Scienceworld Target Identifier logo

Scienceworld Target Identifier

OrganizationPopular
zjunlp
scienceworld-target-identifier

Analyzes room observations to identify objects matching a given target description (e.g., 'living thing'). Triggered after exploring a room when the agent needs to locate a specific type of item. Processes the observation list, filters objects based on target criteria, and returns candidate objects for further action.

Overview

Publisherzjunlp
RepositorySkillNet
Skill namescienceworld-target-identifier
Stars
1.4K
Forks
152
Bundled files
2
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.

  • 2 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 Target Identifier 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-target-identifier
  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-target-identifier .claude/skills/scienceworld-target-identifier
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scienceworld Target Identifier 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 Target Identifier 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 Target Identifier 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: Target Object Identifier

Purpose

This skill enables you to systematically locate objects in the ScienceWorld environment that match a specific target description (e.g., "living thing", "container", "electrical device"). It transforms the raw observation text from look around into a structured list of candidate objects for your current task.

When to Use

  1. Trigger Condition: Immediately after executing look around in any room.
  2. Input Required: The full observation text from look around AND the target description from your task.
  3. Output: A prioritized list of matching objects with their locations and properties.

Execution Workflow

Step 1: Parse Observation

Extract all observable items from the room description. Pay special attention to:

  • Objects listed after "Here you see:"
  • Objects in containers (marked with "containing" or "On the X is:")
  • Substances (marked as "a substance called")
  • Living vs. non-living distinctions

Step 2: Apply Target Filter

Use the bundled classification script to filter objects based on the target description:

  • For "living thing": Include animals, plants, eggs, and biological organisms
  • For specific categories: Match against known object taxonomies
  • For generic descriptions: Use semantic similarity matching

Step 3: Prioritize Candidates

Rank candidates by:

  1. Accessibility: Objects not in closed containers first
  2. Proximity: Objects in current room before other locations
  3. Task Relevance: Objects matching secondary task criteria (e.g., "easy to transport")

Step 4: Generate Action Plan

For each high-priority candidate:

  1. Note its exact name as it appears in observations
  2. Determine if pick up, focus on, or other preliminary action is needed
  3. Plan path to target location if specified in task

Key Considerations

  • Exact Object Names: Use the exact phrasing from observations (e.g., "turtle egg" not "egg turtle")
  • Container States: All containers are open per environment rules
  • Teleportation: You can instantly move between rooms when searching
  • Multiple Matches: If multiple objects match, select based on task context (e.g., choose less mobile items for transport tasks)

Error Handling

  • If no matches found: Teleport to another room and repeat
  • If ambiguous matches: Use examine OBJ for clarification
  • If classification uncertain: Check reference taxonomy in bundled resources

Example Application

Task: "Find a living thing and move it to the blue box in bathroom"

  1. look around in current room
  2. Run this skill with target="living thing"
  3. Receive list: ["baby wolf", "turtle egg", "crocodile egg"]
  4. Select "turtle egg" (easier to transport)
  5. focus on turtle egg → pick up turtle egg → teleport to bathroom → move turtle egg to blue 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 Target Identifier AI skill do?

Analyzes room observations to identify objects matching a given target description (e.g., 'living thing'). Triggered after exploring a room when the agent needs to locate a specific type of item. Processes the observation list, filters objects based on target criteria, and returns candidate objects for further action.

Why use Scienceworld Target Identifier on TypingMind?

Because you install it once and use it with any model. Scienceworld Target Identifier 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 Target Identifier in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-target-identifier. 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 Target Identifier?

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 Target Identifier?

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

Is the Scienceworld Target Identifier 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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