Scienceworld Environment Isolation logo

Scienceworld Environment Isolation

OrganizationPopular
zjunlp
scienceworld-environment-isolation

Use when you need to isolate a space (like a greenhouse) by closing doors or openings to create a contained environment. Trigger before starting pollination, temperature-sensitive experiments, or other environmental-sensitive tasks that require controlled conditions. Modifies room connectivity to optimize conditions for specific processes.

Overview

Publisherzjunlp
RepositorySkillNet
Skill namescienceworld-environment-isolation
Stars
1.4K
Forks
152
Bundled files
1
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.

  • 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 Environment Isolation 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-environment-isolation
  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-environment-isolation .claude/skills/scienceworld-environment-isolation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scienceworld Environment Isolation 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 Environment Isolation 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 Environment Isolation 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

When to Use

Trigger this skill when you need to:

  1. Optimize Pollination: Isolate a room (like a greenhouse) to concentrate pollinators (e.g., bees) and prevent them from leaving, thereby increasing the chance of successful cross-pollination between plants.
  2. Control Environmental Factors: Create a stable, contained space to manage variables like temperature, humidity, or airflow for a sensitive process.
  3. Prevent Contamination or Interference: Seal off a room to protect an ongoing experiment or task from external disturbances.

Core Action Sequence

  1. Assess the Environment: Use look around to identify all doors, windows, or other openings in the current room.
  2. Execute Isolation: For each identified opening (e.g., "door to the outside", "door to the hallway"), issue a close command.
    • Example: close door to outside
    • Example: close door to hallway
  3. Verify Closure: Perform a final look around to confirm all intended openings are now closed and the room is successfully isolated.

Key Principles

  • Completeness: Ensure all exits are closed for full isolation. An open door can defeat the purpose.
  • Context-Specific: The specific doors to close depend entirely on the room's layout. Always verify via look around.
  • Post-Isolation: After isolation, monitor the contained process (e.g., plant growth) and use wait actions as needed to allow time for the optimized conditions to take effect.

Notes

  • This skill modifies the connectivity of a space, not its internal state (like temperature controls).
  • The primary observed benefit in the trajectory was enhancing bee-mediated pollination by preventing bee escape.
  • Reversal (re-opening doors) is not part of this skill's core function but can be done using standard open commands if needed later.

Example

Scenario: You need to cross-pollinate two plants in the greenhouse using bees.

  1. You have placed both plants and a bee jar in the greenhouse.
  2. Run look around — you see: "door to outside (open)", "door to hallway (open)".
  3. Run close door to outside — output: "You close the door to outside."
  4. Run close door to hallway — output: "You close the door to hallway."
  5. Run look around — confirm both doors now show as closed. The greenhouse is fully isolated.
  6. Release the bee by running open bee jar. The bee cannot escape and will pollinate both plants.
  7. Run wait several times to allow pollination to complete.

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 Environment Isolation AI skill do?

Use when you need to isolate a space (like a greenhouse) by closing doors or openings to create a contained environment. Trigger before starting pollination, temperature-sensitive experiments, or other environmental-sensitive tasks that require controlled conditions. Modifies room connectivity to optimize conditions for specific processes.

Why use Scienceworld Environment Isolation on TypingMind?

Because you install it once and use it with any model. Scienceworld Environment Isolation 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 Environment Isolation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-environment-isolation. 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 Environment Isolation?

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 Environment Isolation?

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

Is the Scienceworld Environment Isolation 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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