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alirezarezvani on GitHub

Code Reviewer

Free

Automate your code review process for multiple languages.

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Free · Opens the source repo

What Code Reviewer does

The Code Reviewer skill provides automated tools designed to streamline the code review process across various programming languages including TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, Java, C, C++, Rust, Ruby, PHP, and Dart. This skill analyzes pull requests (PRs) for complexity and risk, checks for code quality issues such as SOLID violations and code smells, and generates comprehensive review reports. By leveraging this skill, developers can ensure that their code meets quality standards before it is merged into the main branch.

The skill is organized into several components, including a PR Analyzer, a Code Quality Checker, and a Review Report Generator. The PR Analyzer assesses the differences between branches, identifying potential risks and complexities in the code. It detects issues such as hardcoded secrets, SQL injection patterns, and other common vulnerabilities. The Code Quality Checker evaluates the source code for structural issues and compliance with best practices, while the Review Report Generator consolidates the findings into a structured report, providing clear verdicts on whether to approve or request changes.

This skill is particularly useful for teams looking to improve their code quality and maintainability by automating repetitive review tasks. It is suitable for developers and teams of all sizes who want to enforce coding standards and detect issues early in the development process. By integrating this skill into your workflow, you can save time and reduce the likelihood of introducing defects into your codebase.

Overall, the Code Reviewer skill is a valuable addition for any development team seeking to enhance their code review practices and ensure high-quality software delivery.

When to use it

Use this skill when reviewing pull requests or analyzing code quality to identify issues and generate review reports.

When not to use it

This skill may not be suitable for very small projects or teams with minimal code review needs, where manual reviews might suffice.

What you can build with it

Automating Code Reviews

Integrate the Code Reviewer into your CI/CD pipeline to automatically analyze pull requests for quality issues.

Identifying Code Smells

Use the Code Quality Checker to scan your codebase for common structural problems and improve maintainability.

Generating Review Reports

Leverage the Review Report Generator to create comprehensive reports for stakeholders after code reviews.

How to install Code Reviewer

View source

1. Install with the skills CLI

npx skills add alirezarezvani/claude-skills/code-reviewer --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by alirezarezvani

Code Reviewer

Automated code review tools for analyzing pull requests, detecting code quality issues, and generating review reports.


How This Skill Is Organized

code-reviewer/
  SKILL.md                        ← you are here (tools + dispatch table)
  rules/
    universal.md                  ← security, async, resources, exceptions, performance — all languages
  languages/
    python.md                     ← Python-specific rules + idioms
    typescript.md                 ← TypeScript / JavaScript-specific rules + idioms
    go.md                         ← Go-specific rules + idioms
    swift.md                      ← Swift-specific rules + idioms
    kotlin.md                     ← Kotlin-specific rules + idioms
    csharp.md                     ← C# / .NET-specific rules + idioms
    java.md                       ← Java-specific rules + idioms
    c.md                          ← C -specific rules + idioms
    cpp.md                        ← C++ -specific rules + idioms
    rust.md                       ← Rust -specific rules + idioms
    ruby.md                       ← Ruby -specific rules + idioms
    php.md                        ← PHP-specific rules + idioms
    dart.md                       ← Dart / Flutter-specific rules + idioms

Loading order for every review

  1. This file (SKILL.md) — tools and thresholds
  2. rules/universal.md — always, for every language
  3. The matching languages/*.md — one file based on the extension table below

That is always exactly 2 additional files, regardless of scope.

Extension(s)Load
.pylanguages/python.md
.ts, .tsx, .js, .jsx, .mjslanguages/typescript.md
.golanguages/go.md
.swiftlanguages/swift.md
.kt, .ktslanguages/kotlin.md
.cs, .csx, .razor, .cshtmllanguages/csharp.md
.javalanguages/java.md
.c, .hlanguages/c.md
.cpp, .cc, .cxx, .hpp, .hh, .hxxlanguages/cpp.md
.rslanguages/rust.md
.rb, .rake, .gemspec, .rulanguages/ruby.md
.php, .phtmllanguages/php.md
.dartlanguages/dart.md

Tools

PR Analyzer

Analyzes git diff between branches to assess review complexity and identify risks.

# Analyze current branch against main
python scripts/pr_analyzer.py /path/to/repo

# Compare specific branches
python scripts/pr_analyzer.py . --base main --head feature-branch

# JSON output for integration
python scripts/pr_analyzer.py /path/to/repo --json

What it detects (universal — see also language file for language-specific signals):

  • Hardcoded secrets (passwords, API keys, tokens, connection strings)
  • SQL / query injection patterns
  • Debug statements left in production code
  • Lint / analyzer suppression annotations
  • TODO/FIXME comments

Language-specific detections are defined in each languages/*.md file.

Output includes:

  • Complexity score (1-10)
  • Risk categorization (critical, high, medium, low)
  • File prioritization for review order
  • Commit message validation

Code Quality Checker

Analyzes source code for structural issues, code smells, and SOLID violations.

# Analyze a directory
python scripts/code_quality_checker.py /path/to/code

# Analyze specific language
# Valid values: python, typescript, javascript, go, swift, kotlin, csharp, java, c, cpp, rust, ruby, php, dart
python scripts/code_quality_checker.py . --language java

# JSON output
python scripts/code_quality_checker.py /path/to/code --json

Universal thresholds:

IssueThreshold
Long function>50 lines
Large file>500 lines
God class>20 methods
Too many params>5
Deep nesting>4 levels
High complexity>10 branches

Language-specific checks are defined in each languages/*.md file.


Review Report Generator

Combines PR analysis and code quality findings into structured review reports.

# Generate report for current repo
python scripts/review_report_generator.py /path/to/repo

# Markdown output
python scripts/review_report_generator.py . --format markdown --output review.md

# Use pre-computed analyses
python scripts/review_report_generator.py . \
  --pr-analysis pr_results.json \
  --quality-analysis quality_results.json

Verdicts:

ScoreVerdict
90+ with no high issuesApprove
75+ with ≤2 high issuesApprove with suggestions
50-74Request changes
<50 or critical issuesBlock

Adding a New Language

Reviewer guidance (required):

  1. Create languages/<name>.md using any existing language file as a template — it must have sections: PR Analyzer Signals, Code Quality Checks, Security, Async, Resource Management, Exception Handling, Performance, Idioms.
  2. Add the extension row to the dispatch table above.

That is all the agent-driven review needs.

Deterministic analyzer support (optional, recommended): the bundled scripts only flag a language they explicitly know. To make code_quality_checker.py score the new language:

  1. Add the extensions to LANGUAGE_EXTENSIONS in scripts/code_quality_checker.py (this also adds the --language choice).
  2. Add function / class / method regex entries for the language in the same file; otherwise it falls back to the Python patterns.
  3. Optionally add a check_<name>_specific_smells(...) detector (see the C#, Java, and C ones) and call it from analyze_file.
  4. Add assets/sample_<name>_smells.<ext> + _clean fixtures and commit the expected --json output under expected_outputs/ as a regression guard.

Regression Fixtures

Labelled fixtures live in assets/ with their committed --json output in expected_outputs/ (C#, Java, and C). Drift from the committed JSON signals a behaviour change in the analyzer:

python scripts/code_quality_checker.py assets/sample_java_smells.java --json \
  | diff - expected_outputs/sample_java_smells_quality.json

Frequently asked questions about Code Reviewer

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