zjunlp/skillnet/scienceworld-living-entity-identifier

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Analyzes room observations to identify potential living things (e.g., eggs, plants, animals) among listed objects. Use this skill when a task involves finding, focusing on, or interacting with a living thing, biological entity, or organism. Processes observation text, flags candidate living items based on domain knowledge, and outputs a focused target for subsequent actions like focus on or pick up.

Install

npx vskill@latest install zjunlp/skillnet/scienceworld-living-entity-identifier

SKILL.md

Skill: Living Entity Identifier

Purpose

Identify living things (eggs, plants, animals) from room observations and focus on them for task progression.

Core Workflow

  1. Survey Room: look around to get the observation text listing all objects.
  2. Identify Candidates: Scan the object list for living entity indicators:
  • Animals: dove, giant tortoise, bee, frog, fish
  • Eggs: dove egg, chicken egg, turtle egg
  • Plants: flower, tree, moss, fern, algae
  • Other biological: mushroom, seed, pollen
  1. Focus on Target: focus on [IDENTIFIED_OBJECT] to signal task progress.
  2. Transport (if needed): pick up [OBJECT] then move [OBJECT] to [CONTAINER].

Key Actions

ActionPurpose
look aroundSurvey room for objects
teleport to LOCMove to rooms with biological likelihood
focus on OBJSignal identification to task system
pick up OBJAcquire entity for transport

Example

Task: "Find a living thing in the environment."

  1. teleport to outside
  2. look around — observation lists: "a dove egg", "a rock", "soil"
  3. Identify "dove egg" as the living entity candidate
  4. focus on dove egg
  5. If transport required: pick up dove egg then move dove egg to blue box

Important Notes

  • Prioritize explicit living things (e.g., "dove egg," "giant tortoise") over ambiguous substances (e.g., "air," "water").
  • If the current room lacks candidates, teleport to rooms with higher biological likelihood: outside, greenhouse, bedroom.
  • Always use focus on immediately after identification — it signals task progress.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
1,024
Repository forks
117
7-day trend score
35

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 6 Jun 2026, 4 months ago.

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