A structured architectural framework for decomposing complex systems into cohesive components based on user workflows rather than data entities.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bookforge-component-identifier
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 bookforge-component-identifier 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 Component Identifier?
The Component Identifier is an essential architectural skill within the Openclaw Skills collection, designed to help developers decompose complex systems into logical, well-defined components. By shifting focus from data persistence to behavioral workflows, this skill helps teams avoid the common Entity Trap anti-pattern, where modules mirror database tables rather than business logic.
Whether you are designing a greenfield application or restructuring an existing monolith, this skill provides a structured discovery process rooted in the fundamentals of software architecture. It enables the identification of clear boundaries, ensuring that each component is cohesive, manageable, and aligned with its specific architectural characteristics.
Component Identifier Use Cases
- Designing a new greenfield system from ambiguous user stories and requirements.
- Refactoring a large, tangled monolithic codebase into more manageable modules or services.
- Transitioning an organization from technical layering to domain-driven partitioning.
- Identifying architectural quanta based on varying quality attributes across different system parts.
How Component Identifier Works
- Select a partitioning style (Domain vs Technical) to set the structural foundation using Openclaw Skills standards.
- Identify system actors and their specific actions to map functional requirements accurately.
- Group related actions into candidate components to maximize functional cohesion and minimize coupling.
- Validate component boundaries by mapping existing requirements and user stories to specific modules.
- Analyze architecture characteristics to detect differences in quality attribute needs across the system.
- Perform a strict Entity Trap check to ensure components represent behaviors, not just database wrappers.
- Refine component granularity through an iterative assessment of inter-component communication overhead.
Component Identifier Setup
To get started with this component identification framework, install it via the CLI:
clawhub install bookforge-component-identifier
Ensure that the architecture-characteristics-identifier is also available in your environment, as this skill leverages its output to determine component boundaries based on quality attributes.
Component Identifier Data Schema & Taxonomy
The skill generates a comprehensive Component Identification Report structured as follows:
| Data Point | Description |
|---|---|
| Partitioning Style | Justification for choosing domain-driven or layered technical partitioning. |
| Actors & Actions | A matrix mapping system users to their primary behavioral workflows. |
| Component Registry | A detailed list of identified components, their responsibilities, and relevant -ilities. |
| Requirement Mapping | A validation table linking each user story to the component that handles it. |
| Granularity Assessment | An analysis of whether components are too fine-grained (chatty) or too coarse (bloated). |
Component Identifier Advanced Features
- Deep integration with architecture-characteristics-identifier for data-driven component decomposition.
- Automated Entity Trap detection and mitigation strategies for workflow-centric design.
- Support for Event Storming workflows to identify components in high-scale event-driven systems.
- Characteristic variance analysis to flag specific components for further quantum analysis.
SKILL.md
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