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Embodied Task Decomposition

by NaNaoiSong · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install embodied-task-decomposition
Description
Decompose complex physical tasks into atomic subtasks for robot execution. Use when user provides: (1) An image showing a physical scene (indoor/outdoor), an...
README (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"
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install embodied-task-decomposition
  3. After installation, invoke the skill by name or use /embodied-task-decomposition
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Slug embodied-task-decomposition
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Embodied Task Decomposition?

Decompose complex physical tasks into atomic subtasks for robot execution. Use when user provides: (1) An image showing a physical scene (indoor/outdoor), an... It is an AI Agent Skill for Claude Code / OpenClaw, with 143 downloads so far.

How do I install Embodied Task Decomposition?

Run "/install embodied-task-decomposition" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Embodied Task Decomposition free?

Yes, Embodied Task Decomposition is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Embodied Task Decomposition support?

Embodied Task Decomposition is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Embodied Task Decomposition?

It is built and maintained by NaNaoiSong (@nanaoisong); the current version is v1.0.0.

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