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Alfworld Temperature Regulator

OrganizationPopular
zjunlp
alfworld-temperature-regulator

Manages the temperature state of an object by placing it into an appropriate appliance (fridge for cooling, microwave for heating). Use when the task requires modifying an object's temperature property, such as "cool some bread" or "heat some food". Takes the object identifier, temperature-modifying receptacle, and final target receptacle as inputs, and outputs the object at the target location with its temperature state changed.

Overview

Publisherzjunlp
RepositorySkillNet
Skill namealfworld-temperature-regulator
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 Alfworld Temperature Regulator 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/alfworld/alfworld-temperature-regulator
  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/alfworld/alfworld-temperature-regulator .claude/skills/alfworld-temperature-regulator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alfworld Temperature Regulator 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 Alfworld Temperature Regulator 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 Alfworld Temperature Regulator 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.

Instructions

This skill executes a sequence to change an object's temperature by placing it in a specific receptacle (e.g., fridge for cooling, microwave for heating) and then relocating it to a final target location.

1. Input Validation & Planning

  • Inputs Required: The object identifier (e.g., bread 1) and the temperature_receptacle identifier (e.g., fridge 1 for cooling, microwave 1 for heating). The final target_receptacle (e.g., diningtable 1) is also required.
  • Verify the provided object and receptacles exist in the agent's current observation. If not, the agent must first navigate to locate them.
  • Plan the sequence: Locate object -> Pick up object -> Navigate to temperature receptacle -> Open it (if closed) -> Place object inside -> Close receptacle (optional, based on environment feedback) -> Navigate to target receptacle -> Place object there.

2. Execution Sequence

Follow this core logic. Use deterministic scripts for error-prone steps (see scripts/).

  1. Acquire Object: go to the object's location, then take {object} from {recep}.
  2. Apply Temperature Effect:
    • go to {temperature_receptacle}.
    • If the receptacle is reported as "closed", open {temperature_receptacle}.
    • put {object} in/on {temperature_receptacle}.
    • (Optional) close {temperature_receptacle} if the environment or task logic suggests it (e.g., maintaining fridge temperature).
  3. Deliver Object: go to {target_receptacle}, then put {object} in/on {target_receptacle}.

3. Error Handling & Observations

  • If an action results in "Nothing happened", consult the troubleshooting guide in references/troubleshooting.md.
  • Always verify the state change after each action (e.g., "You pick up...", "You open...", "You put...").
  • If the object is not at the expected location, pause execution and re-scan the environment.

4. Example

Task: "Cool some bread and put it on the diningtable."

Input: object: bread 1, temperature_receptacle: fridge 1, target_receptacle: diningtable 1

Sequence:

  1. go to countertop 1 → Observation: "You are at countertop 1. You see bread 1, ..."
  2. take bread 1 from countertop 1 → Observation: "You pick up the bread 1 from the countertop 1."
  3. go to fridge 1 → Observation: "You are at fridge 1."
  4. cool bread 1 with fridge 1 → Observation: "You cool the bread 1 using the fridge 1."
  5. go to diningtable 1 → Observation: "You are at diningtable 1."
  6. put bread 1 in/on diningtable 1 → Observation: "You put the bread 1 in/on the diningtable 1."

Output: The bread 1 is cooled and placed on the diningtable 1. Task complete.

5. Completion

The skill is complete when the object has been placed into the temperature_receptacle and subsequently placed onto the target_receptacle. Confirm the final observation states the object is on the target.

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 Alfworld Temperature Regulator AI skill do?

Manages the temperature state of an object by placing it into an appropriate appliance (fridge for cooling, microwave for heating). Use when the task requires modifying an object's temperature property, such as "cool some bread" or "heat some food". Takes the object identifier, temperature-modifying receptacle, and final target receptacle as inputs, and outputs the object at the target location with its temperature state changed.

Why use Alfworld Temperature Regulator on TypingMind?

Because you install it once and use it with any model. Alfworld Temperature Regulator 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 Alfworld Temperature Regulator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/alfworld/alfworld-temperature-regulator. 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 Alfworld Temperature Regulator?

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 Alfworld Temperature Regulator?

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

Is the Alfworld Temperature Regulator 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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