TalentScout Agent Guide

Project Overview

TalentScout is a Next.js application that helps companies find talent and helps talent find jobs. The application uses MongoDB, GraphQL with Apollo, and Next.js with TypeScript and Tailwind CSS.

Development Environment Setup

• Run npm install to install all dependencies
• Copy .env.example to .env.local and fill in the required variables
• Run ./setup.sh to configure OpenAI Codex integration
• Run npm run dev to start the development server

Testing Instructions

• Run npm run lint to check for linting errors
• Run npm run build to ensure the application builds correctly

Code Structure

• /src - Contains all source code
  • /src/app - Next.js App Router pages and layouts
  • /src/components - React components
  • /src/utils - Utility functions including OpenAI integration
  • /src/graphql - GraphQL schemas and resolvers
  • /src/models - MongoDB models

OpenAI Codex Integration

Setup

1. Obtain an OpenAI API key from OpenAI Platform
2. Run ./setup.sh and enter your API key when prompted
3. The script will configure both .env.local and .codexrc files

Available Codex Features

Code Generation

Use the generateCodeCompletion function from src/utils/openai.ts to generate code based on prompts:

import { generateCodeCompletion } from '@/utils/openai';

// Example: Generate a React component
const prompt = 'Create a React component that displays a user profile';
const generatedCode = await generateCodeCompletion(prompt, {
  language: 'typescript',
  maxTokens: 500,
  temperature: 0.7
});

Code Analysis

Use the analyzeCode function to get suggestions for improvements and bug fixes:

import { analyzeCode } from '@/utils/openai';

// Example: Analyze a function for improvements
const codeToAnalyze = `function calculateTotal(items) {
  let total = 0;
  for (let i = 0; i < items.length; i++) {
    total += items[i].price;
  }
  return total;
}`;

const analysis = await analyzeCode(codeToAnalyze, 'javascript');

Unit Test Generation

Use the generateUnitTests function to create tests for your code:

import { generateUnitTests } from '@/utils/openai';

// Example: Generate Jest tests for a function
const codeToTest = `export function validateEmail(email) {
  const regex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
  return regex.test(email);
}`;

const tests = await generateUnitTests(codeToTest, 'javascript', 'jest');

Best Practices for Using Codex

1. Provide Clear Context: When generating code, include relevant context about your project structure and requirements.

2. Review Generated Code: Always review and test code generated by Codex before integrating it into your project.

3. Iterative Refinement: Use Codex iteratively, refining prompts based on initial results to get better output.

4. Security Considerations: Never include sensitive information in your prompts to Codex.

5. Rate Limiting: Be mindful of OpenAI API rate limits and costs when making frequent requests.

Contribution Guidelines

• Follow TypeScript best practices
• Use Tailwind CSS for styling
• Write clean, modular code
• Add appropriate comments and documentation
• Leverage Codex for code reviews and suggestions

PR Instructions

• Provide a clear title and description
• Reference any related issues
• Include screenshots for UI changes
• Ensure all tests pass
• Consider including Codex-generated analysis of your changes