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Scienceworld Tool Fetcher

OrganizationPopular
zjunlp
scienceworld-tool-fetcher

This skill locates and picks up a specified tool or instrument from the environment. It should be triggered when a task requires a specific tool (e.g., thermometer, stopwatch) for measurement or manipulation. The skill identifies the tool's location via observation and executes a pick-up action, moving the tool to inventory.

Overview

Publisherzjunlp
RepositorySkillNet
Skill namescienceworld-tool-fetcher
Stars
1.4K
Forks
152
Bundled files
2
LicenseMIT
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Scienceworld Tool Fetcher 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/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-tool-fetcher
  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/zjunlp/SkillNet.git /tmp/SkillNet
mkdir -p .claude/skills
cp -r /tmp/SkillNet/experiments/src/skills/scienceworld/scienceworld-tool-fetcher .claude/skills/scienceworld-tool-fetcher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scienceworld Tool Fetcher 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 Scienceworld Tool Fetcher 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 Scienceworld Tool Fetcher 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.

Instructions

Primary Goal: Locate a specified tool and move it to your inventory.

1. Identify the Target Tool

  • The required tool will be specified in the user's task or request (e.g., "thermometer", "stopwatch", "lighter").
  • Confirm the exact name of the tool object.

2. Locate the Tool via Exploration

  • If you are not in the correct room, use teleport to [ROOM_NAME] to go to the most likely location (e.g., kitchen, workshop).
  • Use look around to survey the current room.
  • Scan the observation for the target tool name. It may be:
    • Listed directly in the room description (e.g., "a thermometer").
    • Inside an open container (e.g., "a fridge. In the fridge is: chocolate, a wood cup...").
  • If the tool is not immediately visible, examine likely containers using look at [CONTAINER] (e.g., look at counter, look at cupboard).

3. Execute the Pick-up

  • Once the tool is located, execute the action: pick up [TOOL_NAME].
  • Example: pick up thermometer.
  • Verify the action was successful by checking the observation for confirmation (e.g., "You move the thermometer to the inventory.").

4. Post-Action Verification (Optional)

  • If required by the broader task, you may perform a secondary action to signal readiness, such as focus on [TOOL_NAME] in inventory.

Key Constraints & Notes

  • Containers are Open: All containers are pre-opened. Do not use open or close actions.
  • Direct Action: Proceed directly to pick up. Do not attempt to move the tool to an intermediate location first.
  • Tool Not Found: If the tool is not in the initial room, systematically teleport to other relevant rooms and repeat the look around search pattern.
  • Single Tool: This skill fetches one specified tool. For multiple tools, trigger the skill sequentially.

Output: The target tool will be in your inventory, ready for use in subsequent task steps.

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 Scienceworld Tool Fetcher AI skill do?

This skill locates and picks up a specified tool or instrument from the environment. It should be triggered when a task requires a specific tool (e.g., thermometer, stopwatch) for measurement or manipulation. The skill identifies the tool's location via observation and executes a pick-up action, moving the tool to inventory.

Why use Scienceworld Tool Fetcher on TypingMind?

Because you install it once and use it with any model. Scienceworld Tool Fetcher 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 Scienceworld Tool Fetcher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-tool-fetcher. 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 Scienceworld Tool Fetcher?

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 Scienceworld Tool Fetcher?

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

Is the Scienceworld Tool Fetcher AI skill free?

Yes. It is published on GitHub by zjunlp under the MIT 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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