Alfworld Search Pattern Executor logo

Alfworld Search Pattern Executor

OrganizationPopular
zjunlp
alfworld-search-pattern-executor

Systematically searches a sequence of likely locations for a target object based on common sense. Use when you need to find a specific object and know which receptacles to check but not which one contains it. Takes a list of candidate receptacles, orchestrates navigation and inspection, and outputs when the target is found or all locations are exhausted.

Overview

Publisherzjunlp
RepositorySkillNet
Skill namealfworld-search-pattern-executor
Stars
1.4K
Forks
152
Bundled files
1
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.

  • 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 Search Pattern Executor 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-search-pattern-executor
  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-search-pattern-executor .claude/skills/alfworld-search-pattern-executor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alfworld Search Pattern Executor 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 Search Pattern Executor 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 Search Pattern Executor 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

For each candidate receptacle in order, execute this action sequence:

Workflow

  1. Navigate: go to {receptacle}
  2. Open if closed: If observation says "{receptacle} is closed", execute open {receptacle}
  3. Inspect: Read the observation for the target object name
  4. If found: Execute take {target_object} from {receptacle} and stop searching
  5. If not found: If you opened the receptacle, execute close {receptacle}, then continue to the next candidate
  6. If all exhausted: Report that the target was not found in any candidate location

Action Format

  • go to {receptacle} -- navigate to a location
  • open {receptacle} -- open a closed drawer/cabinet/fridge
  • close {receptacle} -- close after checking (state management)
  • take {object} from {receptacle} -- pick up the target when found

Key Rules

  • Search candidates in order; do not skip locations
  • Always close drawers/cabinets after checking if you opened them
  • Once the object is found, immediately stop searching and proceed to the next task phase
  • If "Nothing happened" is returned, verify the receptacle name and retry with the correct identifier

Example

Goal: "find two remotecontrol and put them in armchair."

Thought: I need to find remotecontrol. Candidates: sofa 1, sidetable 1, coffeetable 1. Starting search.
Action: go to sofa 1
Observation: On the sofa 1, you see a pillow 1.
Thought: No remotecontrol on sofa 1. Checking next candidate.
Action: go to sidetable 1
Observation: On the sidetable 1, you see a keychain 1.
Thought: Not here either. Checking coffeetable.
Action: go to coffeetable 1
Observation: On the coffeetable 1, you see a remotecontrol 1, a remotecontrol 2.
Action: take remotecontrol 1 from coffeetable 1
Observation: You pick up the remotecontrol 1 from the coffeetable 1.

Result: First remotecontrol found and picked up. Proceed to place it in armchair 1, then re-activate search for the second one.

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 Search Pattern Executor AI skill do?

Systematically searches a sequence of likely locations for a target object based on common sense. Use when you need to find a specific object and know which receptacles to check but not which one contains it. Takes a list of candidate receptacles, orchestrates navigation and inspection, and outputs when the target is found or all locations are exhausted.

Why use Alfworld Search Pattern Executor on TypingMind?

Because you install it once and use it with any model. Alfworld Search Pattern Executor 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 Search Pattern Executor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjunlp/SkillNet/tree/main/experiments/src/skills/alfworld/alfworld-search-pattern-executor. 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 Search Pattern Executor?

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 Search Pattern Executor?

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

Is the Alfworld Search Pattern Executor 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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