Scienceworld Conditional Placer

OrganizationPopular

zjunlp

scienceworld-conditional-placer

Places an object into one of several designated containers based on a measured condition, such as a temperature threshold. Use this skill when you have completed a measurement or assessment and the task requires sorting or storing the object into one of multiple containers according to a rule (e.g., "if temperature > X, place in container A; otherwise container B").

Overview

Publisher	zjunlp
Repository	`SkillNet`
Skill name	`scienceworld-conditional-placer`
Stars	1.4K
Forks	152
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

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 Conditional Placer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-conditional-placer
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-conditional-placer

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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-conditional-placer .claude/skills/scienceworld-conditional-placer

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scienceworld Conditional Placer 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 Conditional Placer 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 Conditional Placer 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: Conditional Object Placer

Purpose

Place a target object into the correct container based on a measured condition (e.g., temperature threshold, conductivity result). This skill executes the full measure-then-sort workflow.

Core Workflow

Locate & Acquire Measurement Tool: teleport to LOC then pick up the measurement device (e.g., thermometer).
Locate & Acquire Target Object: teleport to LOC then pick up the object to be measured (e.g., metal fork).
Identify Target Containers: Use look around to find the designated containers (e.g., blue box, orange box).
Perform Measurement: use OBJ on OBJ (e.g., use thermometer on metal fork) to obtain the value.
Evaluate Condition & Place: Compare the measured value against the threshold, then move OBJ to OBJ to place the object in the correct container.

Key Actions

Action	Purpose
`teleport to LOC`	Navigate between rooms
`look around`	Survey a room for objects
`pick up OBJ`	Acquire tools or target object
`use OBJ on OBJ`	Perform measurement
`move OBJ to OBJ`	Place object into selected container

Example

Task: "Measure the temperature of the metal fork. If above 50C, place in the orange box. Otherwise, place in the blue box."

teleport to kitchen
look around — find thermometer and metal fork
pick up thermometer
pick up metal fork
use thermometer on metal fork — reads 72 degrees
72 > 50, so: move metal fork to orange box

Important Notes

All containers are pre-opened. Do not use open or close actions.
The measurement tool and target object must be picked up and used from inventory.
Room names, object names, thresholds, and container names vary per task — adapt accordingly.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/action_guide.md2 KB

Frequently asked questions

What does the Scienceworld Conditional Placer AI skill do?

Why use Scienceworld Conditional Placer on TypingMind?

Because you install it once and use it with any model. Scienceworld Conditional Placer 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 Conditional Placer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/scienceworld/scienceworld-conditional-placer. 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 Conditional Placer?

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 Conditional Placer?

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

Is the Scienceworld Conditional Placer 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Skill: Conditional Object Placer

Purpose

Core Workflow

Key Actions

Example

Important Notes

Bundled files

Frequently asked questions

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