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scienceworld-task-interpreter

Parse scientific instructions and formulate stepwise plans for ScienceWorld environments.

145|1|Updated Mar 16, 2026
Search Tags:#task planning#natural language understanding#environment navigation#ScienceWorld#scientific instruction
One-click install
npx skills add https://github.com/taomiao/DynamicSkillCompiler --skill scienceworld-task-interpreter-taomiao
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scienceworld-task-interpreter
Source: https://github.com/taomiao/DynamicSkillCompiler/tree/main/experiments/src/skills/scienceworld/scienceworld-task-interpreter
Command: npx skills add https://github.com/taomiao/DynamicSkillCompiler --skill scienceworld-task-interpreter-taomiao

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill enables AI agents to understand high-level scientific instructions and generate clear, actionable plans, facilitating efficient task execution.

Core Features & Use Cases

  • Instruction Parsing: Extracts objectives, targets, and locations from complex user instructions.
  • Plan Formulation: Creates step-by-step navigation and observation plans based on parsed information.
  • Use Case: For example, interpreting a command like "find the shortest-lived animal in the outside area" and planning a sequence of teleportation, observation, and analysis steps to accomplish it.

Quick Start

Activate this Skill with a natural language instruction to interpret and generate an execution plan for ScienceWorld tasks.

Frequently Asked Questions about scienceworld-task-interpreter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I interpret high-level scientific instructions for AI agents in ScienceWorld?▼

Interpreting high-level scientific instructions requires parsing complex natural language to identify objectives, targets, and locations. This skill leverages natural language understanding to convert instructions into executable steps suitable for environment navigation and analysis.

What is the best way to plan environment navigation tasks from natural language descriptions?▼

Planning environment navigation tasks involves extracting objectives and locations from complex user instructions. This skill formulates step-by-step navigation and observation plans based on parsed information to guide AI actions efficiently.

How do I create stepwise plans for complex scientific tasks in text-based environments?▼

Creating stepwise plans for complex scientific tasks involves parsing high-level instructions to identify objectives and locations. This skill formulates actionable sequences, such as teleportation, observation, and analysis steps, to accomplish specific environmental goals.

Can I use natural language understanding to generate executable observation steps for ScienceWorld tasks?▼

Natural language understanding can generate executable observation steps for ScienceWorld tasks by parsing high-level scientific instructions. The skill identifies specific targets and locations, converting user commands into clear, actionable plans for AI agents.

Does this task planning approach support extracting objectives and locations from scientific commands?▼

Task planning via this approach supports extracting objectives and locations from scientific commands. Instruction parsing analyzes complex user instructions to identify specific targets, enabling the formulation of step-by-step navigation and observation plans.

Why do my AI agents struggle with task clarity when navigating ScienceWorld environments?▼

AI agents struggle with task clarity when navigating ScienceWorld environments due to complex, high-level instructions. This skill solves the problem by parsing instructions and formulating stepwise plans, enhancing task clarity and operational efficiency.

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