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Embodied Task Decomposition

作者 NaNaoiSong · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install embodied-task-decomposition
功能描述
Decompose complex physical tasks into atomic subtasks for robot execution. Use when user provides: (1) An image showing a physical scene (indoor/outdoor), an...
使用说明 (SKILL.md)

Embodied Task Decomposition

This skill decomposes high-level natural language instructions into atomic subtasks that a robot can execute.

When to Use

  • User provides an image AND a task instruction
  • User asks to "decompose", "break down", or "split" a task
  • User wants step-by-step actions for robot execution

Input Format

  1. Image: Photo of the physical scene (any environment: kitchen, office, outdoor, etc.)
  2. Task Instruction: Natural language description of what to accomplish

Example:

Task Instruction: take toasted bread from bread machine on white table place on plate
Image: [image path or description]

Output Format

Numbered list of subtasks, each following format:

{action} {target} {location/optional prepositional phrase} with {left/right/either} gripper

Process

  1. Analyze the image - Identify objects, surfaces, locations, tools visible
  2. Understand the task - What is the goal? What needs to be moved/ manipulated?
  3. Break into atomic actions - Each subtask = one action from the action bank
  4. Specify gripper - Always indicate left, right or either gripper

Action Bank

Refer to action-bank.md for the complete list of allowed actions. All subtasks MUST use actions from this bank.

Examples

See examples.md for detailed decomposition examples across different domains.

Important Notes

  • Use ONLY actions from the action bank
  • Each subtask = one primary action
  • Always specify gripper (left/right/either)
  • Include target object and location
  • Keep subtasks atomic and sequential
  • Consider object state changes (e.g., "open bag" before "take fruit")

Updating the Action Bank

The agent MAY add new actions to the action bank when needed. To add a new action:

  1. Check for duplicates - Search existing actions for similar functionality
  2. Verify functional difference - New action must serve a distinct purpose
  3. Add with documentation - Include description and example usage

Duplicate Check Criteria

A new action is considered a duplicate if it:

  • Has the same name as an existing action
  • Describes the same physical movement (e.g., "lift" vs "raise")
  • Can be used interchangeably with an existing action in all contexts

Adding a New Action

When adding to action-bank.md, follow this format:

| action_name | Description | Example Usage |
|-------------|-------------|---------------|
| new_action | What it does | "new_action the object"

Example of adding "insert" (different from "place" - "place" = put on surface, "insert" = put into container):

| insert | Put object inside a container or slot | "insert the key into the lock"
安全使用建议
This skill is internally coherent and does not request credentials or install external code. Things to consider before installing: (1) the skill allows adding entries to action-bank.md — if you allow the agent write access it could modify the skill files, so review any changes to that file; (2) run the included scripts/validate.py on outputs or proposed new actions to catch duplicates or malformed subtasks; (3) avoid sending sensitive or private images to an agent you haven't audited, and restrict the agent's file write permissions to the skill directory if possible.
功能分析
Type: OpenClaw Skill Name: embodied-task-decomposition Version: 1.0.0 The skill bundle is designed for robot task decomposition, converting natural language and images into atomic subtasks. It includes a validation script (scripts/validate.py) that checks subtask formatting against a predefined action bank (references/action-bank.md). The instructions in SKILL.md and the accompanying Python code are consistent with the stated purpose and show no signs of malicious intent, data exfiltration, or unauthorized command execution.
能力评估
Purpose & Capability
Name/description (robot task decomposition from image+text) match the included files: an action bank, examples, and a local validator script. No unrelated binaries, credentials, or config paths are requested.
Instruction Scope
SKILL.md stays within scope: analyze image + task text, produce atomic subtasks from a fixed action bank. It also permits the agent to add new actions to action-bank.md; this is reasonable for extensibility but means the agent may modify skill files if allowed to write them. The instructions do not direct reading unrelated system files or sending data to external endpoints.
Install Mechanism
No install spec (instruction-only with one local validator script). Nothing is downloaded or written to disk by an installer; lowest-risk install posture.
Credentials
No environment variables, credentials, or external service tokens are required. The validator reads only the included action-bank.md and the provided subtasks; no access to unrelated secrets or system config is requested.
Persistence & Privilege
always:false and no elevated privileges. The only persistence-related behavior is the agent MAY add actions to action-bank.md per instructions; modifying the skill's own files is plausible for this feature but you should ensure the agent's runtime is permitted to write only intended files.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install embodied-task-decomposition
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /embodied-task-decomposition 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of embodied-task-decomposition skill. - Decomposes high-level physical task instructions into atomic robot-executable subtasks using both image and natural language input. - Triggers on phrases like "decompose this task" or when both an image and a task instruction are provided. - Outputs a numbered list of subtasks using a fixed action format, always specifying gripper and drawing from the action bank. - Supports systematic addition of new actions to the action bank with clear documentation and duplication checks.
元数据
Slug embodied-task-decomposition
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Embodied Task Decomposition 是什么?

Decompose complex physical tasks into atomic subtasks for robot execution. Use when user provides: (1) An image showing a physical scene (indoor/outdoor), an... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 143 次。

如何安装 Embodied Task Decomposition?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install embodied-task-decomposition」即可一键安装,无需额外配置。

Embodied Task Decomposition 是免费的吗?

是的,Embodied Task Decomposition 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Embodied Task Decomposition 支持哪些平台?

Embodied Task Decomposition 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Embodied Task Decomposition?

由 NaNaoiSong(@nanaoisong)开发并维护,当前版本 v1.0.0。

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