Model Choice logo

Model Choice

Organization
vstorm-co
model-choice

Pick a model for an agent by quality, speed, cost and where data may go - and say why.

Overview

Publishervstorm-co
Repositoryagenticos
Skill namemodel-choice
Stars
137
Forks
27
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vstorm-co on GitHub. Read the source before you install it.

Installation

Install the Model Choice AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/vstorm-co/agenticos/tree/main/backend/app/core/catalog/skill_gallery/software/model-choice
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vstorm-co/agenticos.git /tmp/agenticos
mkdir -p .claude/skills
cp -r /tmp/agenticos/backend/app/core/catalog/skill_gallery/software/model-choice .claude/skills/model-choice
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Model Choice in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Model Choice on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Model Choice is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Choosing a model

Look up current prices and models with web search before recommending one - they change monthly. Cite the page.

The four questions

  1. How hard is the job? Reasoning over several documents, writing code or planning steps needs a frontier model. Classifying, extracting or short FAQ answers run well on a small, cheap one.
  2. How fast must it answer? A chat widget wants a quick model; a nightly report does not care.
  3. How much will it run? Price × messages per month. Estimate it out loud.
  4. Where may the data go? Some companies need a model in their own region, their own cloud, or open weights they run themselves.

Recommend

One model, the reason in a sentence, and the cheaper fallback: "Claude Sonnet for the answers; Haiku would be a third of the cost if quality holds." Offer to switch later - the model is one setting.

Never

Recommend a model the organization has no key for without saying how to add one.

Frequently asked questions

What does the Model Choice AI skill do?

Pick a model for an agent by quality, speed, cost and where data may go - and say why.

Why use Model Choice on TypingMind?

Because you install it once and use it with any model. Model Choice is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Model Choice in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vstorm-co/agenticos/tree/main/backend/app/core/catalog/skill_gallery/software/model-choice. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Model Choice?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Model Choice?

As many as you like. As long as a model supports skills, you can use Model Choice with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Model Choice AI skill free?

Yes. It is published on GitHub by vstorm-co under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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