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alfworld-goal-interpreter

@zjunlp · 收录于 5 天前 · 上游提交 2 周前

Parses the natural language task goal to extract actionable sub-objectives and required objects. Trigger this skill whenever a new task is assigned to break down complex instructions into clear, sequential targets. It interprets phrases like 'look at X under Y' to identify target objects (pillow), reference objects (desklamp), and spatial relationships (under).

适合你,如果需要在AI环境中将复杂指令转化为具体操作步骤

/ 通过 npx 安装 校验哈希
npx oh-my-skill add zjunlp/skillnet/alfworld-goal-interpreter
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- zjunlp/skillnet/alfworld-goal-interpreter
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify zjunlp/skillnet/alfworld-goal-interpreter
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

装上后,Claude 会把用户用自然语言描述的任务目标,拆解成主要物体、参考物体、空间关系和动作等结构化信息,然后生成一步步的子目标计划,并在执行中根据观察调整。

什么时候触发

当用户分配一个新任务时触发,尤其是需要把复杂指令分解成清晰顺序目标的场景。

装好后可以这样说
解析出目标物体和空间关系
包含容器和动作的指令
技能原文 SKILL.md作者撰写 · MIT · 7bb9a48

Goal Interpretation Protocol

1. Parse the Task Statement

When a new task is assigned, immediately analyze the natural language instruction to extract its core components. Use the parsing script (parse_goal.py) to perform this analysis.

Input: The raw task string (e.g., "look at pillow under the desklamp"). Output: A structured dictionary containing:

  • primary_target: The main object to interact with.
  • reference_object: The object that defines a location or condition.
  • spatial_relation: The preposition linking them (e.g., under, on, in).
  • action: The verb defining the required interaction.
2. Generate Sub-Objectives

Based on the parsed components, formulate a clear, sequential plan. The plan must account for the spatial relationship.

Example Logic:

  • IF relation is under → Sub-goal 1: Locate the reference_object. Sub-goal 2: Inspect the area beneath it for the primary_target.
  • IF relation is in or on → Sub-goal 1: Locate the reference_object. Sub-goal 2: Check its contents/surface.
3. Identify Required Objects & Actions

Map the parsed objects to the available action types in the environment. The primary action verbs (look, take, use, etc.) from the task must be translated into the agent's available action set (go to, take, use, etc.).

Critical Check: If the reference_object is a container (drawer, fridge), ensure the plan includes the open action before inspection.

4. Execute & Adapt

Initiate the plan. After each action, monitor the observation. If the expected object is not found, or the action fails ("Nothing happened"), consult the fallback logic in the reference guide (search_patterns.md).

Remember: The agent must maintain object permanence. If an object is moved (e.g., a pillow is picked up), it is now in the agent's inventory and the spatial relationship is void.

按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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