zjunlp/skillnet/scienceworld-material-classifier

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This skill makes a determination about a material's property (e.g., conductivity) based on environmental cues or domain knowledge when direct testing fails. Trigger it when experimental actions are invalid or unavailable, requiring a logical inference. It uses observed object properties and common-sense reasoning to classify the material and decide its final disposition.

Install

npx vskill@latest install zjunlp/skillnet/scienceworld-material-classifier

SKILL.md

Material Classification Skill

When to Use

Activate when direct experimental testing of a material property (conductivity, magnetism, etc.) fails or equipment is unavailable, and you need to classify the material by inference to complete a sorting task.

Procedure

  1. focus on <OBJECT> — identify the target and note its material composition.
  2. Attempt direct testing if equipment exists (e.g., connect <OBJECT> terminal 1 to <WIRE> terminal 2).
  3. If testing fails, infer the property from the object's material. Consult references/material_properties.md for lookup.
  4. move <OBJECT> to <CONTAINER> — place in the appropriate classification container.
  5. look at <CONTAINER> — verify the object was placed correctly.

Example

Task: Classify a glass jar for electrical conductivity when the circuit test is unavailable.

  1. focus on glass jar
  2. connect glass jar terminal 1 to yellow wire terminal 2 — action fails (invalid connection).
  3. Inference: glass is an electrical insulator → non-conductive.
  4. move glass jar to orange box
  5. look at orange box — observation: "containing a glass jar" — classification complete.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

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

Source

Popularity

Repository stars
1,102
Repository forks
128
7-day trend score
35

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 17 Jul 2026, 3 months ago.

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