
System Design
- 3 installs
- 725 repo stars
- Updated July 30, 2026
- joelhooks/swarm-tools
Applies A Philosophy of Software Design principles (deep modules, information hiding, complexity red flags) when designing modules, APIs, or CLIs.
About
A reference skill distilling John Ousterhout's software-design principles into rules for deep modules, information hiding, and defining errors out of existence. A developer uses it when designing reusable modules, APIs, or CLI tools and wants to keep interfaces simple and complexity contained.
- Make deep modules: simple interface hiding rich functionality
- Red-flag table covering shallow modules, information leakage, and temporal decomposition
System Design by the numbers
- 3 all-time installs (skills.sh)
- Ranked #923 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/joelhooks/swarm-tools --skill system-designAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 3 |
|---|---|
| repo stars | ★ 725 |
| Last updated | July 30, 2026 |
| Repository | joelhooks/swarm-tools ↗ |
What it does
Applies A Philosophy of Software Design principles (deep modules, information hiding, complexity red flags) when designing modules, APIs, or CLIs.
Files
System Design
Principles for building reusable, maintainable coding systems. From "A Philosophy of Software Design" by John Ousterhout.
Core Principle: Fight Complexity
Complexity is the root cause of most software problems. It accumulates incrementally—each shortcut adds a little, until the system becomes unmaintainable.
Complexity defined: Anything that makes software hard to understand or modify.
Symptoms:
- Change amplification: simple change requires many modifications
- Cognitive load: how much you need to know to make a change
- Unknown unknowns: not obvious what needs to change
Deep Modules
The most important design principle: make modules deep.
┌─────────────────────────────┐
│ Simple Interface │ ← Small surface area
├─────────────────────────────┤
│ │
│ │
│ Deep Implementation │ ← Lots of functionality
│ │
│ │
└─────────────────────────────┘Deep module: Simple interface, lots of functionality hidden behind it.
Shallow module: Complex interface relative to functionality provided. Red flag.
Examples
Deep: Unix file I/O - just 5 calls (open, read, write, lseek, close) hide enormous complexity (buffering, caching, device drivers, permissions, journaling).
Shallow: Java's file reading requires BufferedReader wrapping FileReader wrapping FileInputStream. Interface complexity matches implementation complexity.
Apply This
- Prefer fewer methods that do more over many small methods
- Hide implementation details aggressively
- A module's interface should be much simpler than its implementation
- If interface is as complex as implementation, reconsider the abstraction
Strategic vs Tactical Programming
Tactical: Get it working now. Each task adds small complexities. Debt accumulates.
Strategic: Invest time in good design. Slower initially, faster long-term.
Progress
│
│ Strategic ────────────────→
│ /
│ /
│ / Tactical ─────────→
│ / ↘ (slows down)
│ /
└──┴─────────────────────────────────→ TimeRule of thumb: Spend 10-20% of development time on design improvements.
Working Code Isn't Enough
"Working code" is not the goal. The goal is a great design that also works. If you're satisfied with "it works," you're programming tactically.
Information Hiding
Each module should encapsulate knowledge that other modules don't need.
Information leakage (red flag): Same knowledge appears in multiple places. If one changes, all must change.
Temporal decomposition (red flag): Splitting code based on when things happen rather than what information they use. Often causes leakage.
Apply This
- Ask: "What knowledge does this module encapsulate?"
- If the answer is "not much," the module is probably shallow
- Group code by what it knows, not when it runs
- Private by default; expose only what's necessary
Define Errors Out of Existence
Exceptions add complexity. The best way to handle them: design so they can't happen.
Instead of:
function deleteFile(path: string): void {
if (!exists(path)) throw new FileNotFoundError();
// delete...
}Do:
function deleteFile(path: string): void {
// Just delete. If it doesn't exist, goal is achieved.
// No error to handle.
}Apply This
- Redefine semantics so errors become non-issues
- Handle edge cases internally rather than exposing them
- Fewer exceptions = simpler interface = deeper module
- Ask: "Can I change the definition so this isn't an error?"
General-Purpose Modules
Somewhat general-purpose modules are deeper than special-purpose ones.
Not too general: Don't build a framework when you need a function.
Not too specific: Don't hardcode assumptions that limit reuse.
Sweet spot: Solve today's problem in a way that naturally handles tomorrow's.
Questions to Ask
1. What is the simplest interface that covers all current needs? 2. How many situations will this method be used in? 3. Is this API easy to use for my current needs?
Pull Complexity Downward
When complexity is unavoidable, put it in the implementation, not the interface.
Bad: Expose complexity to all callers. Good: Handle complexity once, internally.
It's more important for a module to have a simple interface than a simple implementation.
Example
Configuration: Instead of requiring callers to configure everything, provide sensible defaults. Handle the complexity of choosing defaults internally.
Design Twice
Before implementing, consider at least two different designs. Compare them.
Benefits:
- Reveals assumptions you didn't know you were making
- Often the second design is better
- Even if first design wins, you understand why
Don't skip this: "I can't think of another approach" usually means you haven't tried hard enough.
Red Flags Summary
| Red Flag | Symptom |
|---|---|
| Shallow module | Interface complexity ≈ implementation complexity |
| Information leakage | Same knowledge in multiple modules |
| Temporal decomposition | Code split by time, not information |
| Overexposure | Too many methods/params in interface |
| Pass-through methods | Method does little except call another |
| Repetition | Same code pattern appears multiple times |
| Special-general mixture | General-purpose code mixed with special-purpose |
| Conjoined methods | Can't understand one without reading another |
| Comment repeats code | Comment says what code obviously does |
| Vague name | Name doesn't convey much information |
Applying to CLI/Tool Design
When building CLIs, plugins, or tools:
1. Deep commands: Few commands that do a lot, not many shallow ones 2. Sensible defaults: Work without configuration for common cases 3. Progressive disclosure: Simple usage first, advanced options available 4. Consistent interface: Same patterns across all commands 5. Error elimination: Design so common mistakes are impossible
Example: Good CLI Design
# Deep: one command handles the common case well
swarm setup
# Not shallow: doesn't require 10 flags for basic usage
# Sensible defaults: picks reasonable models
# Progressive: advanced users can customize laterKey Takeaways
1. Complexity is the enemy. Every design decision should reduce it. 2. Deep modules win. Simple interface, rich functionality. 3. Hide information. Each module owns specific knowledge. 4. Define errors away. Change semantics to eliminate edge cases. 5. Design twice. Always consider alternatives. 6. Strategic > tactical. Invest in design, not just working code. 7. Pull complexity down. Implementation absorbs complexity, interface stays simple.