek-image-understanding

An image-analysis tool that describes pictures and answers questions about what they contain. It uses an AI vision service, which interprets visual content rather than only reading text files.

iflytek/iFly-Skills · 61 tokens

image-prompt-builder-nl

Craft high-quality natural-language image prompts for any modern text-to-image or image-edit model that accepts flowing English. Trigger when the user wants help writing, rewriting, improving, or translating an English natural-language image prompt — including "write me an image prompt", "improve this image prompt"…

jim60105/copilot-prompt · 125 tokens

manus-prompt-engineering

Design and audit Manus prompts for engineering, release, production, and security work. Use when writing a Manus prompt or reviewing a Manus execution or recording against authorization and evidence.

JesseRaber/manus-prompt-engineering-skill · 41 tokens

ai-ethics-review

Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety…

mohitagw15856/pm-claude-skills · 88 tokens

ai-product-canvas

Structure AI and ML product decisions with the rigour of any product decision. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Produces a complete AI product canvas covering problem definition, model approach, data requirements, evaluation…

mohitagw15856/pm-claude-skills · 73 tokens

model-migration-plan

Plan the migration of an LLM feature from one model to another without breaking production. Use when a model is being deprecated, a newer model looks better or cheaper, or when asked how to upgrade models safely, run shadow traffic, or set rollback criteria for a model change. Produces a phased migration plan with…

mohitagw15856/pm-claude-skills · 99 tokens