Code Quality Review
Overview
Conducts systematic code quality analysis across multiple dimensions: maintainability, readability, complexity, design patterns, naming conventions, code duplication, and adherence to best practices. Produces actionable feedback with severity ratings and specific improvement recommendations.
Core Capabilities
- Code Smells Detection - Identifies bloaters, object-orientation abusers, change preventers, dispensables, and couplers
- Complexity Analysis - Measures cyclomatic and cognitive complexity with risk assessment
- Maintainability Assessment - Evaluates code maintainability index and technical debt
- Design Pattern Evaluation - Reviews architectural patterns and SOLID principles
- Best Practices Validation - Checks adherence to language-specific standards and conventions
Review Workflow
Step 1: Scope Assessment
Determine review scope based on change size:
- Small (<100 lines): Quick correctness check, 15-30 minutes
- Medium (100-500 lines): Full quality analysis, 1-2 hours
- Large (>500 lines): Architectural review, break into smaller reviews if possible, 2-4 hours
For scope-specific guidance, see review-scope-guidelines.md
Step 2: Initial Assessment
Gather Context:
- Identify programming language and framework
- Understand project type (web app, API, library, CLI, etc.)
- Note existing coding standards or style guides
- Check for linter configuration files (.eslintrc, .pylintrc, checkstyle.xml, etc.)
Read the Code:
- Start with entry points (main files, index files)
- Review module/package organization
- Check dependency management
- Examine test files if available
Step 3: Quality Analysis
Analyze code across key dimensions:
- Code Smells: Long methods, large classes, duplicate code, dead code, etc.
- Complexity: Cyclomatic complexity (target <15), cognitive complexity, nesting depth
- Maintainability: Clear naming, proper abstraction, separation of concerns
- Design Patterns: Appropriate pattern usage, SOLID principles adherence
- Best Practices: Language idioms, error handling, resource management
For detailed analysis criteria and thresholds, see review-workflow.md
For quality metrics and thresholds, see quality-metrics-reference.md
Step 4: Document Findings
Structure the review report with:
- Executive summary with scores and top priorities
- Detailed findings with severity, location, description, and recommendations
- Metrics summary with current vs. target values
- Prioritized recommendations (P0-P3)
- Positive observations acknowledging good practices
- Technical debt summary with effort estimates
For complete report structure and output guidelines, see review-report-format.md
Quality Assurance
Use the checklist to ensure comprehensive reviews:
- Code organization and structure
- Naming conventions and clarity
- Complexity thresholds
- Error handling patterns
- Testing and documentation
- Security considerations
- Performance implications
For complete checklist, see best-practices-checklist.md
Common Pitfalls
Avoid these common review mistakes:
- Focusing only on style issues instead of substantive problems
- Being overly critical without actionable suggestions
- Ignoring context and business constraints
- Overwhelming with too many issues at once
- Using vague terms without explanation
- Forgetting to acknowledge good practices
For detailed guidance, see common-pitfalls-to-avoid.md
Example Patterns
For reference when identifying critical issues in your review, see examples of common high-severity problems in critical-issues.md
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1---2name: code-quality-review-33description: Conducts comprehensive code quality reviews including code smells detection, maintainability assessment, complexity analysis, design pattern evaluation, naming conventions, code duplication, technical debt identification, and best practices validation. Produces detailed review reports with specific issues, severity ratings, metrics analysis, and actionable improvement recommendations. Use when reviewing code quality, analyzing code maintainability, detecting code smells, checking coding standards, measuring code complexity, identifying technical debt, or when users mention "code quality review", "code quality check", "maintainability analysis", "code smells", "clean code", "refactoring candidates", or "technical debt assessment". Use when this capability is needed.4---56# Code Quality Review78## Overview910Conducts systematic code quality analysis across multiple dimensions: maintainability, readability, complexity, design patterns, naming conventions, code duplication, and adherence to best practices. Produces actionable feedback with severity ratings and specific improvement recommendations.1112## Core Capabilities13141. **Code Smells Detection** - Identifies bloaters, object-orientation abusers, change preventers, dispensables, and couplers152. **Complexity Analysis** - Measures cyclomatic and cognitive complexity with risk assessment163. **Maintainability Assessment** - Evaluates code maintainability index and technical debt174. **Design Pattern Evaluation** - Reviews architectural patterns and SOLID principles185. **Best Practices Validation** - Checks adherence to language-specific standards and conventions1920## Review Workflow2122## Step 1: Scope Assessment2324Determine review scope based on change size:2526- **Small (<100 lines)**: Quick correctness check, 15-30 minutes27- **Medium (100-500 lines)**: Full quality analysis, 1-2 hours 28- **Large (>500 lines)**: Architectural review, break into smaller reviews if possible, 2-4 hours2930For scope-specific guidance, see [review-scope-guidelines.md](references/review-scope-guidelines.md)3132### Step 2: Initial Assessment3334**Gather Context:**3536- Identify programming language and framework37- Understand project type (web app, API, library, CLI, etc.)38- Note existing coding standards or style guides39- Check for linter configuration files (.eslintrc, .pylintrc, checkstyle.xml, etc.)4041**Read the Code:**4243- Start with entry points (main files, index files)44- Review module/package organization45- Check dependency management46- Examine test files if available4748### Step 3: Quality Analysis4950Analyze code across key dimensions:5152- **Code Smells**: Long methods, large classes, duplicate code, dead code, etc.53- **Complexity**: Cyclomatic complexity (target <15), cognitive complexity, nesting depth54- **Maintainability**: Clear naming, proper abstraction, separation of concerns55- **Design Patterns**: Appropriate pattern usage, SOLID principles adherence56- **Best Practices**: Language idioms, error handling, resource management5758For detailed analysis criteria and thresholds, see [review-workflow.md](references/review-workflow.md)5960For quality metrics and thresholds, see [quality-metrics-reference.md](references/quality-metrics-reference.md)6162### Step 4: Document Findings6364Structure the review report with:6566- Executive summary with scores and top priorities67- Detailed findings with severity, location, description, and recommendations68- Metrics summary with current vs. target values69- Prioritized recommendations (P0-P3)70- Positive observations acknowledging good practices71- Technical debt summary with effort estimates7273For complete report structure and output guidelines, see [review-report-format.md](references/review-report-format.md)7475## Quality Assurance7677Use the checklist to ensure comprehensive reviews:7879- Code organization and structure80- Naming conventions and clarity81- Complexity thresholds82- Error handling patterns83- Testing and documentation84- Security considerations85- Performance implications8687For complete checklist, see [best-practices-checklist.md](references/best-practices-checklist.md)8889## Common Pitfalls9091Avoid these common review mistakes:9293- Focusing only on style issues instead of substantive problems94- Being overly critical without actionable suggestions95- Ignoring context and business constraints96- Overwhelming with too many issues at once97- Using vague terms without explanation98- Forgetting to acknowledge good practices99100For detailed guidance, see [common-pitfalls-to-avoid.md](references/common-pitfalls-to-avoid.md)101102## Example Patterns103104For reference when identifying critical issues in your review, see examples of common high-severity problems in [critical-issues.md](references/critical-issues.md)105106---107> Converted and distributed by [TomeVault](https://tomevault.io/claim/dauquangthanh) — claim your Tome and manage your conversions.108<!-- tomevault:4.0:skill_md:2026-04-11 -->