code-reviewer
Code review automation for TypeScript, JavaScript, Python, Go, Swift, and Kotlin. Analyzes PRs for complexity, risk, SOLID violations, and code smells. Use when reviewing PRs, analyzing code quality, or generating review checklists.
- Installs
- 187
- Last 24h
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- Trending rank
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- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/borghei/claude-skills --skill code-reviewer- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads code-reviewer automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Code Reviewer
Automated code review tooling that analyzes pull requests for complexity and risk, scans source for code smells and SOLID violations, and consolidates findings into structured review reports with a verdict, score, and prioritized action items. Supports TypeScript, JavaScript, Python, Go, Swift, and Kotlin.
Core Capabilities
- PR risk analysis — scan git diffs for hardcoded secrets, SQL injection, debug statements, lint bypasses,
anytypes, and TODO/FIXME, with a 1-10 complexity score. - Code quality checking — detect long functions, large files, god classes, deep nesting, too many params, high cyclomatic complexity, missing error handling, unused imports, and magic numbers against fixed thresholds.
- SOLID & antipattern detection — flag structural, logic, security, performance, testing, and async antipatterns with fixes.
- Review reports — merge PR and quality findings into a verdict (approve / request changes / block), 0-100 score, and ranked action items in text, markdown, or JSON.
- Review order prioritization — sort files so security-sensitive code is inspected first.
- Commit hygiene — validate conventional-commit format across a branch.
When to Use
- Reviewing a PR and needing fast pre-screening before manual logic review.
- Analyzing code quality or auditing a codebase for smells and SOLID violations.
- Generating a structured review report or review checklist.
- Gating merges in CI/CD on a quality score or review verdict.
Clarify First
Before producing the review, confirm these inputs. If any is unknown or vague, ASK — do not assume:
- What to review — the git diff/branch (base and head) or a source directory (sets
--base/--heador the path the analyzers scan) - Language — TypeScript, JavaScript, Python, Go, Swift, or Kotlin (selects the rules
code_quality_checker.pyapplies via--language) - Output & gate — report format (text/markdown/JSON) and any pass/fail score threshold (sets the artifact format and CI verdict)
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
Tools
| Tool | Purpose | Command |
|---|---|---|
pr_analyzer.py | Assess PR complexity and risk from a git diff | python scripts/pr_analyzer.py . --base main --head feature-branch --json |
code_quality_checker.py | Detect code smells and SOLID violations in source | python scripts/code_quality_checker.py ./src --language typescript --json |
review_report_generator.py | Combine PR + quality findings into a review report | python scripts/review_report_generator.py . --format markdown --output review.md |
References
Load the reference that matches the task — keep this file lean and pull detail on demand:
- references/tool_reference.md — full per-tool usage, detection lists, threshold/verdict tables, all CLI flags, JSON output samples, supported-language extensions, troubleshooting table, and success criteria. Read when running, configuring, or debugging the scripts.
- references/code_review_checklist.md — systematic checklists for pre-review, correctness, security, performance, maintainability, testing, and language-specific checks. Read when performing a manual review pass.
- references/coding_standards.md — language-specific standards for TypeScript, JavaScript, Python, Go, Swift, and Kotlin (types, null safety, async, error handling, class design). Read when judging style and idiom compliance.
- references/common_antipatterns.md — antipattern catalog (structural, logic, security, performance, testing, async) with examples, detection cues, and fixes. Read when explaining or fixing a flagged smell.
Scope & Limitations
Covers:
- Static pattern-based risk detection in git diffs (secrets, SQL injection, debug statements, lint bypasses)
- Structural code quality analysis: function length, class size, cyclomatic complexity, parameter count, SOLID violations
- PR metadata assessment: file categorization by risk priority, commit message validation, complexity scoring
- Consolidated review reports with verdicts, scores, and prioritized action items across text, markdown, and JSON formats
Does NOT cover:
- Runtime or dynamic analysis -- use
senior-qafor test execution andqa-browser-automationfor end-to-end testing - Security vulnerability scanning (CVE databases, dependency audits) -- use
senior-securityorsenior-secopsfor SAST/DAST and supply chain analysis - Performance profiling or benchmarking -- use
senior-backendorsenior-fullstackfor performance optimization workflows - Architecture-level review (system design, service boundaries, API contract validation) -- use
senior-architectfor architectural decision records and design review
Integration Points
| Skill | Integration | Data Flow |
|---|---|---|
senior-security | Feed PR Analyzer critical findings into security review workflows for deeper SAST/DAST analysis | pr_analyzer.py --json output risks.critical[] → security assessment input |
senior-qa | Gate test execution on review report verdict; block test suites when verdict is block | review_report_generator.py --json output summary.verdict → QA pipeline gate |
senior-architect | Escalate high-complexity PRs (score 7+) to architecture review | pr_analyzer.py output summary.complexity_score → architecture review trigger |
senior-fullstack | Combine code quality scores with fullstack quality analyzer for end-to-end project health | code_quality_checker.py --json output → merged with code_quality_analyzer.py metrics |
tdd-guide | Cross-reference review findings with test coverage; flag untested code paths flagged by quality checker | Quality checker smells[] by file → TDD coverage gap analysis |
senior-devops | Integrate review reports into CI/CD pipelines as automated quality gates | review_report_generator.py --json output summary.score → pipeline pass/fail threshold |
FAQ
What does the code-reviewer skill do?
Code review automation for TypeScript, JavaScript, Python, Go, Swift, and Kotlin. Analyzes PRs for complexity, risk, SOLID violations, and code smells. Use when reviewing PRs, analyzing code quality, or generating review checklists.
How do I install code-reviewer?
Run npx skills add https://github.com/borghei/claude-skills --skill code-reviewer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/code-reviewer/ (personal) or .claude/skills/code-reviewer/ (project).
Which AI agents can use code-reviewer?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is code-reviewer safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains code-reviewer?
It is published by borghei in borghei/claude-skills. It has 187 recorded installs.
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