clean-code

name	clean-code
description	Apply Robert C. Martin's Clean Code principles (naming, functions, comments, formatting, error handling, tests, classes, code smells). Use when writing new code, reviewing pull requests, refactoring legacy code, or aligning on team coding standards.

Clean Code Skill

🧠 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.