clean-code

Files (7)

• SKILL.md
• code-smells.md · references/
• comments-formatting.md · references/
• error-handling.md · references/
• functions-and-methods.md · references/
• naming-conventions.md · references/
• testing-principles.md · references/

SKILL.md (first lines)

# Clean Code Framework

A disciplined approach to writing code that communicates intent, minimizes surprises, and welcomes change. Apply these principles when writing new code, reviewing pull requests, refactoring legacy systems, or advising on code quality.

## Core Principle

**Code is read far more often than it is written — optimize for the reader.** The read-to-write ratio is well over 10:1, so every naming choice, function boundary, and formatting decision either adds clarity or adds cost. Clean code reads like well-written prose: names reveal intent, functions tell a story one step at a time, and the Boy Scout Rule applies — always leave the code cleaner than you found it.

## Scoring

**Goal: 10/10.** Rate any code 0-10 against the principles below. Report the current score and the specific improvements needed to reach 10/10.

- **9-10:** Names reveal intent, each function does one thing, error handling is consistent, tests are clean and comprehensive
- **7-8:** Mostly clean with minor naming ambiguities or a few multi-purpose functions; tests may lack edge cases
- **5-6:** Mixed — good patterns alongside unclear names, duplicated logic, or inconsistent error handling
- **3-4:** Long multi-purpose functions, misleading names, poor or missing tests
- **1-2:** Nearly unreadable — magic numbers, cryptic abbreviations, no structure, no tests

## The Clean Code Framework

Six disciplines for writing code that communicates clearly and adapts to change:

### 1. Meaningful Names

**Core concept:** Names should reveal intent, avoid disinformation, and make the code read like prose. If a name requires a comment to explain it, the name is wrong.

**Why it works:** Names are the most pervasive form of documentation — a well-chosen name eliminates the need to read the implementation; a poor one forces every reader to reverse-engineer intent.

**Key insights:**
- A name should answer why it exists, what it does, and how it is used
- No encodings, prefixes, or type information (no Hungarian notation); single letters only for tiny-scope loop counters
- Classes are nouns; methods are verbs
- One word per concept: don't mix `fetch`, `retrieve`, and `get`
- Longer scope demands a longer, more descriptive name
- Rename freely — IDEs make it trivial

**Code applications:**

| Context | Pattern | Example |
|---------|---------|---------|
| **Variables** | Intention-revealing | `elapsedTimeInDays` not `d` |
| **Booleans** | Predicate phrasing | `isActive`, `hasPermission`, `canEdit` |
| **Functions** | Verb + noun | `calculateMonthlyRevenue()` not `calc()` |
| **Classes** | Noun naming the responsibility | `InvoiceGenerator` not `InvoiceManager` |

See: [references/naming-conventions.md](references/naming-conventions.md)

### 2. Functions

**Core concept:** A function does one thing at one level of abstraction, with zero to two arguments. Split it when it does two things, not when it passes a line count: a long function with one job behind a small signature is a deep module (see `/code-organisation`).

**Why it works:** Single-purpose functions are easy to name, understand, test, and reuse; multi-purpose functions hide bugs, resist testing, and accumulate responsibilities. Length is a reason to look for a second job, not proof of one.

**Key insights:**
- Step-Down Rule: code reads top-down, each function calling the next level of abstraction
- Argument count: zero best, one fine, two acceptable, three+ requires justification
- Flag arguments are a smell — the function does two things; split it
- Command-Query Separation: change state or return a value, never both
- Extract a block when it has its own name and its own job; an extraction that only renames a few lines adds a hop, not a concept
- No hidden side effects — the name must tell the whole truth

**Code applications:**

| Context | Pattern | Example |
|---------|---------|---------|
| **Multi-purpose function** | Extract each job as a named step | `validateInput(); transformData(); saveRecord();` |
| **Flag argument** | Split into two functions | `renderForPrint()` / `renderForScreen()` not `render(isPrint)` |
| **Error cases** | Guard clauses at top | Early return for errors, single happy path |
| **Many arguments** | Introduce parameter object | `new DateRange(start, end)` not `report(start, end, format, locale)` |
| **Side effects** | Make effects explicit | `checkPassword()` that starts a session → rename or separate |

See: [references/functions-and-methods.md](references/functions-and-methods.md)

### 3. Comments and Formatting

**Core concept:** A comment is a failure to express yourself in code. When comments are necessary, they explain *why*, never *what*. Formatting creates the visual structure that makes code scannable.

**Why it works:** Comments rot — code changes but comments often don't, creating documentation worse than none. Clean formatting lets developers scan code like a newspaper: headlines first, details on demand.

**Key insights:**
- The best comment is a well-named extracted function
- Acceptable: legal headers, TODOs, public API docs, genuine "why" explanations
- Commented-out code and journal comments: delete — version control remembers
- Vertical openness between concepts; vertical density within them; declare variables near usage
- Newspaper metaphor: high-level functions at the top of the file, details below

**Code applications:**

| Context | Pattern | Example |
|---------|---------|---------|
| **Explaining "what"** | Replace with better name | `// check if eligible` → `isEligible()` |
| **Explaining "why"** | Keep as comment | `// RFC 7231 requires this header for proxies` |
| **Commented-out code** | Delete it | Trust version control |
| **Team formatting** | Decide once, automate | Prettier, Black, gofmt |

See: [references/comments-formatting.md](references/comments-formatting.md)

### 4. Error Handling

**Core concept:** Error handling is a separate concern from business logic. Use exceptions rather than return codes, provide context with every exception, and never return or pass null.

**Why it works:** Return codes clutter the happy path with checks; exceptions separate the two cleanly. Returning null forces null checks on every caller, and one missing check crashes far from the source.

**Key insights:**
- Write the try-catch first — it defines a transaction boundary
- Prefer unchecked exceptions — checked ones violate the Open/Closed Principle
- Define exception classes by the caller's needs, not the failure type
- Don't return null (use empty collections, Optional, or throw); don't pass null either
- Special Case / Null Object pattern: return an object with default behavior instead of null

**Code applications:**

| Context | Pattern | Example |
|---------|---------|---------|
| **Null returns** | Empty collection or Optional | `return Collections.emptyList()` not `return null` |
| **Error codes** | Replace with exceptions | `throw new InsufficientFundsException(balance, amount)` |
| **Third-party APIs** | Wrap with adapter | `PortfolioService` wraps the vendor API, translates its exceptions |
| **Special cases** | Null Object pattern | `GuestUser` with default behavior instead of null checks |
| **Context in errors** | Include operation + state | `"Failed to save invoice #1234 for customer 'Acme'"` |

From jd-solanki/ai, MIT.

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