by spencermarx
AI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse.
# Add to your Claude Code skills
git clone https://github.com/spencermarx/open-code-reviewGuides for using ai agents skills like open-code-review.
Last scanned: 5/30/2026
{
"issues": [
{
"type": "npm-audit",
"message": "esbuild: esbuild enables any website to send any requests to the development server and read the response",
"severity": "medium"
}
],
"status": "PASSED",
"scannedAt": "2026-05-30T15:42:05.734Z",
"npmAuditRan": true,
"pipAuditRan": true
}open-code-review is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by spencermarx. AI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse. It has 290 GitHub stars.
Yes. open-code-review passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/spencermarx/open-code-review" and add it to your Claude Code skills directory (see the Installation section above).
open-code-review is primarily written in TypeScript. It is open-source under spencermarx on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh open-code-review against similar tools.
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Prerequisites: Node.js >= 22.5, Git, and an AI coding assistant.
# 1. Install the CLI globally
npm install -g @open-code-review/cli
# 2. Initialize OCR in your project
cd your-project
ocr init
# 3. Launch the dashboard and run your first review
ocr dashboard
Your browser will open the OCR dashboard — you're ready to run your first review.
Any package manager works. From v2.1 OCR uses Node's built-in SQLite (
node:sqlite) — there's no native module to compile, sonpm i -g,pnpm add -g, andyarn global addall install cleanly (including under pnpm 10+, which blocks dependency build scripts). It just needs Node >= 22.5.
ocr init detects your installed AI tools (Claude Code, Cursor, Windsurf, and 11 more) and configures each one automatically. Then open the dashboard to run a review, browse results, and manage your workflow from the browser.
Or run reviews directly from your AI coding assistant:
/ocr:review # Claude Code / Cursor
/ocr-review # Windsurf / other tools
/ocr-review Review against openspec/spec.md # With requirements
When you ask an AI to "review my code," you get a single perspective — one pass, one set of priorities. OCR changes that fundamentally:
CLAUDE.md, .cursorrules, OpenSpec configs, and other common patterns. Reviewers apply your conventions. ┌─────────────┐
│ Tech Lead │ ← Orchestrates the review
└──────┬──────┘
│
┌─────────────────┼─────────────────┐
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────┐ ┌─────────────────┐
│ Your Team │ │ Your Team │ │ Your Team │
│ Composition │ │ Composition│ │ Composition │
└─────────────────┘ └─────────────┘ └─────────────────┘
│ │ │
└─────────────────┼─────────────────┘
│
┌──────▼──────┐
│ Discourse │ ← Reviewers debate findings
└──────┬──────┘
│
┌──────▼──────┐
│ Synthesis │ ← Unified, prioritized feedback
└─────────────┘
Note: OCR does not replace human code review. The goal is to reduce the burden on human reviewers by catching issues earlier — so human review is faster and more focused on things machines can't catch.
The dashboard is the recommended way to run reviews, browse results, and manage your workflow. Launch it with ocr dashboard.
The Command Center lets you launch multi-agent code reviews and Code Review Maps directly from the dashboard. Specify targets, add requirements, toggle fresh starts — then watch live terminal output as agents work.
View verdict banners, individual reviewer cards, findings tables, and cross-reviewer discourse for every review round. Set triage status on findings (needs review, in progress, changes made, acknowledged, dismissed) with filtering and sorting.
Navigate large changesets with section-based breakdowns, rendered Mermaid dependency graphs, and file-level progress tracking.
Two posting modes from the review round page:
The Team page lets you browse all 28 reviewer personas grouped by tier (Generalists, Specialists, Famous Engineers, Custom). View full prompts, focus areas, and persona details. Create new reviewers or sync metadata — all from the dashboard.
Pick which personas show up on every review and how many instances of each — your default lineup, persisted to .ocr/config.yaml.
Different reviewers, different models. Pair a fast model on a generalist with a deeper model on a specialist, mix vendors across a single team, or set a workspace-wide default. The dashboard discovers your installed vendor (Claude Code or OpenCode) and lists every model it offers.
Need a heavier-hitting model for one risky changeset? The Command Center lets you swap personas and models per-review without touching your saved defaults.
After reviewing findings, address them directly. Copy a portable AI prompt into any coding tool, or — with Claude Code or OpenCode detected — run an agent directly from the dashboard to corroborate, validate, and implement changes.
AI-powered chat on every review round and map run page. Ask follow-up questions about specific findings, request clarification on reviewer reasoning, or explore alternative approaches.
The dashboard reads from the same .ocr/ directory and SQLite database used by the review workflow. No separate configuration is needed.
Run all OCR commands directly from your AI coding assistant using slash commands.
git add .
Then in your AI assistant:
/ocr-review # Windsurf / flat-prefix tools
/ocr:review # Claude Code / Cursor
/ocr-review Review against openspec/spec.md # With requirements context
In a separate te