home / skills / ratacat / claude-skills / clean-code

clean-code skill

/skills/clean-code

This skill helps you write and review clean code by applying naming, structure, and error-handling practices from Clean Code.

npx playbooks add skill ratacat/claude-skills --skill clean-code

Review the files below or copy the command above to add this skill to your agents.

Files (8)
SKILL.md
9.4 KB
---
name: clean-code
description: Use when writing, reviewing, or refactoring code. Apply when naming variables or functions, structuring classes, handling errors, writing tests, or when code feels complex or hard to understand. Based on Robert C. Martin's Clean Code.
---

# Clean Code

## Overview

Clean code reads like well-written prose. Every name reveals intent. Every function tells a story. Every class has a single purpose. The goal isn't just working code—it's code that others can understand quickly, modify safely, and extend confidently.

> "Clean code always looks like it was written by someone who cares." — Michael Feathers

> "You know you are working on clean code when each routine turns out to be pretty much what you expected." — Ward Cunningham

**The Boy Scout Rule:** Leave the code cleaner than you found it. Every commit should improve quality, even if just slightly. Small improvements compound.

## Chapter References

This skill provides an overview with quick references. For detailed guidance with examples, see the chapter files:

- `chapters/names.md` - Meaningful Names (intention-revealing, searchable, pronounceable)
- `chapters/functions.md` - Functions (small, do one thing, few arguments)
- `chapters/comments.md` - Comments (why to avoid, what's acceptable)
- `chapters/objects-and-data.md` - Objects and Data Structures (Law of Demeter, DTOs)
- `chapters/error-handling.md` - Error Handling (exceptions, null handling, Special Case Pattern)
- `chapters/tests.md` - Unit Tests (TDD, F.I.R.S.T., clean tests)
- `chapters/classes.md` - Classes (SRP, cohesion, OCP, DIP)
- `smells-and-heuristics.md` - Complete code smells reference (66 smells with explanations)

## Quick Reference: Names

Names should reveal intent and be searchable.

| Rule | Bad | Good |
|------|-----|------|
| Reveal intent | `d` | `elapsedTimeInDays` |
| Avoid disinformation | `accountList` (not a List) | `accounts` |
| Make distinctions | `a1, a2` | `source, destination` |
| Pronounceable | `genymdhms` | `generationTimestamp` |
| Searchable | `7` | `MAX_CLASSES_PER_STUDENT` |
| Classes = nouns | `Process` | `Customer`, `Account` |
| Methods = verbs | `data` | `postPayment()`, `save()` |

**Avoid:** `Manager`, `Processor`, `Data`, `Info` in class names—they hint at unclear responsibilities.

**Key insight:** If you need a comment to explain what a variable is, rename it instead.

## Quick Reference: Functions

### Size and Scope
- **Ideal:** 4-10 lines, rarely over 20
- **Indent level:** Never more than one or two
- **Do one thing** — if you can extract another function with a non-restating name, it's doing too much

### Arguments
| Count | Guidance |
|-------|----------|
| 0 | Best |
| 1 | Good |
| 2 | Acceptable |
| 3+ | Avoid—wrap in object |

**Flag arguments (booleans) are ugly.** They proclaim the function does two things. Split it:
```python
# Bad
def render(is_suite: bool): ...

# Good
def render_for_suite(): ...
def render_for_single_test(): ...
```

### Key Rules
- **Command Query Separation:** Do something OR answer something, not both
- **No side effects:** If `checkPassword()` also initializes a session, it lies
- **Prefer exceptions to error codes:** Separates happy path from error handling
- **Extract try/catch blocks:** Error handling is one thing

## Quick Reference: Comments

> Comments are, at best, a necessary evil. The proper use of comments is to compensate for our failure to express ourselves in code.

### Delete These Comments
- **Redundant** — restating what code says
- **Journal/changelog** — use git
- **Commented-out code** — an abomination, git remembers
- **Noise** — `// default constructor`, `// increment i`
- **Closing brace** — `} // end if` means too much nesting

### Acceptable Comments
- Legal notices
- Explanation of intent (why, not what)
- Warning of consequences (`// takes 30 minutes`)
- TODO (but clean them up)
- Clarifying external library behavior

**The Rule:** When you feel the urge to comment, first try to refactor the code so the comment would be unnecessary.

## Quick Reference: Error Handling

**Error handling is important, but if it obscures logic, it's wrong.**

| Rule | Details |
|------|---------|
| Use exceptions over return codes | Separates algorithm from error handling |
| Provide context | Include operation that failed and type of failure |
| Wrap third-party APIs | Minimizes dependencies, enables mocking |
| Use Special Case Pattern | Return object that handles special case (empty list, default values) |
| **Don't return null** | Creates work, invites NullPointerException |
| **Don't pass null** | Worse than returning null—forbid it by default |

```python
# Bad - null checks everywhere
if employees is not None:
    for e in employees:
        total += e.pay

# Good - return empty collection instead of null
for e in get_employees():  # Returns [] if none
    total += e.pay
```

## Quick Reference: Classes

### Single Responsibility Principle (SRP)
> A class should have one, and only one, reason to change.

**Tests:**
- Can you derive a concise name? (Avoid `Manager`, `Processor`, `Super`)
- Can you describe it in 25 words without "if," "and," "or," "but"?

### Cohesion
Methods should use the class's instance variables. When methods cluster around certain variables but not others, the class should be split.

### Open-Closed Principle (OCP)
Classes should be open for extension but closed for modification. Add new behavior via subclassing, not modifying existing code.

### Dependency Inversion Principle (DIP)
Depend on abstractions, not concrete details. Inject dependencies for testability.

```python
# Bad - can't test without network
class Portfolio:
    def __init__(self):
        self.exchange = TokyoStockExchange()

# Good - injectable, testable
class Portfolio:
    def __init__(self, exchange: StockExchange):
        self.exchange = exchange
```

## Quick Reference: Tests

### The Three Laws of TDD
1. Don't write production code until you have a failing test
2. Don't write more test than sufficient to fail
3. Don't write more production code than sufficient to pass

### F.I.R.S.T. Principles
- **Fast** — Run quickly so you run them often
- **Independent** — Don't depend on each other
- **Repeatable** — Same result in any environment
- **Self-Validating** — Boolean output (pass/fail)
- **Timely** — Written just before production code

### Clean Tests
- **Readability** is paramount
- Use **BUILD-OPERATE-CHECK** pattern
- Create domain-specific testing language
- **One concept per test** (not necessarily one assert)

**Warning:** Test code is just as important as production code. If you let tests rot, your code will rot too.

## Objects vs Data Structures

| Concept | Hides | Exposes | Easy to add... |
|---------|-------|---------|----------------|
| Objects | Data | Functions | New types |
| Data Structures | Nothing | Data | New functions |

**The idea that everything is an object is a myth.** Sometimes you want simple data structures with procedures operating on them.

### Law of Demeter
A method should only call methods of:
- The class itself
- Objects it creates
- Objects passed as arguments
- Objects held in instance variables

**Don't** call methods on objects returned by allowed functions (train wrecks):
```python
# Bad
output_dir = ctxt.get_options().get_scratch_dir().get_absolute_path()

# Good - tell the object to do the work
bos = ctxt.create_scratch_file_stream(class_file_name)
```

## The Most Critical Smells

From Chapter 17's comprehensive list, these are the most important:

### G5: Duplication
**The root of all evil in software.** Every duplication is a missed abstraction opportunity:
- Identical code → extract to function
- Repeated switch/if-else → polymorphism
- Similar algorithms → Template Method or Strategy pattern

### G30: Functions Should Do One Thing
If you can extract another function from it, the original was doing more than one thing.

### N1: Choose Descriptive Names
Names are 90% of what makes code readable. Take time to choose wisely.

### F1: Too Many Arguments
Zero is best, then one, two, three. More requires justification.

### F3: Flag Arguments
Boolean parameters mean the function does two things. Split it.

### G9: Dead Code
Code that isn't executed. Delete it—version control remembers.

### G11: Inconsistency
If you do something one way, do all similar things the same way.

### C5: Commented-Out Code
An abomination. Delete it immediately.

## The Craft

> "Writing clean code requires the disciplined use of a myriad little techniques applied through a painstakingly acquired sense of 'cleanliness.' The code-sense is the key."

Clean code isn't written by following rules mechanically. It comes from values that drive disciplines—caring about craft, respecting readers of your code, and taking pride in professional work.

**How do you write clean code?** First drafts are clumsy—long functions, nested loops, arbitrary names, duplication. You refine: break out functions, change names, eliminate duplication, shrink methods. Nobody writes clean code from the start.

Getting software to work and making it clean are different activities. Most of us have limited room in our heads, so we focus on getting code to work first. **The problem is that too many of us think we are done once the program works.** We fail to switch to organization and cleanliness. We move on to the next problem rather than going back and breaking overstuffed classes into decoupled units.

Don't. Go back. Clean it up. Leave it better than you found it.

Overview

This skill distills principles from Clean Code to help you write, review, and refactor readable, maintainable code. It focuses on naming, function and class design, error handling, tests, and common smells so your code communicates intent and resists rot. Use it to turn working-but-messy code into clear, trustworthy code that others can change safely.

How this skill works

The skill inspects code structure and suggests concrete, actionable improvements: better names, smaller functions, clearer responsibilities for classes, and safer error handling. It highlights smells like duplication, long functions, flag arguments, dead code, and commented-out code, and recommends targeted refactorings and test hygiene. Recommendations are pragmatic and aimed at making the minimal change that yields maximal clarity.

When to use it

  • When naming variables, functions, classes, or public APIs
  • While writing or reviewing functions that feel long, complex, or have many arguments
  • When classes mix responsibilities or methods cluster around different data
  • When error handling is scattered, returns nulls, or obscures the main flow
  • When tests are slow, brittle, or difficult to understand
  • During code cleanup commits to incrementally improve quality (Boy Scout Rule)

Best practices

  • Choose intention-revealing, pronounceable, and searchable names; avoid vague terms like Manager or Data
  • Keep functions small (4–10 lines if practical), with one responsibility and few arguments
  • Prefer exceptions to error codes, return empty collections not null, and wrap third-party APIs
  • Apply SRP: give each class one reason to change; split classes that lack cohesion
  • Write clean, fast, independent tests following F.I.R.S.T.; use BUILD-OPERATE-CHECK
  • Eliminate duplication first; treat commented-out code and dead code as removable

Example use cases

  • Refactor a long utility function that mixes parsing, validation, and persistence into focused helpers
  • Rename cryptic variables and functions to improve code review throughput
  • Split a God class into smaller classes with injected dependencies for testability
  • Replace boolean flag arguments with separate functions to clarify intent
  • Improve test suite speed and reliability by removing shared state and making tests independent

FAQ

How aggressive should I be when refactoring a working feature?

Be conservative: prioritize refactors that reduce risk and improve clarity. Use small commits, keep tests passing, and apply the Boy Scout Rule—leave code slightly cleaner with each change.

When is a comment acceptable?

Only to explain intent, rationale, or non-obvious consequences. If a comment explains what code does, prefer renaming or restructuring so the code itself communicates that intent.