Wandb Autoresearch

Organization

wandb

wandb-autoresearch

Run bounded, evidence-driven training research through W&B Launch: assess project readiness, establish launchable code and queue capacity, smoke-test real jobs, execute serial trials, compare metrics, and persist resumable research state. Use when a coding agent is asked to autonomously test training hypotheses or tune a real W&B-tracked workload.

Overview

Publisher	wandb
Repository	`skills`
Skill name	`wandb-autoresearch`
Stars	74
Forks	3
Bundled files	5
License	Apache-2.0
Links	Skill source Repository

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 wandb on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/wandb/skills/tree/main/skills/wandb-autoresearch
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.

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/wandb/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/wandb-autoresearch .claude/skills/wandb-autoresearch

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wandb Autoresearch 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 Wandb Autoresearch 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 Wandb Autoresearch 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.

W&B autoresearch

Use W&B Launch to execute real training experiments, read their results, and choose the next bounded trial. Do not create a local wandb.init() run as a substitute for compute that was supposed to run through Launch.

The Launch implementation lives in skills/wandb-primary:

skills/wandb-primary/scripts/launch_helpers.py
the Launch section in skills/wandb-primary/SKILL.md

Install missing packages explicitly with uv; do not assume a fixed working directory or preinstalled environment.

Flow

Read only the reference for the current stage:

Stage	Entry condition	Read
Understand	Always first; inspect launchable code, queue capacity, data location, and prior state	`references/understand.md`
Set up	Launchable code or usable queue capacity is missing	`references/setup.md`
Search	Launchable code and queue capacity both exist	`references/search.md`

The readiness gate is launchable code + queue with usable capacity. A dataset may be a versioned Artifact or may be supplied by the code/image; its storage form alone does not determine readiness.

Experiment records

Use each W&B object for one job:

Runs hold trial config, metrics, system metrics, status, and code/job lineage.
Job or code Artifacts make code relaunchable.
Dataset Artifacts provide versioned inputs when the workload needs them.
Launch queues and agents provide compute.
A small local markdown file holds the hypothesis, trial tally, decisions, queue, and next step.

Keep local state at a user-visible path in the current project or a path the user supplied. Sync it to a W&B Artifact only when cross-session resume is useful and the user authorizes the write:

bash
S=skills/wandb-autoresearch/scripts/autoresearch_state.py
uv run --with wandb python "$S" load ENTITY PROJECT --dest .
uv run --with wandb python "$S" save ENTITY PROJECT --path AUTORESEARCH_STATE.md

Compute safety

Confirm the queue, metric direction, search axis, and trial/compute budget before the first non-smoke launch. Do not exceed the agreed budget.
Smoke-test the real job at a deliberately small setting before full trials.
Change only config fields the program actually reads. Use a code edit and a new job Artifact for architecture or pipeline changes.
Run trials serially unless the user explicitly authorizes parallel compute. Inspect each completed result before selecting the next trial.
Report failures, hardware utilization, and uncertainty. Re-run a likely winner with another seed when the apparent gap could be noise.
Never fabricate a run, metric, queue result, or completion state.

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 Wandb Autoresearch AI skill do?

Why use Wandb Autoresearch on TypingMind?

Because you install it once and use it with any model. Wandb Autoresearch 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 Wandb Autoresearch in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wandb/skills/tree/main/skills/wandb-autoresearch. 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 Wandb Autoresearch?

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 Wandb Autoresearch?

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

Is the Wandb Autoresearch AI skill free?

Yes. It is published on GitHub by wandb 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

W&B autoresearch

Flow

Experiment records

Compute safety

Bundled files

Frequently asked questions

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