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Cover image for Introducing PrivateCV- Build Your Resume Without Compromising Privacy
Arunjyoti Debnath
Arunjyoti Debnath

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Introducing PrivateCV- Build Your Resume Without Compromising Privacy

#devchallenge #githubchallenge #cli #githubcopilot

GitHub Copilot CLI Challenge Submission

This is a submission for the GitHub Copilot CLI Challenge

What I Built

PrivateCV is a professional, open-source resume builder that runs entirely in your browser. Unlike traditional resume builders that collect and store your personal data on their servers, PrivateCV is built with privacy as its core principle and your information never leaves your device.

The application features:

  • 14 professionally-designed templates optimized for different industries and roles
  • Multiple export formats (PDF, DOCX, JPG, JSON) generated entirely client-side
  • Smart import capabilities from PDF, Word documents, LinkedIn CSV, and JSON
  • AI-powered career tools including ATS scoring, job matching, and career gap analysis
  • Optional encrypted cloud backup to your own Google Drive (BYOS - Bring Your Own Storage)
  • Full offline support as a Progressive Web App

What makes this project meaningful to me is solving a real problem I've experienced: the discomfort of uploading sensitive career information to unknown servers. With PrivateCV, job seekers maintain complete control over their data while still accessing powerful resume-building features.

Demo

Live Site: https://privatecv.vercel.app/
GitHub Repository: https://github.com/1arunjyoti/private-cv

Screenshots:

Landing Page

Template Selection

Resume content & customization

Dashboard & Resume Management

Settings page

My Experience with GitHub Copilot CLI

GitHub Copilot CLI significantly accelerated my development process, particularly when working with unfamiliar libraries and debugging complex integration issues. Rather than constantly switching between my terminal and browser to search documentation, I could ask questions directly in my workflow.

Some moments where it really helped:

  1. Implementing IndexedDB with Dexie.js - This was my first time working with browser-based databases at this scale. When designing the schema for storing resume data with proper relationships and indexes, Copilot CLI helped me understand the performance implications of different indexing strategies. It was particularly helpful in explaining why certain fields should be indexed versus just showing me the syntax.

  2. Debugging PDF generation edge cases - The @react-pdf/renderer library has specific constraints around styling and layout that differ from regular React. When sections were breaking awkwardly across pages, I used Copilot CLI to troubleshoot and helped me understand the library's page break behavior and suggested wrapping strategies that maintained visual consistency.

  3. Working with the Google Drive API - Implementing OAuth PKCE flow for the optional cloud sync feature involved several security considerations. Copilot CLI helped me navigate the Google Drive API documentation and understand the proper token refresh flow without storing sensitive credentials.

  4. Writing the AI integration layer - Since I needed to support multiple AI providers (OpenAI, Anthropic, Google Gemini, and local models), I used Copilot CLI to understand the different API patterns and how to create a unified abstraction layer. It suggested factory patterns and helped me avoid common pitfalls in error handling across different providers.

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