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coding-principles

Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality.

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价格未确认★ 679 GitHub Stars目录更新于 · 2026年9月5日agent-skill

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Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality.

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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

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
  • 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.

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文件元数据
name: coding-principles
description: Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality.
查看原始文本
---
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

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

## 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
- 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`.

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shinpr/claude-code-workflows
许可证
MIT
版本
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最近 GitHub 推送
2026年9月5日
目录更新于
2026年9月5日
技能指令路径
dev-skills/skills/coding-principles/SKILL.md @ 2cfab9417b28

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      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 77,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 73,
    "label": "Strong"
  },
  "supply": {
    "track": "Coding and developer agents",
    "scenario": "Coding agents",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "high-compliance environments without internal security review",
    "No major risk signals from current metadata",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Quality score needs review",
    "Permission surface needs review: secrets or environment access, shell or command execution"
  ],
  "agent_contract": {
    "task_input": "Use coding-principles in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 73/100 Strong shortlist",
      "Audit: 77/100 Needs review",
      "Safety: 33/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "shinpr-coding-principles (coding-principles)",
      "install_command": "npx skills add shinpr/claude-code-workflows --skill coding-principles",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "shinpr-coding-principles",
      "task": "Use coding-principles in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/shinpr-coding-principles",
    "api": "https://www.openagentskill.com/api/agent/skills/shinpr-coding-principles",
    "audit": "https://www.openagentskill.com/skills/shinpr-coding-principles/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=shinpr-coding-principles&task=Use%20coding-principles%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20coding-principles%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20coding-principles%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/shinpr-coding-principles/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/shinpr-coding-principles"
  }
}

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