@codemoot/core

Multi-model AI orchestration engine — debate, review, policy, caching, and job queue


Keywords
ai, llm, orchestration, multi-model, code-review, mcp, debate, policy, codex
License
MIT
Install
npm install @codemoot/core@0.2.14

Documentation

CodeMoot

CI License: MIT

A second opinion for AI-generated code. Claude Code + Codex CLI collaboration platform that brings debate, review, autofix, and consensus patterns to your development workflow.

CodeMoot bridges Claude and GPT so they work as partners — one plans, the other reviews, and together they build better code than either could alone.

Quick Start

# Install globally
npm install -g @codemoot/cli

# One-command setup: verifies codex, creates config, runs first review
codemoot start

# Or step by step:
codemoot doctor           # check prerequisites
codemoot init             # create .cowork.yml
codemoot review src/      # review code with GPT
codemoot fix src/         # autofix loop: review → fix → re-review

# Debate architecture with GPT
codemoot debate start "Should we use REST or GraphQL?"

# Ship with confidence
codemoot shipit --profile safe

Prerequisites

  • Node.js >= 20
  • Codex CLI installed (npm install -g @openai/codex)
  • ChatGPT subscription (Codex CLI uses your existing subscription — $0 API cost)

Commands

Getting Started

Command Description
codemoot start First-run concierge: verify codex, init config, run quick review
codemoot doctor Preflight diagnostics: check codex, config, database, git, node
codemoot init Initialize CodeMoot in current project

Core Workflows

Command Description
codemoot review <file> Code review via GPT with structured findings
codemoot review --prompt "..." Freeform review — GPT explores codebase via tools
codemoot review --diff HEAD~3..HEAD Review git changes
codemoot review --preset security-audit Use named preset (5 built-in)
codemoot fix <file> Autofix loop: review → apply fixes → re-review
codemoot cleanup [path] Scan for unused deps, dead code, duplicates, hardcoded values
codemoot plan <task> Generate plan via architect + reviewer loop
codemoot run <task> Full plan-review-implement cycle

Multi-Model Debate

Command Description
codemoot debate start <topic> Start a Claude vs GPT debate (--timeout sets default)
codemoot debate turn <id> <prompt> Send next prompt (--output, --force, --quiet, --response-cap)
codemoot debate next <id> Auto-continue debate (--quiet for programmatic use)
codemoot debate status <id> Show debate progress
codemoot debate list List all debates
codemoot debate history <id> Full message history (--output <file> for untruncated export)
codemoot debate complete <id> Mark debate as done

Automation

Command Description
codemoot shipit [--profile fast|safe|full] Composite workflow: lint → test → review → cleanup → commit
codemoot watch Watch files, auto-enqueue reviews on save
codemoot build start <task> Automated build loop with GPT review

Background Jobs

Command Description
codemoot review --background Enqueue review, return immediately
codemoot jobs list List background jobs
codemoot jobs status <id> Job details with logs
codemoot jobs logs <id> Full job log output
codemoot jobs cancel <id> Cancel a job
codemoot jobs retry <id> Retry a failed job

Session Management

Command Description
codemoot session start Start new persistent GPT session
codemoot session current Show active session with token usage
codemoot session list List all sessions
codemoot session close <id> Close a session

Observability

Command Description
codemoot cost Token usage dashboard (by command, by day)
codemoot events --follow Stream events as JSONL (for editors/CI)

Review Presets

Preset Focus Timeout Use Case
security-audit Injection, auth, secrets 1200s Pre-deploy security scan
performance N+1, memory, blocking 900s Performance optimization
quick-scan Top bugs only 240s Quick sanity check
pre-commit Changed code blockers 180s Git pre-commit hook
api-review Contracts, versioning 900s API design review

Shipit Profiles

Profile Steps Use Case
fast review Quick check before push
safe lint → test → review → cleanup Default — catches most issues
full lint → test → review → cleanup → commit Full pipeline with auto-commit

Policy Engine

CodeMoot includes a built-in policy engine that gates actions:

  • Block on CRITICAL: Any critical finding blocks the commit
  • Warn on NEEDS_REVISION: Review verdict triggers a warning
  • Custom rules via predicate-based engine (enforce/warn modes)

Architecture

TypeScript monorepo with 3 packages:

Package Description Status
@codemoot/core Orchestration engine, memory, policy, caching Stable
@codemoot/cli Command-line interface (15 commands) Stable
@codemoot/mcp-server MCP server (5 tools for IDE integration) Experimental

How It Works

  1. Claude Code is your primary AI — it plans, writes code, manages your project
  2. Codex CLI (GPT) acts as reviewer/critic — it reads your codebase, finds bugs, suggests fixes
  3. CodeMoot bridges them — structured prompts, session persistence, token tracking, policy gates

All GPT calls happen via Codex CLI using your ChatGPT subscription — $0 API cost.

Configuration

.cowork.yml in your project root:

models:
  codex-architect:
    provider: openai
    model: gpt-5.3-codex
    providerMode: cli
  codex-reviewer:
    provider: openai
    model: gpt-5.3-codex
    providerMode: cli

roles:
  architect:
    model: codex-architect
  reviewer:
    model: codex-reviewer

workflow: plan-review-implement
mode: autonomous

.codemootignore

Exclude files from review/cleanup/watch (gitignore syntax):

node_modules
dist
*.db
.env

MCP Server (Experimental)

Add to your .mcp.json:

{
  "mcpServers": {
    "codemoot": {
      "command": "npx",
      "args": ["@codemoot/mcp-server"],
      "env": {
        "CODEMOOT_PROJECT_DIR": "/path/to/your/project"
      }
    }
  }
}

Tools: codemoot_review, codemoot_plan, codemoot_debate, codemoot_memory, codemoot_cost

Development

git clone https://github.com/katarmal-ram/codemoot.git
cd codemoot
pnpm install
pnpm build
pnpm test         # 624 tests across 47 files
pnpm lint         # Biome linter
pnpm typecheck    # TypeScript strict checks

Known Limitations

  • Background job worker must be started manually (auto-spawn coming)
  • Watch mode enqueues jobs but requires worker process
  • MCP server is experimental — core + CLI are stable
  • Autofix loop depends on GPT's ability to apply edits via Codex tools
  • Windows path normalization may have edge cases

License

MIT