A broad code-review process that uses several specialized perspectives to examine security, performance, style, tests, documentation, pull-request feedback, and architecture.

Use it for pull-request reviews, security audits, performance checks, test-coverage assessment, architecture reviews, and analysis of reviewer comments.

It helps organize large or complex reviews and turns scattered findings into prioritized, actionable fixes with references to the relevant code.

code-review — Skill by viktorbezdek

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add skills/viktorbezdek/skillstack/code-review

Any agent

npx skills add viktorbezdek/skillstack --skill code-review

Clone the repo

git clone --depth 1 https://github.com/viktorbezdek/skillstack

Made for: Claude Code, Codex.

Per session 142 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,304 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00142	$0.01304
Opus 5	$0.00071	$0.00652
Sonnet 5	$0.00028	$0.00261
Haiku 4.5	$0.00014	$0.00130

Measured 2d ago against content hash e10f8a252d07, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 24 executable files (examples/ai-powered-testing.py, examples/console_logging.py, examples/element_discovery.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

code-review/skills/code-review/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Comprehensive Code Review Skill

This skill is a curated merge of four complementary code review skills:

Evidence-Based Code Review: Evidence-based multi-agent swarm review with specialized reviewers
PR Comment Analysis: Extract, consolidate, and prioritize GitHub PR comments
Development Workflow Specialist: TDD, debugging, performance optimization, and automated code review
Consultant: AI-powered deep analysis for complex architectural and security reviews

When to Use

Use this skill when:

Reviewing PRs systematically with multiple quality dimensions
Extracting and consolidating feedback from multiple reviewers
Need evidence-based findings with file:line references
Assessing security vulnerabilities, performance bottlenecks, or code quality
Creating action plans from PR comments
Complex architectural decisions requiring deep analysis
Audit requirements mandate systematic review (compliance, release gates)

Do NOT use for:

Simple formatting fixes (use linter/prettier directly)
Non-code files (documentation, configuration without logic)
Trivial changes (typo fixes, comment updates)
Generated code (build artifacts, vendor dependencies)

Core Capabilities

1. Evidence-Based Code Review

Every finding MUST include:

Code location: [file:line] with surrounding context (5 lines before/after)
Evidence type: DIRECT, STYLE_RULE, or BEST_PRACTICE
Severity: CRITICAL, MAJOR, MINOR, or NIT
Confidence score: 0.0-1.0
Suggested fix with specific code changes

2. PR Comment Analysis

Fetches ALL comments from GitHub PR (inline + conversation)
Groups comments by file path and code section
Identifies "High Consensus Issues" (2+ reviewers same concern)
Three-phase analysis: Consolidation, Context Validation, Impact Analysis

3. Multi-Agent Swarm Review

Five specialized review agents working in parallel:

Security Reviewer: Vulnerabilities, unsafe patterns, secrets
Performance Analyst: Bottlenecks, optimization opportunities
Style Reviewer: Code style, best practices, maintainability
Test Specialist: Test coverage, quality, edge cases
Documentation Reviewer: Comments, API docs, README updates

Read the full file on GitHub · 140 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2d ago First seen · 140 lines · 142 tokens per session scan A e10f8a252d07

Subscribe to this mod's changes

code-review is a skill published in the GitHub repository viktorbezdek/skillstack (11 stars, last pushed 2mo ago), licensed MIT. It adds 142 tokens to every session and 1,304 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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