Scienceworld Task Interpreter logo

Scienceworld Task Interpreter

OrganizationPopular
zjunlp
scienceworld-task-interpreter

This skill parses a user's high-level scientific task in the ScienceWorld environment and extracts the core objective and target location. It should be triggered when a new task instruction is received, especially those involving finding, comparing, or manipulating objects. The skill interprets the query to identify the goal (e.g., 'find the animal with the shortest life span') and any specified locations (e.g., 'animals are in the outside location'), outputting a clear, actionable sub-goal for navigation or observation.

Overview

Publisherzjunlp
RepositorySkillNet
Skill namescienceworld-task-interpreter
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 Task Interpreter 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-task-interpreter
  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-task-interpreter .claude/skills/scienceworld-task-interpreter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scienceworld Task Interpreter 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 Task Interpreter 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 Task Interpreter 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

Activate this skill when the user provides a new task instruction for the ScienceWorld environment. Your primary function is to interpret the instruction and generate a clear, executable plan.

1. Parse the Task

Read the user's instruction carefully. Extract the following core components:

  • Primary Objective: What is the ultimate goal? (e.g., "find", "compare", "manipulate").
  • Target Object/Subject: What is the main focus of the task? (e.g., "animal with the shortest life span").
  • Specified Location: Is a location explicitly mentioned? (e.g., "animals are in the 'outside' location").

2. Formulate the Plan

Based on the parsed components, construct a plan. The standard plan structure is:

  1. Navigate: If a target location is specified and you are not there, teleport to it immediately.
  2. Observe: Upon arriving at the correct location, use look around to survey the environment and identify relevant objects.
  3. Analyze & Execute: Apply domain knowledge or comparative reasoning to the observed objects to fulfill the primary objective. Then, take the final required action (e.g., focus on [OBJECT], pick up [OBJECT]).

3. Output the Interpretation

Before taking the first action, articulate your interpretation and plan in a Thought step. This confirms the skill has correctly parsed the task. Output Format:

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 Task Interpreter AI skill do?

This skill parses a user's high-level scientific task in the ScienceWorld environment and extracts the core objective and target location. It should be triggered when a new task instruction is received, especially those involving finding, comparing, or manipulating objects. The skill interprets the query to identify the goal (e.g., 'find the animal with the shortest life span') and any specified locations (e.g., 'animals are in the outside location'), outputting a clear, actionable sub-goal for navigation or observation.

Why use Scienceworld Task Interpreter on TypingMind?

Because you install it once and use it with any model. Scienceworld Task Interpreter 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 Task Interpreter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-task-interpreter. 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 Task Interpreter?

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 Task Interpreter?

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

Is the Scienceworld Task Interpreter 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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