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Jax Agents

Organization
VectorSpaceLab
jax-agents

Select, configure, and adapt Acme JAX agents and JAX experiment workflows.

Overview

PublisherVectorSpaceLab
RepositoryAREX-Skill
Skill namejax-agents
Stars
341
Forks
26
Bundled files
5
LicenseApache-2.0
Links
Skill sourceRepository
  • 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.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by VectorSpaceLab on GitHub. Read the source before you install it.

Installation

Install the Jax Agents 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/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/acme/sub-skills/jax-agents
  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/VectorSpaceLab/AREX-Skill.git /tmp/AREX-Skill
mkdir -p .claude/skills
cp -r /tmp/AREX-Skill/skills/repositories/repo-skills/acme/sub-skills/jax-agents .claude/skills/jax-agents
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jax Agents 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 Jax Agents 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 Jax Agents 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.

Acme JAX Agents

Use this sub-skill when the task is to choose, configure, or adapt acme.agents.jax algorithms or acme.jax.experiments runners for continuous-control, discrete-control, offline RL, imitation, learning-from-demonstrations, model-based, or decentralized multiagent workflows.

Quick Routing

  • Start with references/agent-catalog.md to choose the JAX algorithm family from task signals such as action space, online vs offline data, demonstrations, model-based planning, and multiagent structure.
  • Use scripts/select_jax_agent.py for a safe local recommendation helper; it uses only Python standard-library imports and --help does not import Acme.
  • Use references/experiment-workflows.md to build ExperimentConfig or OfflineExperimentConfig, switch between local and Launchpad distributed execution, add evaluators, checkpointing, or offline datasets.
  • Use references/api-reference.md for import paths, config classes, builder classes, network factories, experiment runner signatures, actor utilities, and saving helpers.
  • Use references/troubleshooting.md before diagnosing dependency imports, JAX/JAXLIB wheels, Launchpad/Reverb/TF extras, PRNG handling, spec/network mismatches, and expensive examples.

Boundaries

  • Route generic acme.EnvironmentLoop, environment wrappers, logging loops, and package-level setup to the Acme core workflows skill.
  • Route replay table, adders, dataset iterator, TFDS/RLDS, and Reverb data-pipeline internals to the replay/data skill unless the issue is selecting a JAX builder or offline experiment shape.
  • Route TensorFlow agent selection or acme.agents.tf.* code to the TF agents skill.
  • Do not require users to inspect Acme source docs, examples, or tests at runtime; the API names and workflow patterns needed for JAX agent adaptation are distilled in the bundled references.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Jax Agents AI skill do?

Select, configure, and adapt Acme JAX agents and JAX experiment workflows.

Why use Jax Agents on TypingMind?

Because you install it once and use it with any model. Jax Agents 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 Jax Agents in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/acme/sub-skills/jax-agents. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Jax Agents?

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 Jax Agents?

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

Is the Jax Agents AI skill free?

Yes. It is published on GitHub by VectorSpaceLab 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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