parallel-code-review

A code-review workflow that uses several specialized review agents in parallel.

In plain words
What is it for?
It is for comprehensive reviews before merging, especially for large changes or work that needs multiple technical perspectives.
Why use it?
It provides separate perspectives on areas such as security, architecture, and performance while reducing the time needed for a broad review.

Skill for Claude CodeCodex

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/dgalarza/claude-code-workflows/parallel-code-review
Any agent
npx skills add dgalarza/claude-code-workflows --skill parallel-code-review
Clone the repo
git clone --depth 1 https://github.com/dgalarza/claude-code-workflows

Made for: Claude Code, Codex.

Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,617 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.

ModelPer sessionOnce invoked
Fable 5 $0.00062 $0.01617
Opus 5 $0.00031 $0.00809
Sonnet 5 $0.00012 $0.00323
Haiku 4.5 $0.00006 $0.00162

Measured 2d ago against content hash 868de3eecc86, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

parallel-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.

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.

plugins/parallel-code-review/skills/parallel-code-review/SKILL.md · 283 lines

How it starts

The opening of the file, as written. The whole thing — 283 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Parallel Code Review

This skill provides guidance for launching multiple specialized code review agents in parallel for comprehensive, efficient analysis from different perspectives.

Purpose

Parallel code reviews maximize efficiency and coverage by running multiple specialized reviewers simultaneously. Instead of sequential reviews that take time proportional to the number of reviewers, parallel execution completes in the time of the slowest reviewer while providing comprehensive feedback from all perspectives.

When to Use This Skill

Use this skill when:

  • Performing comprehensive code review before merging
  • Need multiple specialized perspectives (security, architecture, performance)
  • Want faster review by parallelizing analysis
  • Reviewing large changesets that benefit from division of labor
  • Implementing continuous review practices

Benefits of Parallel Reviews

Speed: 2+ specialized reviews complete in the time of 1 Depth: Each agent focuses on specific expertise area Comprehensive Coverage: Security + Architecture + Performance simultaneously

Core Workflow

Phase 1: Prepare for Review

1. Check Decision Log (Prevent Redundancy)

# Search memory for previous code review decisions
mcp__memory__search_nodes query:"code_review_decision"

# Read decision log file
cat code_review_decisions.md

Decision log format:

# Code Review Decisions

## 2025-01-15: Result Pattern Required

**Decision**: All service objects must return Result objects
**Rationale**: Explicit success/failure handling improves error management
**Status**: Accepted standard pattern

2. Get Code Changes

# Get diff for review
git diff main...HEAD

# Or specific branch
git diff main...feature-branch

Phase 2: Launch Parallel Reviewers

Use Task tool to launch multiple agents concurrently:

Example: Launch 2 reviewers in parallel by sending a SINGLE message with MULTIPLE Task tool calls:

Task({
  subagent_type: "cybersecurity-expert",
  description: "Security review of changes",
  prompt: "Review git diff for security vulnerabilities..."
})

Task({
  subagent_type: "rails-backend-expert",
  description: "Architecture review of changes",
  prompt: "Review git diff for code quality..."
})

Read the full file on GitHub · 283 lines

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.

  1. 2d ago First seen · 283 lines · 62 tokens per session scan A 868de3eecc86

Subscribe to this mod's changes

parallel-code-review is a skill published in the GitHub repository dgalarza/claude-code-workflows (59 stars, last pushed 5d ago), licensed MIT. It adds 62 tokens to every session and 1,617 once invoked, about $0.0003 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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