A powerful utility for breaking down complex user requests into executable subtasks while identifying or creating the necessary Openclaw Skills for completion.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install task-decomposer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install task-decomposer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Task Decomposer & Skill Generator?
The Task Decomposer & Skill Generator is a sophisticated framework designed to handle multi-step AI requests by transforming them into a structured execution plan. It acts as a bridge between high-level user intent and technical execution by analyzing objectives, identifying required capabilities, and searching the ecosystem for existing Openclaw Skills. This skill is essential for developers building complex automations that require a mix of native agent abilities and specialized external tools.
By leveraging a universal capability taxonomy, the decomposer ensures that every part of a workflow—from data retrieval to message delivery—is mapped to the most efficient tool available. When a functionality gap is identified, it provides the templates and logic necessary to initialize new Openclaw Skills, ensuring your AI agent is never limited by its initial configuration.
Task Decomposer & Skill Generator Use Cases
- Automating complex daily workflows such as aggregating email data and delivering summaries to Slack.
- Building research pipelines that require web searching, PDF downloading, and data extraction.
- Identifying missing capabilities in an agent's toolkit and generating new skill definitions automatically.
- Managing large-scale projects by breaking them into atomic, verifiable subtasks with clear dependencies.
How Task Decomposer & Skill Generator Works
- Analyze the user's request to identify core objectives, involved domains, and execution triggers.
- Decompose the goal into atomic subtasks, defining specific inputs, outputs, and logical dependencies for each.
- Map subtasks to universal capability types like browser automation, API integration, or data extraction.
- Search the global repository for existing Openclaw Skills that match the required capabilities using CLI tools.
- Perform a gap analysis to determine if tasks can be handled by built-in agent functions or if new skills must be created.
- Compile a structured execution plan that includes installation commands, skill initialization, and verification steps.
Task Decomposer & Skill Generator Setup
To begin using this skill and managing your library of Openclaw Skills, you can utilize the following CLI commands:
# Search for existing skills in the ecosystem
npx skills find <keyword>
# Install a specific skill for your project
npx skills add <owner/repo@skill> -g -y
# Initialize the directory structure for a new custom skill
npx skills init <skill-name>
Task Decomposer & Skill Generator Data Schema & Taxonomy
The skill organizes its workflow using a structured metadata schema to ensure task verifiability and clear execution paths.
| Component | Description |
|---|---|
| task_id | A unique identifier for each atomic unit of work |
| capability | The mapped functional category (e.g., web_search, file_operations) |
| status | Classification of the skill source: Found, Built-in, or Create |
| search_query | Optimized keywords used to discover relevant Openclaw Skills |
| dependencies | A list of task IDs that must be completed before the current task begins |
Task Decomposer & Skill Generator Advanced Features
- Universal Capability Mapping: Standardizes how tasks are matched against the Openclaw Skills ecosystem for higher accuracy.
- Automated Skill Initialization: Provides ready-to-use templates for generating new functional modules when no existing solution is found.
- Atomic Task Principles: Ensures every subtask is independent and verifiable, reducing errors in complex automated sequences.
- Integrated Search & Discovery: Directly interacts with skills.sh to leverage the latest community-driven capabilities.
SKILL.md
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