open-code-review

Customizable multi-agent code review for AI-assisted development

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Quick Start

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, so npm i -g, pnpm add -g, and yarn global add all 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

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Why Open Code Review?

When you ask an AI to "review my code," you get a single perspective — one pass, one set of priorities. OCR changes that fundamentally:

• Multi-agent redundancy — Multiple reviewer instances examine your code independently. Different attention patterns catch different issues. What one reviewer misses, another finds.
• Discourse before synthesis — Reviewers don't just produce findings — they debate them. They challenge assumptions, validate concerns, and surface questions no single reviewer would ask.
• Fully customizable teams — Pick from 28 reviewer personas (including famous engineers like Martin Fowler, Kent Beck, and Sandi Metz), create your own persistent reviewers, or describe ephemeral one-off reviewers inline.
• Requirements-aware — Pass in a spec, proposal, or acceptance criteria. Every reviewer evaluates the code against your stated requirements, not just general best practices.
• Project context — OCR discovers your standards from 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.

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Table of Contents

• The Dashboard
• IDE & CLI Workflows
• Features
  • Multi-Agent Review
  • Multi-Model Teams
  • Code Review Maps
  • Requirements-Aware Review
  • Reviewer Discourse
  • GitHub PR Posting
  • Multi-Round Reviews
  • Custom Reviewers
  • Famous Engineer Personas
  • Ephemeral Reviewers
  • Real-Time Progress
  • Address Feedback
  • Session Notes & Chat
• Configuration
• Commands Reference
• Updating OCR
• Supported AI Tools
• Requirements
• Contributing

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The Dashboard

The dashboard is the recommended way to run reviews, browse results, and manage your workflow. Launch it with ocr dashboard.

Run reviews and maps

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.

Browse and triage reviews

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.

Explore Code Review Maps

Navigate large changesets with section-based breakdowns, rendered Mermaid dependency graphs, and file-level progress tracking.

Post to GitHub

Two posting modes from the review round page:

• Post Team Review — Posts the multi-reviewer synthesis as-is
• Generate Human Review — AI-rewrites all findings into a single, natural human voice following Google's code review guidelines. Preview, edit, and save drafts before posting.

Manage your review team

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.

Set your default team composition

Pick which personas show up on every review and how many instances of each — your default lineup, persisted to .ocr/config.yaml.

Assign models per reviewer

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.

Override the team for a single review

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.

Address Feedback

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.

Ask the Team

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 chat is read-only: the AI can only read and search files in your repository. It requires Claude Code 2.1.295 or later, or OpenCode 1.3.4 or later (1.x).

The dashboard reads from the same .ocr/ directory and SQLite database used by the review workflow. No separate configuration is needed.

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IDE & CLI Workflows

Run all OCR commands directly from your AI coding assistant using slash commands.

Start a review

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

Watch progress in real-time

In a separate terminal:

ocr progress

  Open Code Review

  2026-01-26-main  ·  Round 2  ·  1m 23s

  ━━━━━━━━━━━━━━━━────────  60%  ·  Parallel Reviews

  ✓ Context Discovery
  ✓ Change Context
  ✓ Tech Lead Analysis
  ▸ Parallel Reviews
    Round 2
    ✓ Principal #1 2  │  ✓ Principal #2 1  │  ○ Quality #1 0  │  ○ Quality #2 0
    Round 1 ✓ 4 reviewers
  · Aggregate Findings
  · Reviewer Discourse
  · Final Synthesis

  Ctrl+C to exit

More AI assistant commands

/ocr-map                   # Generate a Code Review Map for large changesets
/ocr-post                  # Post review to GitHub PR
/ocr-doctor                # Verify installation
/ocr-reviewers             # List available reviewer personas
/ocr-history               # List past review sessions
/ocr-show [session]        # Display a specific past review

For Claude Code / Cursor, use /ocr:review, /ocr:map, /ocr:post, etc.

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Features

Multi-Agent Review

OCR follows an 8-phase workflow orchestrated by a Tech Lead agent:

Phase	What happens
1. Context Discovery	Load config, discover project standards, read OpenSpec context
2. Change Analysis	Analyze git diff, understand what changed and why
3. Tech Lead Assessment	Summarize changes, identify risks, select reviewer team
4. Parallel Reviews	Each reviewer examines code independently based on your team config
5. Aggregation	Merge findings from redundant reviewers
6. Discourse	Reviewers challenge, validate, and connect findings
7. Synthesis	Produce prioritized, deduplicated final review
8. Presentation	Display results; optionally post to GitHub

Multi-Model Teams