Alfworld Environment Scanner

OrganizationPopular

zjunlp

alfworld-environment-scanner

Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles. Use when you first enter an environment and need to build a mental map for task planning. Processes raw observation text into a structured list of entities, categorizing them as objects or receptacles.

Overview

Publisher	zjunlp
Repository	`SkillNet`
Skill name	`alfworld-environment-scanner`
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 Environment Scanner 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-environment-scanner
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-environment-scanner

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-environment-scanner .claude/skills/alfworld-environment-scanner

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

Use it in TypingMind

Enable Alfworld Environment Scanner 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 Environment Scanner 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 Environment Scanner 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

Primary Objective

Execute an initial environmental scan at the start of any Alfworld task. Your goal is to systematically identify and catalog all objects and receptacles mentioned in the initial observation text.

Core Workflow

Trigger: This skill is triggered immediately upon receiving the initial environment description from the simulator (e.g., "You are in the middle of a room. Looking quickly around you, you see...").
Parse & Extract: Process the raw observation text. Extract every noun phrase that represents a physical entity (object or receptacle). Note the naming convention (e.g., "armchair 2", "diningtable 1").
Categorize: Mentally categorize each entity. A receptacle is a surface or container that can hold other objects (e.g., sofa, sidetable, diningtable, dresser). An object is an item that can be manipulated (e.g., laptop, creditcard, pillow). Some entities (like ottoman) can be both depending on context.
Output Structured Mental Map: Formulate a clear, concise internal summary. Do not output this summary to the simulator—it is for your planning use only.
- Format: Scan Complete. Receptacles: [list]. Objects: [list].
- Example: Based on the trajectory, the mental map should be: Scan Complete. Receptacles: [armchair 2, armchair 1, diningtable 1, drawer 4, drawer 3, drawer 2, drawer 1, dresser 1, garbagecan 1, ottoman 1, sidetable 3, sidetable 2, sidetable 1, sofa 1]. Objects: []. (Note: Initial scan only lists visible furniture; objects on them are discovered upon interaction.)

Execution Rules

Single Action: This skill culminates in a single go to <receptacle> action to begin the task-specific search. Choose the most logical first receptacle to inspect (e.g., large central surfaces like diningtable 1 or sofa 1).
No Looping: Do not create a loop of go to actions. After executing the first go to, the skill ends, and standard task planning takes over.
Integration: The mental map generated by this skill must inform all subsequent planning. When searching for a target object, reason about which receptacles from your map are most likely to contain it.

Example from Trajectory

Initial Observation: "You are in the middle of a room... you see a armchair 2, a armchair 1, a diningtable 1, a drawer 4... sofa 1." Skill Execution:

Thought: Initiating environment scan. I see multiple receptacles: armchairs, tables, drawers, a dresser, garbage can, ottoman, sidetables, and a sofa. I will build a mental map and then start searching for the laptop on a likely surface.
Action: go to sofa 1 (The agent then proceeds with the main task using the knowledge from the scan.)

Bundled files

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

references/alfworld_actions_guide.md2 KB

Frequently asked questions

What does the Alfworld Environment Scanner AI skill do?

Why use Alfworld Environment Scanner on TypingMind?

Because you install it once and use it with any model. Alfworld Environment Scanner 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 Environment Scanner in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/alfworld/alfworld-environment-scanner. 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 Environment Scanner?

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 Environment Scanner?

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

Is the Alfworld Environment Scanner 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

Instructions

Primary Objective

Core Workflow

Execution Rules

Example from Trajectory

Bundled files

Frequently asked questions

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