Coding Principles

Language-Agnostic Coding Principles

Core Philosophy

1. Maintainability over Speed: Prioritize long-term code health over initial development velocity
2. Simplicity First: Choose the simplest solution that meets requirements (YAGNI principle)
3. Design Convergence: Deliver the current required outcome with the least new design surface. Selecting persistent state, public or cross-boundary contracts, behavioral modes, reusable abstractions, or component splits carries enough surface to justify the full convergence process first.
4. Explicit over Implicit: Make intentions clear through code structure and naming
5. Delete over Comment: Remove unused code instead of commenting it out

Code Quality

Continuous Improvement

• Refactor related code inside the accepted outcome and governing boundaries when it reduces the change's risk or maintenance cost
• Improve code structure incrementally
• Keep the codebase lean and focused
• Delete code proven obsolete by the requested change after checking its callers; report uncertain or out-of-scope cleanup separately

Readability

• Use meaningful, descriptive names drawn from the problem domain
• Use full words in names; abbreviations are acceptable only when widely recognized in the domain
• Use descriptive names; single-letter names are acceptable only for loop counters or well-known conventions (i, j, x, y)
• Extract magic numbers and strings into named constants
• Keep code self-documenting where possible

Function Design

Parameter Management

• Group related positional parameters into an object, struct, or dictionary when call-site clarity or coordinated evolution requires it. Retain positional parameters when their order is conventional and the call remains clear, or an external/public signature requires them
• Preserve external/public signatures unless their migration is part of the accepted outcome or governing artifact

Single Responsibility

• Each function should do one thing well
• Extract a function when independently changing responsibilities or obscured control flow make the current unit harder to understand, verify, or reuse; retain a cohesive domain flow when extraction would create artificial coupling
• Extract complex logic into separate, well-named functions
• Functions should have a single level of abstraction

Function Organization

• Pure functions when possible (no side effects)
• Separate data transformation from side effects
• Use early returns to reduce nesting
• Use early returns or extraction when nesting obscures state transitions or decision ownership; retain nested structure when it maps the domain decision more clearly

Error Handling

Error Management Principles

• Always handle errors: Log with context or propagate explicitly
• Log appropriately: Include context for debugging
• Protect sensitive data: Mask or exclude passwords, tokens, PII from logs
• Fail fast: Detect and report errors as early as possible

Error Propagation

• Use language-appropriate error handling mechanisms
• Propagate errors to appropriate handling levels
• Provide meaningful error messages
• Include error context when re-throwing

Dependency Management

Loose Coupling via Parameterized Dependencies

• Inject external dependencies as parameters (constructor injection for classes, function parameters for procedural/functional code)
• Depend on abstractions, not concrete implementations
• Minimize inter-module dependencies
• Facilitate testing through mockable dependencies

Reference Representativeness

Verifying References Before Adoption

When adopting patterns, APIs, or dependencies from existing code:

• IF a reference sample covers only nearby files → THEN confirm the pattern is representative by checking relevant repository usage before adopting
• IF multiple approaches coexist in the repository → THEN identify the majority pattern and make a deliberate choice — selecting whichever is nearest is insufficient
• IF adopting an external dependency (library, plugin, SDK) → THEN verify repository-wide usage and compatibility evidence; when that evidence cannot determine the required version, record the unresolved version decision and the evidence needed to settle it
• IF following an existing pattern → THEN state the reason for following it when an alternative exists (e.g., consistency with surrounding code, avoiding breaking changes, pending coordinated update)

Principle

Nearby code is a starting point for investigation, not a sufficient basis for adoption. Verify that what you reference is representative of the repository's conventions and current best practices before using it as a model.

Performance Considerations

Optimization Approach

• Measure first: Profile before optimizing
• Focus on algorithms: Algorithmic complexity > micro-optimizations
• Use appropriate data structures: Choose based on access patterns
• Resource management: Handle memory, connections, and files properly

When to Optimize

• After identifying actual bottlenecks through profiling
• When performance issues are measurable
• Optimize only after measurable bottlenecks are identified, not during initial development

Code Organization

Structural Principles

• Group related functionality: Keep related code together
• Separate concerns: Domain logic, data access, presentation
• Consistent naming: Follow project conventions
• Module cohesion: High cohesion within modules, low coupling between

File Organization

• One primary responsibility per file
• Logical grouping of related functions/classes
• Clear folder structure reflecting architecture
• Split a file when it contains independently changing responsibilities or creates material navigation, coupling, or verification cost; retain a cohesive file when splitting would add avoidable coupling or navigation cost