CLAUDE CODE PLUGIN v2.4

Cross-Model Code Review
& Parallel Delegation

Route code reviews across multiple AI models simultaneously. Delegate tasks in parallel. Catch what one model misses. Ship with confidence.

3.2×
Bug Coverage vs. Single Model
47%
Faster Review Cycles
12
Supported Models
89k
Reviews Completed

From Commit to Consensus

Every code change passes through an orchestrated pipeline. Models review in parallel, findings are merged, and a unified report surfaces actionable insights.

01
Commit Hook
Git push triggers the Codex pipeline. Diffs are parsed and chunked by file scope.
02
Model Routing
Chunks are dispatched to selected models based on specialization rules.
03
Parallel Review
Each model reviews independently. Security, logic, and style checks run concurrently.
04
Finding Merge
Duplicate findings are deduplicated. Conflicts are flagged for human triage.
05
Consensus Report
A unified report with severity scores and suggested fixes is delivered inline.

Live Review Board

Track every review item from queue to completion. Each card shows model attribution, severity, and time elapsed.

Queued4
auth/session.ts
Token refresh logic — awaiting model assignment
Medium
api/routes.ts
New endpoint validation rules
Low
db/migrations/024.sql
Schema change — index impact analysis
Medium
utils/cache.ts
TTL strategy update
Low
In Review3
payments/stripe.ts
Webhook signature verification — Opus + Sonnet
CriticalOpusSonnet
core/scheduler.ts
Race condition in job queue — GPT-4o reviewing
HighGPT-4o
ui/dashboard.tsx
Component render optimization
MediumSonnet
Conflicts2
lib/crypto.ts
Opus flags deprecated algo; Sonnet approves — needs triage
HighOpusSonnet
services/email.ts
GPT-4o and Opus disagree on error handling pattern
MediumGPT-4oOpus
Resolved6
middleware/cors.ts
Origin whitelist — all models agreed
Consensus
tests/auth.spec.ts
Test coverage gaps identified and patched
Consensus
config/env.ts
Env var validation — auto-resolved
Auto-resolved

Parallel Task Assignment

Assign tasks to models based on their strengths. Monitor progress in real-time. Each model handles what it does best.

Op

Claude Opus

Deep Analysis & Architecture
Security audit — payments module
2m 14s
Architecture review — event system
3m 41s
Data flow analysis — user pipeline
1m 08s
Dependency vulnerability scan
Pending
So

Claude Sonnet

Fast Iteration & Code Style
Lint rule compliance — 23 files
0m 34s
Type safety check — API layer
0m 52s
Unit test generation — utils/
1m 17s
Documentation sync — README
0m 28s
4o

GPT-4o

Logic Verification & Edge Cases
Edge case analysis — scheduler
1m 45s
Concurrency review — worker pool
2m 03s
Input validation — form handlers
Pending
Error boundary review — React tree
Pending

Real Review Output

Actual findings from a cross-model review session. Each finding includes the model that caught it, severity, and a suggested fix.

SQL Injection via Unsanitized Input
Critical Opus payments/stripe.ts:142
141 // Build query from user input 142 const q = `SELECT * FROM orders WHERE id = '${req.params.id}'`; 142 const q = db.query('SELECT * FROM orders WHERE id = $1', [req.params.id]); 143 const result = await db.execute(q);
String interpolation in SQL queries allows injection attacks. Use parameterized queries. Opus flagged this; Sonnet missed it due to context window position.
Race Condition in Job Scheduler
High GPT-4o core/scheduler.ts:87
85 async processQueue() { 86 const job = this.queue.shift(); 86 const job = await this.queue.dequeueAtomic(); 87 if (job) await this.execute(job);
Array.shift() is not atomic. Under concurrent workers, two processes can grab the same job. GPT-4o identified this through its edge-case analysis pass.
Unnecessary Re-renders in Dashboard
Medium Sonnet ui/dashboard.tsx:34
33 const Dashboard = ({ data }) => { 34 const processed = data.map(d => transform(d)); 34 const processed = useMemo(() => data.map(d => transform(d)), [data]); 35 return <Grid items={processed} />;
Expensive transformation runs on every render. Wrapping in useMemo prevents recalculation when data hasn't changed. Sonnet caught this in its performance pass.

Know Each Model's Edge

Different models excel at different review dimensions. Codex routes tasks to maximize coverage based on empirical benchmarks.

Claude Opus
Deep reasoning & security
Security96%
Architecture94%
Speed62%
Code Style78%
Deep AnalysisVulnerabilities
Claude Sonnet
Speed & code quality
Security79%
Architecture72%
Speed95%
Code Style91%
Fast PassesLint & Style
GPT-4o
Logic & edge cases
Security82%
Architecture80%
Speed88%
Code Style74%
Edge CasesLogic Bugs

How Teams Ship with Codex

A real-world workflow from a team using Codex on a production Node.js application. Total review cycle: 4 minutes 12 seconds.

Developer Pushes to Feature Branch
T+0s
Sarah pushes 14 changed files across 3 modules. The Codex git hook activates and begins diff parsing.
Codex Routes to 3 Models
T+4s
Payment files → Opus (security focus). UI components → Sonnet (style + perf). Scheduler logic → GPT-4o (edge cases). All three start simultaneously.
Models Complete Review
T+2m 38s
Sonnet finishes first (34s). GPT-4o second (1m 45s). Opus last (2m 14s). Finding merge begins as each model completes.
Conflict Detected — Human Triage
T+2m 42s
Opus and Sonnet disagree on crypto.ts. Codex flags the conflict and presents both arguments. Sarah sides with Opus — the algorithm is indeed deprecated.
Unified Report Delivered
T+4m 12s
8 findings total: 1 critical, 2 high, 3 medium, 2 low. Inline suggestions applied. PR is updated with review comments and a summary card.