codebase-design
Provides a shared design language for creating deep, modular code. Use to improve interface design, seam identification, and testability.
Install
mkdir -p .claude/skills/codebase-design && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17458" && unzip -o skill.zip -d .claude/skills/codebase-design && rm skill.zipInstalls to .claude/skills/codebase-design
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.Key capabilities
- →Define modules, interfaces, and implementations.
- →Identify and create deep modules with small interfaces and large implementations.
- →Place clean seams to alter behavior without editing in that place.
- →Design for testability by accepting dependencies and returning results.
- →Evaluate module depth based on use for callers.
- →Improve code locality for maintainers.
How it works
This skill provides a shared vocabulary and principles for designing deep modules, which are characterized by a large amount of behavior behind a small interface, placed at a clean seam, and testable through that interface.
Inputs & outputs
When to use codebase-design
- →Designing a new software module interface
- →Restructuring code for better testability
- →Identifying optimal seams for decoupling systems
About this skill
Codebase Design
Design deep modules: a lot of behaviour behind a small interface, placed at a clean seam, testable through that interface. Use this language and these principles wherever code is being designed or restructured. The aim is leverage for callers, locality for maintainers, and testability for everyone.
Glossary
Use these terms exactly — don't substitute "component," "service," "API," or "boundary." Consistent language is the whole point.
Module — anything with an interface and an implementation. Deliberately scale-agnostic: a function, class, package, or tier-spanning slice. Avoid: unit, component, service.
Interface — everything a caller must know to use the module correctly: the type signature, but also invariants, ordering constraints, error modes, required configuration, and performance characteristics. Avoid: API, signature (too narrow — they refer only to the type-level surface).
Implementation — what's inside a module, its body of code. Distinct from Adapter: a thing can be a small adapter with a large implementation (a Postgres repo) or a large adapter with a small implementation (an in-memory fake). Reach for "adapter" when the seam is the topic; "implementation" otherwise.
Depth — leverage at the interface: the amount of behaviour a caller (or test) can exercise per unit of interface they have to learn. A module is deep when a large amount of behaviour sits behind a small interface, shallow when the interface is nearly as complex as the implementation.
Seam (Michael Feathers) — a place where you can alter behaviour without editing in that place; the location at which a module's interface lives. Where to put the seam is its own design decision, distinct from what goes behind it. Avoid: boundary (overloaded with DDD's bounded context).
Adapter — a concrete thing that satisfies an interface at a seam. Describes role (what slot it fills), not substance (what's inside).
Leverage — what callers get from depth: more capability per unit of interface they learn. One implementation pays back across N call sites and M tests.
Locality — what maintainers get from depth: change, bugs, knowledge, and verification concentrate in one place rather than spreading across callers. Fix once, fixed everywhere.
Deep vs shallow
Deep module = small interface + lots of implementation:
┌─────────────────────┐
│ Small Interface │ ← Few methods, simple params
├─────────────────────┤
│ │
│ Deep Implementation│ ← Complex logic hidden
│ │
└─────────────────────┘
Shallow module = large interface + little implementation (avoid):
┌─────────────────────────────────┐
│ Large Interface │ ← Many methods, complex params
├─────────────────────────────────┤
│ Thin Implementation │ ← Just passes through
└─────────────────────────────────┘
When designing an interface, ask:
- Can I reduce the number of methods?
- Can I simplify the parameters?
- Can I hide more complexity inside?
Principles
- Depth is a property of the interface, not the implementation. A deep module can be internally composed of small, mockable, swappable parts — they just aren't part of the interface. A module can have internal seams (private to its implementation, used by its own tests) as well as the external seam at its interface.
- The deletion test. Imagine deleting the module. If complexity vanishes, it was a pass-through. If complexity reappears across N callers, it was earning its keep.
- The interface is the test surface. Callers and tests cross the same seam. If you want to test past the interface, the module is probably the wrong shape.
- One adapter means a hypothetical seam. Two adapters means a real one. Don't introduce a seam unless something actually varies across it.
Designing for testability
Good interfaces make testing natural:
-
Accept dependencies, don't create them.
// Testable function processOrder(order, paymentGateway) {} // Hard to test function processOrder(order) { const gateway = new StripeGateway(); } -
Return results, don't produce side effects.
// Testable function calculateDiscount(cart): Discount {} // Hard to test function applyDiscount(cart): void { cart.total -= discount; } -
Small surface area. Fewer methods = fewer tests needed. Fewer params = simpler test setup.
Relationships
- A Module has exactly one Interface (the surface it presents to callers and tests).
- Depth is a property of a Module, measured against its Interface.
- A Seam is where a Module's Interface lives.
- An Adapter sits at a Seam and satisfies the Interface.
- Depth produces Leverage for callers and Locality for maintainers.
Rejected framings
- Depth as ratio of implementation-lines to interface-lines (Ousterhout): rewards padding the implementation. We use depth-as-leverage instead.
- "Interface" as the TypeScript
interfacekeyword or a class's public methods: too narrow — interface here includes every fact a caller must know. - "Boundary": overloaded with DDD's bounded context. Say seam or interface.
Going deeper
- Deepening a cluster given its dependencies — see DEEPENING.md: dependency categories, seam discipline, and replace-don't-layer testing.
- Exploring alternative interfaces — see DESIGN-IT-TWICE.md: spin up parallel sub-agents to design the interface several radically different ways, then compare on depth, locality, and seam placement.
When not to use it
- →Do not substitute 'component,' 'service,' 'API,' or 'boundary' for the defined terms.
Limitations
- →The skill's vocabulary is strict and does not allow substitution of terms.
- →It does not provide a quantitative metric for depth as a ratio of implementation lines to interface lines.
- →It does not cover the full scope of 'interface' as only TypeScript `interface` keyword or public methods.
How it compares
This skill offers a specific vocabulary and set of principles for designing deep modules, which differs from generic software design by focusing on use, locality, and testability through interface design.
Compared to similar skills
codebase-design side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| codebase-design (this skill) | 0 | 24d | No flags | Intermediate |
| solid-principles | 57 | 9mo | No flags | Intermediate |
| python-design-patterns | 19 | 2mo | No flags | Intermediate |
| modular-code | 4 | 6mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
solid-principles
SmidigStorm
Enforce SOLID principles (Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, Dependency Inversion) in object-oriented design. Use when writing or reviewing classes and modules.
python-design-patterns
wshobson
Python design patterns including KISS, Separation of Concerns, Single Responsibility, and composition over inheritance. Use when making architecture decisions, refactoring code structure, or evaluating when abstractions are appropriate.
modular-code
parcadei
Modular Code Organization
component-common-domain-detection
tech-leads-club
Identifies duplicate domain functionality across components and suggests consolidation opportunities. Use when finding common domain logic, detecting duplicate functionality, analyzing shared classes, planning component consolidation, or when the user asks about common components, duplicate code, or domain consolidation.
framework-migration-code-migrate
sickn33
You are a code migration expert specializing in transitioning codebases between frameworks, languages, versions, and platforms. Generate comprehensive migration plans, automated migration scripts, and
framework-migration-legacy-modernize
sickn33
Orchestrate a comprehensive legacy system modernization using the strangler fig pattern, enabling gradual replacement of outdated components while maintaining continuous business operations through ex