Alfworld Environment ScannerSAFE

Create, Evaluate, and Connect AI Skills

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: alfworld-environment-scanner
description: 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.
---
# 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
1.  **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...").
2.  **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").
3.  **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.
4.  **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.)*

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.