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clean-code

This skill embodies the principles of "Clean Code" by Robert C. Martin (Uncle Bob). Use it to transform "code that works" into "code that is clean."

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Clean Code Skill

This skill embodies the principles of "Clean Code" by Robert C. Martin (Uncle Bob). Use it to transform "code that works" into "code that is clean."

🧠 Core Philosophy

"Code is clean if it can be read, and enhanced by a developer other than its original author." — Grady Booch

When to Use

Use this skill when:

  • Writing new code: To ensure high quality from the start.
  • Reviewing Pull Requests: To provide constructive, principle-based feedback.
  • Refactoring legacy code: To identify and remove code smells.
  • Improving team standards: To align on industry-standard best practices.

1. Meaningful Names

  • Use Intention-Revealing Names: elapsedTimeInDays instead of d.
  • Avoid Disinformation: Don't use accountList if it's actually a Map.
  • Make Meaningful Distinctions: Avoid ProductData vs ProductInfo.
  • Use Pronounceable/Searchable Names: Avoid genymdhms.
  • Class Names: Use nouns (Customer, WikiPage). Avoid Manager, Data.
  • Method Names: Use verbs (postPayment, deletePage).

2. Functions

  • Small!: Functions should be shorter than you think.
  • Do One Thing: A function should do only one thing, and do it well.
  • One Level of Abstraction: Don't mix high-level business logic with low-level details (like regex).
  • Descriptive Names: isPasswordValid is better than check.
  • Arguments: 0 is ideal, 1-2 is okay, 3+ requires a very strong justification.
  • No Side Effects: Functions shouldn't secretly change global state.

3. Comments

  • Don't Comment Bad Code—Rewrite It: Most comments are a sign of failure to express ourselves in code.
  • Explain Yourself in Code:
    # Check if employee is eligible for full benefits
    if employee.flags & HOURLY and employee.age > 65:
    
    vs
    if employee.isEligibleForFullBenefits():
    
  • Good Comments: Legal, Informative (regex intent), Clarification (external libraries), TODOs.
  • Bad Comments: Mumbling, Redundant, Misleading, Mandated, Noise, Position Markers.

4. Formatting

  • The Newspaper Metaphor: High-level concepts at the top, details at the bottom.
  • Vertical Density: Related lines should be close to each other.
  • Distance: Variables should be declared near their usage.
  • Indentation: Essential for structural readability.

5. Objects and Data Structures

  • Data Abstraction: Hide the implementation behind interfaces.
  • The Law of Demeter: A module should not know about the innards of the objects it manipulates. Avoid a.getB().getC().doSomething().
  • Data Transfer Objects (DTO): Classes with public variables and no functions.

6. Error Handling

  • Use Exceptions instead of Return Codes: Keeps logic clean.
  • Write Try-Catch-Finally First: Defines the scope of the operation.
  • Don't Return Null: It forces the caller to check for null every time.
  • Don't Pass Null: Leads to NullPointerException.

7. Unit Tests

  • The Three Laws of TDD:
    1. Don't write production code until you have a failing unit test.
    2. Don't write more of a unit test than is sufficient to fail.
    3. Don't write more production code than is sufficient to pass the failing test.
  • F.I.R.S.T. Principles: Fast, Independent, Repeatable, Self-Validating, Timely.

8. Classes

  • Small!: Classes should have a single responsibility (SRP).
  • The Stepdown Rule: We want the code to read like a top-down narrative.

9. Smells and Heuristics

  • Rigidity: Hard to change.
  • Fragility: Breaks in many places.
  • Immobility: Hard to reuse.
  • Viscosity: Hard to do the right thing.
  • Needless Complexity/Repetition.

🛠️ Implementation Checklist

  • Is this function smaller than 20 lines?
  • Does this function do exactly one thing?
  • Are all names searchable and intention-revealing?
  • Have I avoided comments by making the code clearer?
  • Am I passing too many arguments?
  • Is there a failing test for this change?

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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