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alfworld-environment-scanner

@zjunlp · 收录于 5 天前 · 上游提交 2 周前

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.

适合你,如果需要在ALFWorld环境中快速获取结构化地图信息。

/ 通过 npx 安装 校验哈希
npx oh-my-skill add zjunlp/skillnet/alfworld-environment-scanner
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- zjunlp/skillnet/alfworld-environment-scanner
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify zjunlp/skillnet/alfworld-environment-scanner
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 7bb9a48 · 表述以原文为准
它做什么

进入 ALFWorld 游戏环境时,自动扫描并列出所有可见的家具(容器)和物品,帮你记住周围有哪些东西可以拿或放。

什么时候触发

当模拟器首次给出环境描述(例如“你在一间房间中间”)时自动触发,用于构建初始心理地图。

装好后可以这样说
Claude 会执行扫描并列出可见物体。
Claude 输出容器和物品列表。
触发环境扫描,为后续行动准备。
技能原文 SKILL.md作者撰写 · MIT · 7bb9a48

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.
  5. Format: Scan Complete. Receptacles: [list]. Objects: [list].
  6. 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.)

按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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