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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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가격 미확인★ 679 GitHub 스타목록 업데이트 · 2026년 9월 5일agent-skill

개요

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

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
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.

소스 보기 ↗

파일 메타데이터

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

원문 보기

---
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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소스 저장소: shinpr/claude-code-workflows
라이선스: MIT
버전: 1.0.0
최근 GitHub 푸시: 2026년 9월 5일
목록 업데이트: 2026년 9월 5일
지침 경로: dev-skills/skills/coding-principles/SKILL.md @ 2cfab9417b28

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품질

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강함

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추가 정보

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      "install": "npx skills add shinpr/claude-code-workflows --skill coding-principles",
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      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "coding-agents",
      "agent-skill"
    ],
    "known_risks": [
      "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"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "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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제작자: shinpr
출처: shinpr/claude-code-workflows
색인 주체: OpenAgentSkill 커뮤니티 인덱스

귀속은 공개 저장소 또는 제작자 프로필에 연결됩니다. 제작자는 등록을 주장하여 소유권 신호를 업데이트할 수 있습니다.

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이 Registry 색인 등록은 shinpr에게 귀속되어 있지만 아직 공식으로 표시되지 않았습니다. 소유권을 주장하면 확인된 소유자 신호가 추가되어 이후 출시, 설치 및 감사 업데이트를 더 신뢰할 수 있습니다.

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개발자가 저장소를 평가하는 위치에 정규 등록, 현재 신뢰 및 감사 신호, 실제 Agent-Proven 증거를 표시합니다.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/shinpr-coding-principles?metric=listed&label=Listed)](https://www.openagentskill.com/skills/shinpr-coding-principles?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
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커뮤니티 신호

이 스킬이 Agent 워크플로에 유용한지 알려 주세요. 집계된 피드백은 시간이 지날수록 순위를 개선합니다.

개요

Language-Agnostic Coding Principles

Core Philosophy

Code Quality

Continuous Improvement

Readability

Function Design

Parameter Management

Single Responsibility

Function Organization

Error Handling

Error Management Principles

Error Propagation

Dependency Management

Loose Coupling via Parameterized Dependencies

Reference Representativeness

Verifying References Before Adoption

Principle

Performance Considerations

Optimization Approach

When to Optimize

Code Organization

Structural Principles

File Organization

Commenting Principles

Default: code first

The test for every comment

Comment Scope

Comment Quality

Refactoring Approach

Safe Refactoring

Refactoring Triggers

Security Principles

Secure Defaults

Input and Output Boundaries

Access Control

소스 확인

가격 및 실행 비용

작은 작업부터 시작

출처 및 사용 안내

Agent 연결

관련 스킬

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