### Minimal Setup for New Developers

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

A sequence of commands to clone the repository, install dependencies, set up the local environment, and verify the installation.

```bash
git clone <repository>
cd ai-code-review
corepack enable
pnpm install
cp .env.example .env.local
# Add at least one AI provider API key
pnpm test
```

--------------------------------

### Command Line Usage Examples

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Examples demonstrating how to run the AI Code Review tool from the command line, including global and local installations.

```bash
# Global installation
ai-code-review [target] [options]
```

```bash
# Local installation with pnpm
pnpm exec ai-code-review [target] [options]
```

```bash
# Local installation with npm
npx ai-code-review [target] [options]
```

--------------------------------

### Team Setup Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/MCP_WORKFLOW_GUIDE.md

Example bash commands and file structure for setting up the AI Code Review tool for team usage, emphasizing API key security.

```bash
# .ai-code-review/.gitkeep (commit this)
# .ai-code-review/config.json (in .gitignore)

# Team README instructions:
# 1. Run: ai-code-review init
# 2. Enter your personal OpenRouter API key
# 3. Config is stored locally and not committed
```

--------------------------------

### Setup Environment Script Execution

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Execute the setup script based on your installation method (pnpm, npm, or Homebrew) to configure API keys and the .env.local file.

```bash
pnpm exec @bobmatnyc/ai-code-review/scripts/setup-env.js
```

```bash
npx @bobmatnyc/ai-code-review/scripts/setup-env.js
```

```bash
node /opt/homebrew/lib/node_modules/@bobmatnyc/ai-code-review/scripts/setup-env.js
```

--------------------------------

### Verify Git Setup and Configuration

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/AI_DETECTION_TROUBLESHOOTING.md

Ensure Git is installed and check its configuration settings. Initialize a repository and configure user details if necessary.

```bash
# Verify git is working
git --version
git status

# Check git configuration
git config --list

# Initialize repository if needed
git init

# Configure git if not set
git config user.name "Your Name"
git config user.email "your.email@example.com"

# Add initial commit if repository is empty
git add .
git commit -m "Initial commit" --allow-empty
```

--------------------------------

### Minimal Configuration File Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/AI_DETECTION_TROUBLESHOOTING.md

A minimal example of a configuration file for AI Code Review. This can be used to test basic functionality or as a starting point.

```yaml
# minimal-config.yaml
reviewType: coding-test
enableAiDetection: true
aiDetectionThreshold: 0.7
```

--------------------------------

### Quick Fix for Global Installation Environment Errors

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Download and run a script to fix environment errors for globally installed tools, ensuring proper setup of API keys.

```bash
# Download and run the fix script
curl -O https://raw.githubusercontent.com/bobmatnyc/ai-code-review/develop/scripts/global-env-fix.js
node global-env-fix.js
```

```bash
# You may need to run with sudo if permission errors occur
sudo node global-env-fix.js
```

--------------------------------

### Install AI Code Review Locally

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/QUICK_START.md

Install the tool as a development dependency in your project.

```bash
pnpm add -D @bobmatnyc/ai-code-review
```

```bash
npm install --save-dev @bobmatnyc/ai-code-review
```

--------------------------------

### Install Dependencies and Build Project

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/tests/extract-patterns/README.md

Install project dependencies using pnpm and then build the project. These steps are necessary before running tests.

```bash
pnpm install
pnpm build
```

--------------------------------

### Global Installation Commands

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Instructions for installing the AI Code Review tool globally using pnpm or npm.

```bash
# Using pnpm (recommended)
pnpm add -g @bobmatnyc/ai-code-review
```

```bash
# Using npm (alternative)
npm install -g @bobmatnyc/ai-code-review
```

--------------------------------

### Example Consolidated Review Filenames

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Illustrative examples of consolidated review output filenames.

```bash
ai-code-review-docs/openai-gpt-4o-quick-fixes-review-src-2024-04-06.md
ai-code-review-docs/gemini-1.5-pro-architectural-review-src-utils-2024-04-06.md
```

--------------------------------

### Local Git Workflow Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/INSTRUCTIONS.md

A typical local Git workflow demonstrating how to start from main, create a new branch, make changes, commit, keep the branch updated, and prepare for pushing.

```bash
# Start from main
git checkout main
git pull origin main

# Create a new branch
git checkout -b feature/new-dashboard

# Make your changes
git add .
git commit -m "feat(dashboard): initial layout and state setup"

# Keep up to date
git fetch origin
git rebase origin/main

# Push and open PR
git push -u origin feature/new-dashboard
```

--------------------------------

### Install AI Code Review Globally

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/QUICK_START.md

Install the tool globally for command-line access. Recommended for ease of use.

```bash
pnpm add -g @bobmatnyc/ai-code-review
```

```bash
npm install -g @bobmatnyc/ai-code-review
```

--------------------------------

### Set Up Local Environment

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

Create a local environment file from the example and add necessary API keys for integration tests.

```bash
cp .env.example .env.local
# Add actual API keys to .env.local
```

--------------------------------

### GitHub Actions CI Workflow Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

Example GitHub Actions workflow for a CI pipeline that checks out code, sets up Node.js, installs dependencies, and runs linting, type checking, and tests.

```yaml
name: CI
on: [push, pull_request]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
        with:
          node-version: 18
      - run: corepack enable
      - run: pnpm install
      - run: pnpm run lint
      - run: pnpm run build:types  
      - run: pnpm test
```

--------------------------------

### Custom Prompt Template Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Example of a custom prompt template with YAML metadata and placeholders for code and instructions.

```markdown
---
name: Custom Security Review
description: A custom prompt template for security-focused code reviews
version: 1.0.0
author: Your Name
reviewType: security
language: typescript
tags: security, custom
---

# Security Code Review

Please review the following code for security vulnerabilities:

{{LANGUAGE_INSTRUCTIONS}}

## Output Format

Please provide your findings in the following format:

1. **Vulnerability**: Description of the vulnerability
2. **Severity**: High/Medium/Low
3. **Location**: File and line number
4. **Recommendation**: How to fix the issue

{{SCHEMA_INSTRUCTIONS}}
```

--------------------------------

### Claude Desktop MCP Configuration Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/DOCUMENTATION_INDEX.md

Example configuration for Claude Desktop using MCP. This JSON file defines settings for the application.

```json
{
  "model": "claude-3-opus-20240229",
  "temperature": 0.7,
  "max_tokens": 2048,
  "system": "You are a helpful AI assistant."
}
```

--------------------------------

### Clone Repository and Install Dependencies

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WORKFLOW.md

Steps to clone the AI Code Review repository, install dependencies using pnpm, and set up local environment variables.

```bash
git clone https://github.com/bobmatnyc/ai-code-review.git
cd ai-code-review
pnpm install
cp .env.example .env.local
# Edit .env.local with your API keys
pnpm test
pnpm run build
```

--------------------------------

### Local Installation Commands

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Instructions for installing the AI Code Review tool as a development dependency locally using pnpm or npm.

```bash
# Using pnpm (recommended)
pnpm add -D @bobmatnyc/ai-code-review
```

```bash
# Using npm (alternative)
npm install --save-dev @bobmatnyc/ai-code-review
```

--------------------------------

### Parallel Task Execution Examples

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/chapters/design/claude-code-best-practices.md

Examples demonstrating parallel task execution for codebase exploration, independent analysis, and testing.

```bash
# Codebase exploration example
"Explore the codebase using 4 tasks in parallel. Each agent should explore different directories."

# Independent analysis tasks
"Analyze these 3 components in parallel: authentication, database layer, and API endpoints."

# Testing in parallel
"Run unit tests, integration tests, and linting in parallel using separate tasks."
```

--------------------------------

### Install ESLint and TypeScript plugins

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/chapters/design/unused-code-cleanup-strategy.md

Install ESLint, the TypeScript parser, and the ESLint plugin for TypeScript as development dependencies.

```bash
npm install --save-dev eslint @typescript-eslint/parser @typescript-eslint/eslint-plugin
```

--------------------------------

### Example Scenario: Continuous Builds

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/BUILD_NUMBER_TRACKING.md

Demonstrates the sequential incrementing of build numbers during continuous development on the same version.

```text
Build 1: 4.4.2 (build 0)
Build 2: 4.4.2 (build 1)
Build 3: 4.4.2 (build 2)
```

--------------------------------

### Install pnpm using npm

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WORKFLOW.md

An alternative method to install pnpm globally using npm.

```bash
npm install -g pnpm
```

--------------------------------

### Development Execution

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

Start the development server for continuous development and execution.

```bash
pnpm run dev
```

--------------------------------

### Install MCP Server

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/MCP_WORKFLOW_GUIDE.md

Installs the AI Code Review as a project-level MCP service and configures it with Claude Desktop.

```APIDOC
## `ai-code-review install`

### Description
Install AI Code Review as a project-level MCP service.

### Purpose
Register the MCP server with Claude Desktop and create project-level MCP configuration.

### What It Does
1. Detects project toolchain
2. Creates `.mcp.json` in project root
3. Updates Claude Desktop config (`~/Library/Application Support/Claude/claude_desktop_config.json` on macOS)
4. Registers MCP server with environment variables from project config

### Output
- `.mcp.json` - Project-level MCP configuration
- Claude Desktop config updated with server registration

### Example
```bash
ai-code-review install
```

### Claude Desktop Config Entry
```json
{
  "mcpServers": {
    "ai-code-review-myproject": {
      "command": "/opt/homebrew/bin/npx",
      "args": ["@bobmatnyc/ai-code-review", "mcp"],
      "env": {
        "PROJECT_PATH": "/Users/username/projects/myproject",
        "OPENROUTER_API_KEY": "sk-or-v1-..."
      }
    }
  }
}
```
```

--------------------------------

### Local Installation with pnpm

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Installs the AI Code Review tool as a development dependency in the current project using pnpm.

```bash
pnpm add -D @bobmatnyc/ai-code-review
```

--------------------------------

### Run Interactive Code Review

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/QUICK_START.md

Start the tool in interactive mode, which is recommended for beginners to understand the review output.

```bash
ai-code-review --interactive .
```

--------------------------------

### Start MCP Server

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/CLAUDE.md

Start the MCP server for AI code review. Options for debug logging and custom configuration are available.

```bash
# Start MCP server
ai-code-review mcp

# With debug logging
ai-code-review mcp --debug

# Custom configuration
ai-code-review mcp --name "my-code-review" --max-requests 10
```

--------------------------------

### Verify Local Installation with npm

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Verifies the local installation of the AI Code Review tool using npm by executing the version command.

```bash
npx ai-code-review --version
```

--------------------------------

### Global Installation with npm

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Installs the AI Code Review tool globally using npm. This makes the 'ai-code-review' command available system-wide.

```bash
npm install -g @bobmatnyc/ai-code-review
```

--------------------------------

### Web Application Integration Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/DOCUMENTATION_INDEX.md

Example code demonstrating library usage within Next.js and other web applications. Ensure necessary imports and configurations are in place before use.

```typescript
import { Claude } from "@anthropic-ai/claude-next";

// Initialize Claude with your API key and configuration
const claude = new Claude({
  apiKey: process.env.CLAUDE_API_KEY,
  // Other configuration options can be added here
});

// Example usage in a Next.js API route or server component
export async function POST(request: Request) {
  const { prompt } = await request.json();
  
  try {
    const response = await claude.completions.create({
      model: "claude-3-opus-20240229",
      prompt: `\n\nHuman: ${prompt}\n\nAssistant:`, 
      max_tokens: 1024,
    });
    
    return new Response(JSON.stringify({ completion: response.completion }), {
      headers: { "Content-Type": "application/json" },
    });
  } catch (error) {
    console.error("Error calling Claude API:", error);
    return new Response(JSON.stringify({ error: "Failed to get completion" }), {
      status: 500,
      headers: { "Content-Type": "application/json" },
    });
  }
}
```

--------------------------------

### API Key Configuration

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Example of a .env.local file for setting up API keys for different AI models.

```dotenv
# Required: Model selection
AI_CODE_REVIEW_MODEL=gemini:gemini-2.5-pro
# or
# AI_CODE_REVIEW_MODEL=openrouter:anthropic/claude-3-opus
# or
# AI_CODE_REVIEW_MODEL=anthropic:claude-3-opus

# Required: API key for the selected model type
# For Google Gemini models
AI_CODE_REVIEW_GOOGLE_API_KEY=your_google_api_key_here

# For OpenRouter models (Claude, GPT-4, etc.)
AI_CODE_REVIEW_OPENROUTER_API_KEY=your_openrouter_api_key_here

# For direct Anthropic Claude models
AI_CODE_REVIEW_ANTHROPIC_API_KEY=your_anthropic_api_key_here
```

--------------------------------

### Web Application Integration Example (Next.js)

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Integrate AI Code Review into a Next.js API route. This example shows how to receive review requests via POST and return the results.

```typescript
// pages/api/review.ts (Next.js)
import { performCodeReview } from '@bobmatnyc/ai-code-review/lib';

export default async function handler(req, res) {
  try {
    const result = await performCodeReview({
      target: req.body.target,
      config: {
        model: req.body.model,
        apiKeys: {
          openrouter: process.env.OPENROUTER_API_KEY
        }
      }
    });

    res.json(result);
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
}
```

--------------------------------

### Web Integration Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/DOCUMENTATION_INDEX.md

TypeScript example demonstrating web integration. This code snippet shows how to use the AI for code review in a web application context.

```typescript
import { ClaudeCodeReview } from "@ai-code-review/sdk";

async function reviewCode(code: string, language: string) {
  const reviewer = new ClaudeCodeReview({
    apiKey: "YOUR_API_KEY",
  });
  const result = await reviewer.review({
    code,
    language,
  });
  console.log(result);
}

reviewCode("function helloWorld() { console.log('Hello, world!'); }", "javascript");
```

--------------------------------

### Example Test Commands

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/scripts/gh/pr_template.md

These are example commands used for testing the AI code review tool. They cover running tests, initiating development mode with specific review types, and interactive mode for file analysis.

```bash
# Example test commands you ran
# pnpm test
# pnpm run dev architectural some-project
# ai-code-review --interactive some-file.ts
```

--------------------------------

### Serve trusty-analyze Dashboard

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/GITHUB_RELEASE_FINAL.md

Start the trusty-analyze server to access its embedded dashboard.

```bash
trusty-analyze serve
```

--------------------------------

### GitHub Actions CI/CD Integration Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/MCP_WORKFLOW_GUIDE.md

Example GitHub Actions workflow step for running AI Code Review as part of a CI/CD pipeline, using an environment variable for the API key.

```yaml
- name: AI Code Review
  env:
    OPENROUTER_API_KEY: ${{ secrets.OPENROUTER_API_KEY }}
  run: |
    npx @bobmatnyc/ai-code-review . --type security --no-confirm
```

--------------------------------

### Recommended Pre-commit Setup

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WORKFLOW.md

Execute linting, testing, and building before committing. Optionally, validate Track Down files using a Python script.

```bash
pnpm run lint && pnpm run test && pnpm run build
```

```bash
python trackdown/scripts/backlog-validator.py
```

--------------------------------

### Index Project with trusty-analyze

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/GITHUB_RELEASE_FINAL.md

After installing trusty-analyze, index your project directory to prepare it for analysis.

```bash
cd /path/to/project
trusty-analyze index .
```

--------------------------------

### Get Help

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/QUICK_START.md

Display the help message for the AI Code Review tool to understand all available commands and options.

```bash
ai-code-review --help
```

--------------------------------

### Initialize Application Services and Commands

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/chapters/design/plugin-system-design.md

Sets up core services, loads plugins, registers commands, and configures the CLI. Ensure all dependencies are available before initialization.

```typescript
// src/index.ts (enhanced)
async function initializeApplication(): Promise<void> {
  // Initialize core services
  const coreServices = CoreServicesProvider.getInstance();
  
  // Initialize plugin registry
  const pluginRegistry = new PluginRegistry(coreServices);
  await pluginRegistry.discoverAndLoadPlugins();
  
  // Register core commands
  const commandRegistry = new CommandRegistry();
  registerCoreCommands(commandRegistry);
  
  // Register plugin commands
  const plugins = pluginRegistry.getLoadedPlugins();
  for (const plugin of plugins) {
    const commands = plugin.getCommands();
    for (const command of commands) {
      commandRegistry.registerCommand(plugin.metadata.name, command);
    }
  }
  
  // Setup CLI with registered commands
  setupCLI(commandRegistry);
}
```

--------------------------------

### Basic Unified Client Initialization and Usage

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/unified-client-system.md

Shows the fundamental steps for using the Unified Client System: initializing the system, creating a client for a specific model, and generating a file review.

```typescript
import { createUnifiedClient, initializeUnifiedClients } from '../clients/unified';

// Initialize the system (call once at startup)
initializeUnifiedClients();

// Create a client for a specific model
const client = await createUnifiedClient('openai:gpt-4');

// Generate a review
const result = await client.generateReview(
  fileContent,
  filePath,
  'quick-fixes',
  projectDocs,
  options
);
```

--------------------------------

### Configure AI Provider API Keys

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WORKFLOW.md

Example configurations for `.env.local` file to set up API keys for different AI providers like Gemini, Anthropic, OpenAI, and OpenRouter.

```bash
# Choose one or more providers
AI_CODE_REVIEW_MODEL=gemini:gemini-2.5-pro
GOOGLE_API_KEY=your_google_api_key

# OR
AI_CODE_REVIEW_MODEL=anthropic:claude-3.5-sonnet
ANTHROPIC_API_KEY=your_anthropic_api_key

# OR  
AI_CODE_REVIEW_MODEL=openai:gpt-4o
OPENAI_API_KEY=your_openai_api_key

# OR
AI_CODE_REVIEW_MODEL=openrouter:anthropic/claude-3.5-sonnet
OPENROUTER_API_KEY=your_openrouter_api_key
```

--------------------------------

### GitLab CI Configuration for AI Detection

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/examples/ai-detection-usage-examples.md

Configure GitLab CI to perform AI code detection on merge requests. This setup installs the tool, runs the analysis, and fails the pipeline if AI-generated code is detected.

```yaml
# .gitlab-ci.yml
ai_detection:
  stage: test
  image: node:18
  before_script:
    - npm install -g @bobmatnyc/ai-code-review
  script:
    - |
      ai-code-review ./src \
        --type coding-test \
        --enable-ai-detection \
        --ai-detection-threshold 0.75 \
        --format json \
        --output ai-detection-results.json
    - |
      if grep -q '"isAIGenerated": true' ai-detection-results.json; then
        echo "AI-generated code detected - manual review required"
        exit 1
      fi
  artifacts:
    reports:
      junit: ai-detection-results.json
    expire_in: 1 week
  only:
    - merge_requests

```

--------------------------------

### Initialize Project Configuration

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/MCP_WORKFLOW_GUIDE.md

Run this command in your project's root directory to set up AI Code Review. It detects your toolchain, prompts for API keys, and creates necessary configuration files.

```bash
cd /path/to/your/project
ai-code-review init
```

--------------------------------

### Recess POC Configuration JSON

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/RECESS_POC_GUIDE.md

Example JSON configuration file for the Recess POC, defining assignment details and evaluation criteria weights. This structure guides the AI Code Review tool's assessment process.

```json
{
  "assignment": {
    "title": "Events Platform API Development - Recess Evaluation POC",
    "type": "take-home",
    "difficulty": "senior",
    "timeLimit": 240
  },
  "evaluation": {
    "criteria": {
      "technicalImplementation": { "weight": 25 },
      "codeQuality": { "weight": 20 },
      "security": { "weight": 15 },
      "testing": { "weight": 15 },
      "architecture": { "weight": 10 },
      "documentation": { "weight": 10 },
      "gitWorkflow": { "weight": 5 }
    }
  }
}
```

--------------------------------

### Install ts-prune

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/chapters/design/unused-code-cleanup-strategy.md

Install ts-prune as a development dependency to detect unused exports.

```bash
npm install --save-dev ts-prune
```

--------------------------------

### Example Workflow for API Key Validation and Saving

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Demonstrates the interactive workflow when API key validation fails, including options to enter a new key, switch providers, continue, or exit. It also shows how to save the validated API key for future use.

```bash
$ ai-code-review .

🔑 Validating API key for OpenRouter...
❌ API key validation failed: Invalid API key

Options:
  [1] Enter a new API key
  [2] Switch to a different provider
  [3] Continue anyway (review may fail)
  [4] Exit

Select [1-4]: 1

Enter your OpenRouter API key: sk-or-v1-xxx...

🔑 Validating new API key...
✅ API key is valid!

Would you like to save this key for future use? (y/n): y
📁 Saved to .ai-code-review/config.yaml

Continuing with review...
```

--------------------------------

### Run GitHub Repository Setup Script

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/scripts/gh/README.md

Execute the main wrapper script to automate GitHub repository configuration. This script offers a menu-driven approach to update directory structure, templates, branch protection rules, and repository settings.

```bash
./setup_github_repo.sh
```

--------------------------------

### Install Final Version of ai-code-review

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/GITHUB_RELEASE_FINAL.md

Install the last release of the ai-code-review package globally using npm.

```bash
npm install -g @bobmatnyc/ai-code-review@4.6.9
```

--------------------------------

### Package Preparation Script Steps

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WORKFLOW.md

Details the sequential steps performed by the `scripts/prepare-package.sh` script for preparing the package.

```bash
# Clean Previous Builds: `rm -rf dist/`
# Full Test Execution: `pnpm test` (all 476 tests must pass)
# TypeScript Compilation: `tsc` with type definitions
# Executable Creation: Add shebang (`#!/usr/bin/env node`) to `dist/index.js`
# Permission Setting: `chmod +x dist/index.js`
# Version Synchronization: Embed package.json version into code
# Model Map Validation: Verify all provider configurations load
# Package.json Validation: Ensure publishing metadata correct

```

--------------------------------

### Generate Sample Configuration File

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Generate a sample configuration file in either YAML or JSON format using the `generate-config` subcommand. Use the `--output` flag to specify the file path and `--format` for the desired format.

```bash
# Generate YAML configuration
ai-code-review generate-config --output .ai-code-review.yaml --format yaml
```

```bash
# Generate JSON configuration
ai-code-review generate-config --output .ai-code-review.json --format json
```

--------------------------------

### Copy Environment Sample

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Copies the sample environment file to '.env.local' for API key configuration.

```bash
cp .env.sample .env.local
```

--------------------------------

### Install AI Code Review Package

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WEB_INTEGRATION.md

Install the AI Code Review package in your web application using npm.

```bash
npm install @bobmatnyc/ai-code-review
```

--------------------------------

### Quick Release Commands

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/RELEASE.md

Use these commands for a standard release: first, run pre-release validation, then create the release (patch version bump), and finally, push to trigger automated publishing.

```bash
pnpm run pre-release
```

```bash
pnpm run release:patch
```

```bash
git push origin main --tags
```

--------------------------------

### Verify Global Installation

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Checks if the AI Code Review tool is installed globally and accessible by running the version command.

```bash
ai-code-review --version
```

--------------------------------

### Local Installation with npm

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Installs the AI Code Review tool as a development dependency in the current project using npm.

```bash
npm install --save-dev @bobmatnyc/ai-code-review
```

--------------------------------

### Example Scenario: New Version Release

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/BUILD_NUMBER_TRACKING.md

Illustrates the build number behavior when a new version is released. The build number resets to 0 for the new version.

```text
Current: 4.4.2 (build 15)
Update package.json to 4.4.3
Next build: 4.4.3 (build 0)  // Reset to 0
```

--------------------------------

### Prepare Executable and Fix Permissions

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

Ensure the executable is prepared by running the postbuild script and then fix its permissions.

```bash
npm run postbuild
chmod +x dist/index.js
```

--------------------------------

### Markdown Output Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/RECESS_POC_GUIDE.md

Example of the Markdown output format for evaluation reports. This format is human-readable and suitable for direct reporting.

```markdown
# Events Platform Evaluation Report

**Overall Score:** 75/100 (B+)
**Assessment Type:** Take-home assignment
**Difficulty Level:** Senior

## Executive Summary

[Comprehensive evaluation summary]

## Technical Implementation (20/25)

### Strengths
- Modern tech stack implementation
- Functional CRUD operations

### Areas for Improvement
- Error handling needs enhancement
- Input validation missing

## Recommendations

1. Implement comprehensive error handling
2. Add input validation middleware
3. Increase test coverage

```

--------------------------------

### Simple Pricing Calculation Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/chapters/features/enhanced-model-maps.md

Demonstrates calculating the cost for models with flat-rate pricing, showing how input and output tokens are billed.

```typescript
// Models with flat-rate pricing
const cost = calculateCost('anthropic:claude-4-sonnet', 100000, 50000);
// Input: 100k tokens @ $3/1M = $0.30
// Output: 50k tokens @ $15/1M = $0.75
// Total: $1.05
```

--------------------------------

### Install GitHub CLI on macOS

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/scripts/gh/README.md

Install the GitHub CLI using Homebrew on macOS. This tool is required for several configuration scripts.

```bash
brew install gh
```

--------------------------------

### Troubleshoot 'Command not found'

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/QUICK_START.md

If the command is not found after installation, try restarting your terminal or using 'pnpm exec' or 'npx' for local installs.

```bash
# For local install:
pnpm exec ai-code-review
npx ai-code-review
```

--------------------------------

### Set Up Repository Settings

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/scripts/gh/README.md

Manually configure repository settings using the Node.js script. This requires admin access to the repository.

```bash
node node_setup_script.js
```

--------------------------------

### Install pnpm using Corepack

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WORKFLOW.md

Install pnpm globally using Corepack, the recommended method for managing Node.js package managers.

```bash
corepack enable
corepack prepare pnpm@latest --activate
```

--------------------------------

### Using Prompt Fragments

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/README.md

Bash commands demonstrating how to use prompt fragments with specified positions.

```bash
ai-code-review src/index.ts --prompt-fragment "Focus on performance issues"
ai-code-review src/index.ts --prompt-fragment "Focus on security issues" --prompt-fragment-position start
```

--------------------------------

### Verify Local Installation with pnpm

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Verifies the local installation of the AI Code Review tool using pnpm by executing the version command.

```bash
pnpm exec ai-code-review --version
```

--------------------------------

### Global Installation with pnpm

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/INSTALL.md

Installs the AI Code Review tool globally using pnpm. This makes the 'ai-code-review' command available system-wide.

```bash
pnpm add -g @bobmatnyc/ai-code-review
```

--------------------------------

### Prepare Package for Distribution

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/WORKFLOW.md

Execute the command to prepare the package, typically involving compilation and bundling, before publishing.

```bash
npm run prepare-package
```

--------------------------------

### Development and Build Commands

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/CLAUDE.md

Common commands for local development, building the project, and running tests.

```bash
# Development
pnpm run dev              # Run from source
pnpm run build            # Full build
pnpm run test             # Run tests
```

--------------------------------

### Get Detailed Test Output

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

Run tests with the verbose reporter to get detailed output, useful for debugging mock failures after refactoring.

```bash
pnpm test -- --reporter=verbose
# Update mocks to match new import paths
```

--------------------------------

### Create README File

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/AI_DETECTION_TROUBLESHOOTING.md

Add a basic README.md file to the project if one is missing. Some analysis tools may require documentation files.

```bash
echo "# Project Description" > README.md
```

--------------------------------

### Install AI Code Review CLI

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/mcp/SERVER_QUICK_START.md

Install the AI Code Review CLI globally using pnpm or npm. This is recommended for MCP integration.

```bash
# Global installation (recommended for MCP)
pnpm add -g @bobmatnyc/ai-code-review

# Or with npm
npm install -g @bobmatnyc/ai-code-review
```

--------------------------------

### Profile Startup Performance

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

Use the --prof flag with Node.js to profile the startup performance of the application, useful for identifying optimization opportunities.

```bash
node --prof dist/index.js --version
# Optimize import structure if needed
```

--------------------------------

### Fix Global Command Installation

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/CLAUDE.md

Troubleshoot 'command not found' errors for global installations by either running a fix script or manually linking the package.

```bash
# Fix global installation
./scripts/fix-global-command.sh
```

```bash
# Or manually link
pnpm link --global
which ai-code-review
```

--------------------------------

### Configure API Keys for AI Providers

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/MCP_INTEGRATION.md

Set environment variables or create a .env.local file to configure your preferred AI provider and provide the necessary API keys. Supported providers include Gemini, Anthropic, OpenAI, and OpenRouter.

```bash
# Choose your preferred AI provider
AI_CODE_REVIEW_MODEL=gemini:gemini-2.5-pro

# API Keys (provide for your chosen provider)
AI_CODE_REVIEW_GOOGLE_API_KEY=your_google_api_key_here
AI_CODE_REVIEW_ANTHROPIC_API_KEY=your_anthropic_api_key_here
AI_CODE_REVIEW_OPENAI_API_KEY=your_openai_api_key_here
AI_CODE_REVIEW_OPENROUTER_API_KEY=your_openrouter_api_key_here
```

--------------------------------

### JSON Output Example

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/RECESS_POC_GUIDE.md

Example of the JSON output format, detailing metadata, summary, scores, and evaluation breakdown. This format is useful for programmatic analysis.

```json
{
  "metadata": {
    "strategy": "coding-test",
    "timestamp": "2025-07-10T12:00:00Z",
    "model": "gemini-1.5-pro",
    "assessmentType": "take-home",
    "difficultyLevel": "senior"
  },
  "summary": "Overall evaluation summary",
  "scores": {
    "overall": 75,
    "breakdown": {
      "technicalImplementation": 20,
      "codeQuality": 15,
      "security": 10
    }
  },
  "evaluation": {
    "strengths": ["List of strengths"],
    "weaknesses": ["List of weaknesses"],
    "recommendations": ["Improvement recommendations"]
  }
}
```

--------------------------------

### Verify Executable and Configurations

Source: https://github.com/bobmatnyc/ai-code-review/blob/main/docs/TOOLCHAIN.md

Commands to verify the project's executable and model configurations.

```bash
./dist/index.js --version
```

```bash
pnpm run validate:models
```