Code Council

One AI can miss things. A council of AIs catches more.

Unanimous

When all models agree, you can be confident it's a real issue. Fix it.

Majority

Most models flagged this. Probably worth investigating.

Disagreement

Models conflict. You know exactly where to focus your judgment.

How It Works

Your code goes through multiple models simultaneously

Multi-Model Consensus Different models, different strengths, unified insights Minimax M2.1 GLM 4.7 Kimi K2.5 DeepSeek V3.2 UNANIMOUS 4/4 models SQL Injection in users.ts:42 High confidence - fix this MAJORITY 3/4 models Missing input validation Likely valid - investigate ? DISAGREEMENT split Token expiration policy Your judgment needed
1

Submit code

Paste or review git

2

4 models analyze

Running in parallel

3

Cluster findings

Group by location

4

Score consensus

Unanimous/majority/split

Available Tools

Each tool runs your input through multiple AI models in parallel

review_code review_frontend review_backend review_plan Consensus Engine 4 models in parallel Unanimous Majority Disagreement
review_code
General code review for bugs, security, performance, and quality issues across any language.
Use review_code to check this function: [paste code]
code* language context output_format
review_frontend
Accessibility, performance, and UX review for React, Vue, Svelte, and other frameworks.
Use review_frontend with review_type=accessibility
code* framework review_type
review_backend
Security-focused review for APIs and servers. Catches auth issues, injection vulnerabilities.
Use review_backend with review_type=security
code* language review_type
review_plan
Review implementation plans BEFORE coding. Catch design issues when they're cheap to fix.
Use review_plan to analyze this plan: [paste]
plan* review_type context
review_git_changes
Review git changes directly. Works with staged, unstaged, branch diffs, or specific commits.
Use review_git_changes with review_type=staged
review_type commit_hash context
discuss_with_council
Multi-turn conversations. Each model maintains its own context for diverse perspectives.
Use discuss_with_council to ask: [question]
message* session_id discussion_type
tps_audit
Toyota Production System analysis. Flow, waste, bottlenecks. Generates HTML reports.
Use tps_audit to analyze this repository
path focus_areas max_files output_format

Configuration

Config files, environment variables, and customization

Generate Config File
# TypeScript config (recommended)
npx @klitchevo/code-council init

# JavaScript in project root
npx @klitchevo/code-council init --js --root

Creates .code-council/config.ts with full type support.

Example Config
import { defineConfig } from "@klitchevo/code-council/config";

export default defineConfig({
  models: {
    codeReview: ["anthropic/claude-sonnet-4"],
    backendReview: ["openai/gpt-4o"],
  },
  llm: {
    temperature: 0.3,
    maxTokens: 16384,
  },
});

Environment Variables

VariableDescription
OPENROUTER_API_KEYRequired. Your OpenRouter API key
CODE_REVIEW_MODELSModels for general reviews (JSON array)
FRONTEND_REVIEW_MODELSModels for frontend reviews
BACKEND_REVIEW_MODELSModels for backend reviews
TEMPERATUREResponse randomness (0.0-2.0, default: 0.3)
MAX_TOKENSMax response tokens (default: 16384)

Model Selection

Choose models based on your needs and budget

Why These Defaults?

We picked 4 models that are cheap, fast, and different enough from each other to catch different things. All available through OpenRouter at a fraction of the cost of frontier models. You can swap in Claude or GPT-4 anytime.

Minimax M2.1

Chinese lab model with strong code understanding. Fast inference and very cheap. Good at spotting logical errors and edge cases in business logic.

minimax/minimax-m2.1

GLM 4.7

Zhipu AI's latest model. Trained on diverse multilingual data, which means it sometimes catches patterns Western-trained models miss. Solid at documentation and naming issues.

z-ai/glm-4.7

Kimi K2.5

Moonshot AI's flagship. Known for strong reasoning and 128k context window. Handles large files well and tends to be thorough - sometimes catches security issues others miss.

moonshotai/kimi-k2.5

DeepSeek V3.2

One of the best open-weight models available. Competitive with GPT-4 on coding benchmarks at a fraction of the price. Strong at architecture and design pattern analysis.

deepseek/deepseek-v3.2

Pricing Tiers

Budget (Default)

~$0.01-0.05 per review
["minimax/minimax-m2.1", "deepseek/deepseek-v3.2"]

Balanced

~$0.10-0.30 per review
["anthropic/claude-sonnet-4", "openai/gpt-4o"]

Premium

~$0.50-1.00 per review
["anthropic/claude-opus-4.5", "openai/gpt-4o"]

Quick Start

Add to your Claude Desktop config and start reviewing

UNDERSTANDING YOUR RESULTS Unanimous All models agree Majority Most models agree ? Disagreement Models conflict 1 Single One model only
{
  "mcpServers": {
    "code-council": {
      "command": "npx",
      "args": ["-y", "@klitchevo/code-council"],
      "env": {
        "OPENROUTER_API_KEY": "your-api-key"
      }
    }
  }
}

Get your API key at openrouter.ai/keys