code-quality

name	code-quality
description	Code quality standards. Defines complexity management, modular design, code smell detection, comment standards. Applied automatically when writing or reviewing code. Invoke directly to clean up comments in a file. Triggers on: 'clean up comments', 'comment cleanup', '/code-quality'.
argument-hint	[file_path]

Programming Philosophy and Quality Standards

Core Philosophy

• Code is primarily written for humans to read and maintain; machine execution is a by-product
• Priority: Readability & Maintainability > Correctness > Performance > Code length
• Follow idiomatic practices of each language community

Complexity Management

Complexity = Dependencies + Obscurity

Symptoms to Watch For

Symptom	Description
Change Amplification	Small changes require modifications in many places
Cognitive Load	Developers need excessive information to complete tasks
Unknown Unknowns	Unclear what code needs modification (worst symptom)

Mitigation Strategies

• "Zero tolerance" for incremental complexity growth
• Invest time upfront in design
• Avoid tactical shortcuts that create technical debt

Modular Design Principles

Design deep modules: a lot of behaviour behind a small interface, placed at a clean seam. Hide design decisions inside implementations; combat over-specialization and "classitis". For the full vocabulary (module, interface, seam, adapter, depth, leverage, locality) and design procedures, use the codebase-design skill.

Code Smells to Watch For

Proactively identify and flag:

• Duplicated logic / copy-paste code
• Over-tight coupling or circular dependencies
• Fragile designs where one change breaks unrelated parts
• Unclear intent, confused abstractions, vague naming
• Over-engineering without real benefit

When identifying code smells:

• Explain the problem concisely
• Provide 1–2 refactoring directions with pros/cons

Error Handling Strategy

• Define errors out of existence — design APIs with no exceptions when possible
• Mask exceptions at low levels to protect higher layers
• Aggregate exceptions with general-purpose handlers
• Just crash for rare, unrecoverable errors

Comment Standards

• Self-documenting code first — improve naming and structure before adding comments
• WHY over WHAT — comments explain intent and reasoning, not mechanics
• Reduce cognitive load — make implicit knowledge explicit
• Zero redundancy — never restate what code already expresses

DO comment: design decisions/trade-offs, non-obvious behavior, interface contracts, gotchas/edge cases, cross-module dependencies

DON'T comment: self-evident code, well-named variables/functions, standard patterns, implementation details visible in code

When modifying code:

1. Remove comments that restate what code does
2. Keep comments that explain WHY
3. Add comments only for non-obvious behavior or design decisions
4. Update stale comments when code changes invalidate them
5. Never add comments just to fill space or appear thorough

Comment Cleanup Procedure

When invoked directly with a file path (/code-quality <file>), clean up its comments per the Comment Standards above:

1. Read the file to understand its purpose and structure
2. Suggest naming improvements that make code self-documenting, applying them if safe
3. Remove comments that restate code, add noise, or are outdated
4. Add comments only where they explain non-obvious behavior, design decisions, complex algorithms, or essential interface contracts
5. Leave the file cleaner than found