Scienceworld Substance Fetcher

OrganizationPopular

zjunlp

scienceworld-substance-fetcher

Locates and retrieves a target substance or material from a container in the environment. Use this skill when the task requires processing a specific substance (e.g., chocolate, sodium chloride, a chemical) and you need to find and acquire it. Searches rooms and containers (fridge, cupboard, counter) and retrieves the substance via pick up or move actions.

Overview

Publisher	zjunlp
Repository	`SkillNet`
Skill name	`scienceworld-substance-fetcher`
Stars	1.4K
Forks	152
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

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.
1 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 Substance Fetcher 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/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-substance-fetcher
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-substance-fetcher

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/zjunlp/SkillNet.git /tmp/SkillNet
mkdir -p .claude/skills
cp -r /tmp/SkillNet/experiments/src/skills/scienceworld/scienceworld-substance-fetcher .claude/skills/scienceworld-substance-fetcher

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

Use it in TypingMind

Enable Scienceworld Substance 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 Substance 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 Substance 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.

Skill: Substance Fetcher

Primary Objective

Locate a specified target substance (e.g., chocolate, sodium chloride) within the environment and retrieve it for subsequent processing.

Core Logic & Workflow

Identify Target: The target substance name is provided as part of the task initiation (e.g., "Your task is to measure the melting point of chocolate").
Search Strategy:
- If the current room does not contain the target, use teleport to [room] to navigate to likely locations (e.g., kitchen, workshop, greenhouse).
- Use look around to survey a room and identify containers.
Locate in Container:
- Examine open containers (fridge, cupboard, counter, drawer) listed in the room description.
- The target substance is often found inside a container (e.g., "In the fridge is: chocolate").
Retrieval Action:
- If the substance is a portable object, use pick up [substance].
- If the substance is inside another object (e.g., in a pot), use move [substance] to [destination container] to prepare it for use.
- Key Assumption: All containers are already open. Do not use open or close actions.

Critical Constraints & Notes

Container State: Assume all containers (fridge, cupboard, drawer) are already open. Do not waste actions opening them.
Action Efficiency: Prefer pick up for direct acquisition. Use move only when necessary to transfer the substance to a specific vessel for an experiment.
Verification: After retrieval, you may use examine [substance] or check your inventory to confirm success before proceeding to the next phase of the experiment.

Example Execution (Based on Trajectory)

Task Context: "Your task is to measure the melting point of chocolate..."

teleport to kitchen
look around (Observes: "In the fridge is: chocolate...")
pick up chocolate or move chocolate to metal pot

Error Handling

If the substance is not found in the initially suspected room, teleport to and search other relevant rooms (e.g., workshop for chemicals, greenhouse for plants).
If the retrieval action fails (e.g., object not found), re-examine the room description with look around to confirm the substance's location and container.

Bundled files

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

references/action_primer.md1 KB

Frequently asked questions

What does the Scienceworld Substance Fetcher AI skill do?

Why use Scienceworld Substance Fetcher on TypingMind?

Because you install it once and use it with any model. Scienceworld Substance 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 Substance 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-substance-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 Substance 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 Substance Fetcher?

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

Is the Scienceworld Substance 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Skill: Substance Fetcher

Primary Objective

Core Logic & Workflow

Critical Constraints & Notes

Example Execution (Based on Trajectory)

Error Handling

Bundled files

Frequently asked questions

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