coding-principles
GitHub提供语言无关的编码原则,涵盖可维护性、可读性及函数设计等核心哲学。用于在实现功能、重构代码或审查代码质量时指导最佳实践,强调简洁、显式意图及错误处理规范。
Trigger Scenarios
Install
npx skills add shinpr/claude-code-workflows --skill coding-principles -g -y
SKILL.md
Frontmatter
{
"name": "coding-principles",
"description": "Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality."
}
Language-Agnostic Coding Principles
Core Philosophy
- Maintainability over Speed: Prioritize long-term code health over initial development velocity
- Simplicity First: Choose the simplest solution that meets requirements (YAGNI principle)
- 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.
- Explicit over Implicit: Make intentions clear through code structure and naming
- 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
Commenting Principles
Default: code first
Names, types, and structure are the primary medium. A comment earns its place only by carrying information the code itself cannot express. When in doubt, improve the name instead of adding a comment.
The test for every comment
A comment is justified only if it answers one of these:
- Why: reasoning, trade-off, or constraint behind a non-obvious decision
- Limitation / edge case: a boundary a reader cannot infer from the code
- Public API contract: behavior, inputs, outputs of an exported interface
One comment per decision. If a comment restates what the names and control flow already show, delete it and rename instead.
Comment Scope
- Comment the why, limits, and public contracts (per the test above); let names and structure carry everything else, including the "how"
- Record historical context in version control commit messages, not in comments
- Delete commented-out code (retrieve from git history when needed)
Comment Quality
- Base comments on stable rationale, limits, and contracts rather than dates, versions, or temporary state
- Update comments when changing code
- Use proper grammar and formatting
- Write for future maintainers
Refactoring Approach
Safe Refactoring
- Small steps: Make one change at a time
- Maintain working state: Keep tests passing
- Verify behavior: Run tests after each change
- Incremental improvement: Make the smallest sufficient improvement in each increment
Refactoring Triggers
- Code duplication (DRY principle)
- Functions that contain independently changing responsibilities or obscured control flow
- Complex conditional logic
- Unclear naming or structure
Security Principles
Secure Defaults
- Store credentials and secrets through environment variables or dedicated secret managers
- Use parameterized queries (prepared statements) for all database access
- Use established cryptographic libraries provided by the language or framework
- Generate security-critical values (tokens, IDs, nonces) with cryptographically secure random generators
- Encrypt sensitive data at rest and in transit using standard protocols
Input and Output Boundaries
- Validate all external input at system entry points for expected format, type, and length. External input includes request data, external service responses, model or tool output, and stored data whose writer is untrusted or whose consumer needs a guarantee the store does not make
- When a change alters a boundary where external content or model output selects a tool's action, target, or destination, verify that those values cannot exceed the operation scope and access rights already granted to the caller
- Encode output appropriately for its rendering context (HTML, SQL, shell, URL)
- Return only information necessary for the caller in error responses; log detailed diagnostics server-side
Access Control
- Apply authentication to all entry points that handle user data or trigger state changes
- Verify authorization for each resource access, not only at the entry point
- Grant only the permissions required for the operation (files, database connections, API scopes)
- For changes involving identity or protected resources, prioritize authentication and per-resource authorization review
For concrete detection patterns used by security review, see references/security-checks.md.
Version History
-
0caac06
Current 2026-09-27 15:05
刷新安全审查的范围和条件
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416af89
2026-08-12 16:40
更新持续改进章节,将重构范围从特定命名调整为基于用户或当前任务/设计工件,以更贴合实际工作流。
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29b9210
2026-08-03 04:23
移除了技能间的相互引用,改为通过命名决策类型来界定边界,避免依赖未加载的技能。
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d439b50
2026-07-31 02:54
将‘最小化设计表面’原则精简为‘设计收敛’,简化表述并移除冗余解释,使核心哲学更清晰易懂。
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56ab6c1
2026-07-19 22:45
重构提示执行指南:强化持续改进中关于代码清理和结构优化的具体操作指引,明确删除废弃代码的条件与报告机制,细化函数设计的抽象层级要求。
- 66e3b29 2026-07-05 12:01


