Alfworld Receptacle Finder

OrganizationPopular

zjunlp

alfworld-receptacle-finder

Searches for a suitable empty or appropriately occupied receptacle (like a shelf or table) to place an object. Use when you are holding an object that needs to be stored or placed and must find a receptacle that meets the placement criteria. Examines candidate receptacles by navigating to and inspecting each one until a suitable location is found.

Overview

Publisher	zjunlp
Repository	`SkillNet`
Skill name	`alfworld-receptacle-finder`
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 Alfworld Receptacle Finder 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/alfworld/alfworld-receptacle-finder
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/alfworld/alfworld-receptacle-finder

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/alfworld/alfworld-receptacle-finder .claude/skills/alfworld-receptacle-finder

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

Use it in TypingMind

Enable Alfworld Receptacle Finder 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 Receptacle Finder 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 Receptacle Finder 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

Trigger: Use this skill when you have an object in your inventory that needs to be stored or placed, and you must find a suitable receptacle (e.g., shelf, table, basin).

Core Procedure

Identify Target Object: Confirm the object you are holding and its state (e.g., soapbar 1, clean).
Survey Environment: Use go to {recep} actions to navigate to and visually inspect candidate receptacles from the observation list.
Evaluate Candidates: For each receptacle, assess its suitability:
- Primary Goal: Find an empty receptacle.
- Fallback: If no empty receptacle is available, identify one that can logically accommodate the object without conflict (e.g., a shelf with a tissuebox may still have space for a soapbar).
Select & Place: Navigate to the chosen suitable receptacle and execute put {obj} in/on {recep}.

Key Considerations

Object State: Ensure the object meets any required pre-conditions (e.g., clean) before searching for a receptacle. Use skills like clean if necessary.
Efficiency: Prioritize receptacles that are logically appropriate for the object (e.g., a shelf for a soapbar over a toilet).
Observation Parsing: Carefully read the observation after each go to action. The line "On the {recep}, you see..." lists its contents. "you see nothing." indicates it is empty.
Invalid Actions: If an action fails ("Nothing happened"), re-evaluate your target and try a different receptacle or confirm the object is in your inventory.

Example

Scenario: You are holding soapbar 1 (clean) and need to find an empty shelf to place it.


Thought: I need to find an empty shelf for the soapbar. I'll check shelf 1 first.
Action: go to shelf 1
Observation: On the shelf 1, you see a tissuebox 1.
Thought: Shelf 1 has items. Let me try shelf 2.
Action: go to shelf 2
Observation: On the shelf 2, you see nothing.
Action: put soapbar 1 in/on shelf 2
Observation: You put the soapbar 1 in/on the shelf 2.

Result: Found an empty shelf and placed the soapbar on it.

Bundled Reference

For a detailed example including handling object pre-cleaning and sequential shelf evaluation, refer to references/example_trajectory.md.

Bundled files

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

references/example_trajectory.md1 KB

Frequently asked questions

What does the Alfworld Receptacle Finder AI skill do?

Why use Alfworld Receptacle Finder on TypingMind?

Because you install it once and use it with any model. Alfworld Receptacle Finder 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 Receptacle Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/alfworld/alfworld-receptacle-finder. 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 Receptacle Finder?

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 Receptacle Finder?

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

Is the Alfworld Receptacle Finder 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.

View all

Wasm Gallery

ruvnet

CommunityPopular

Browse, publish, and install WASM agents from the community gallery

Browser Extract

Extract structured data via stored browser-templates or one-shot DOM queries, with mandatory AIDefence PII + prompt-injection gates before content reaches the model

Browser Record

Open a named, traced browser session into an RVF cognitive container with a ruvector trajectory recording every action

Init Project

Initialize a new Ruflo project with MCP tools, hooks, and agent configuration. Use when setting up Ruflo in a fresh repo, or when the user says "init ruflo", "set up ruflo", or asks how to bootstrap…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Instructions

Core Procedure

Key Considerations

Example

Bundled Reference

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now