Does this skill suggest making my files smaller?

Not necessarily. It focuses on reducing system complexity. Sometimes this means merging small, shallow modules into a single 'deep' module to hide complexity more effectively.

How does it help with 'pass-through' methods?

It identifies forwarding methods that add layers without adding abstraction, typically recommending a merge to eliminate the unnecessary connective tissue.

What are 'conjoined methods' in this context?

Conjoined methods are a red flag where two methods are so intertwined that you cannot understand or modify one without reading the other, suggesting a failed split.

Can it help during a code review?

Yes, it provides a structured framework for evaluating if a decomposition decision correctly encloses design decisions or if it creates 'unknown unknowns' in the codebase.

When should I use the module-boundaries skill?

Use it when you are deciding whether to split or merge specific modules, or when a change in one module frequently forces a change in another due to tight coupling.

Module Boundaries Review

Name: Module Boundaries Review
Author: codybrom

bycodybrom

•

协作工具

Evaluates and optimizes software architecture by determining whether modules should be merged, split, or refactored to reduce system complexity.

The Module Boundaries skill provides an architectural lens for Claude Code, grounded in the philosophy of deep software design. It helps developers move beyond the common 'smaller is better' fallacy by analyzing whether components are truly independent or merely fragmented. By identifying 'conjoined methods,' information leakage, and shallow interfaces, this skill provides actionable guidance on when to combine coupled modules, decompose large classes into independent peers, or extract entirely new abstractions to minimize system-wide cognitive load.

主要功能

01Analysis of shared knowledge and information leakage between modules

02Discovery process for extracting hidden abstractions to resolve pass-through code

03Strategic splitting guidance based on domain knowledge and rates of change

043 GitHub stars

05Identification of conjoined methods that cannot be understood independently

06Heuristics for merging shallow modules that increase boilerplate complexity

使用场景

01Reviewing architectural decomposition decisions during code reviews to ensure system simplicity

02Refactoring a large, complex class into independent and decoupled components

03Consolidating multiple shallow modules that share the same data structures

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add codybrom/clairvoyance module-boundaries

For use in Claude.ai and ChatGPT

主要功能

01Analysis of shared knowledge and information leakage between modules

02Discovery process for extracting hidden abstractions to resolve pass-through code

03Strategic splitting guidance based on domain knowledge and rates of change

043 GitHub stars

05Identification of conjoined methods that cannot be understood independently

06Heuristics for merging shallow modules that increase boilerplate complexity

使用场景

01Reviewing architectural decomposition decisions during code reviews to ensure system simplicity

02Refactoring a large, complex class into independent and decoupled components

03Consolidating multiple shallow modules that share the same data structures

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add codybrom/clairvoyance module-boundaries

For use in Claude.ai and ChatGPT