Scienceworld Room Scanner logo

Scienceworld Room Scanner

OrganizationPopular
zjunlp
scienceworld-room-scanner

This skill performs a 'look around' action to scan and describe the current room's contents, including visible objects, containers, and doors. Use when entering a new room or when the agent needs to locate specific items or assess the environment state. The skill outputs a detailed room description, which is essential for inventory discovery and situational awareness.

Overview

Publisherzjunlp
RepositorySkillNet
Skill namescienceworld-room-scanner
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 Room Scanner 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-room-scanner
  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-room-scanner .claude/skills/scienceworld-room-scanner
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scienceworld Room Scanner 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 Room Scanner 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 Room Scanner 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: Room Scanner

Purpose

Execute a look around action to obtain a comprehensive description of the current room in the ScienceWorld environment. This description is the foundational step for any task requiring item location, environmental assessment, or navigation planning.

Core Instruction

When this skill is invoked, the agent must perform the look around action.

Trigger Conditions

Invoke this skill when:

  1. You first enter a new room via teleport or other movement.
  2. You need to locate a specific object or container mentioned in your task.
  3. The state of the room may have changed (e.g., after an interaction).
  4. You are formulating a plan and require an inventory of available resources.

Output Processing

The observation from look around will contain:

  • Room Name: The identifier of your current location.
  • Visible Objects & Agents: A list of all entities in the room.
  • Container Contents: For open containers, a nested list of items inside (e.g., a bowl (containing a red apple, a banana)).
  • Device States: The status of interactive objects (e.g., a stove, which is turned off).
  • Connections: All accessible doors and their destination rooms.

You must parse this output carefully. Use it to update your mental model of the environment before proceeding with other actions like pick up, examine, or use.

Integration Notes

  • This is a low-level, atomic skill. It should often be the first action in a sequence.
  • The observation it generates is critical context for subsequent decision-making. Refer back to it.
  • Do not overuse it. Once you have a recent description of a room, rely on that knowledge until you have reason to believe the state has changed.

Example

Task: Survey the workshop after teleporting there.

  1. look around
  2. Observation: "This room is called the workshop. In it, you see: a table. On the table is: a battery, a blue light bulb, an orange wire, a yellow wire, a green wire. You also see: a blue box, an orange box. There is a door to the hallway."
  3. Parse: available components include battery, light bulb, three wires; classification containers are blue box and orange box.

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 Room Scanner AI skill do?

This skill performs a 'look around' action to scan and describe the current room's contents, including visible objects, containers, and doors. Use when entering a new room or when the agent needs to locate specific items or assess the environment state. The skill outputs a detailed room description, which is essential for inventory discovery and situational awareness.

Why use Scienceworld Room Scanner on TypingMind?

Because you install it once and use it with any model. Scienceworld Room Scanner 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 Room Scanner in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-room-scanner. 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 Room Scanner?

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 Room Scanner?

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

Is the Scienceworld Room Scanner 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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