Burnout Detector for Coders

Manasa Krishna — Mon, 16 Feb 2026 09:20:55 +0000

What we Built

Burnout is one of those problems every developer silently deals with but rarely measures. We push through long coding sessions, skip breaks, and normalize late-night work until productivity drops or motivation fades. We wanted to build something that makes burnout visible, measurable, and actionable.

That idea became Burnout Detector for Coders a local-first developer productivity system designed to track coding sessions, analyze focus patterns, detect burnout risk, and suggest healthier work habits. Instead of being another time-tracking app, this tool focuses on behavioral signals that indicate mental fatigue: long uninterrupted sessions, insufficient breaks, late-night coding streaks, and excessive daily hours.

The project is built as a three-layer system:

A CLI tool that developers actually use while coding
A backend API that aggregates and analyzes session data
A frontend dashboard that visualizes productivity and burnout risk clearly

The CLI is the heart of the system. It tracks when a coding session starts and stops, records break intervals, and computes meaningful analytics locally. The backend exposes clean REST APIs for aggregated insights, while the frontend presents those insights in a professional, dark-mode SaaS dashboard with subtle animations and clear visual hierarchy.

To us, this project represents a shift from “working harder” to working intentionally using data to protect focus and mental health without disrupting the developer workflow.

Demo

The project includes:

A fully functional CLI with commands such as start, stop, break, stats, and suggest
A REST backend that computes daily and weekly analytics
A responsive frontend dashboard with animated charts and burnout indicators

🔗 Project Repository:

cli-hackathon.vercel.app

🎥 Demo Video:

res.cloudinary.com

The demo walkthrough shows:

Starting and stopping coding sessions from the CLI
Automatic tracking of breaks and session duration
Burnout score calculation based on real behavioral patterns
A frontend dashboard displaying weekly productivity trends, focus durations, and risk indicators

Our Experience with GitHub Copilot CLI

GitHub Copilot CLI played a critical role in how this project was built not by writing everything for me, but by accelerating the boring parts so we could focus on design and logic.

We primarily used Copilot CLI to:

Scaffold the CLI command structure cleanly and consistently
Generate boilerplate for Express routes and validation layers
Refactor analytics logic into readable, modular functions
Improve CLI UX with colored output, summaries, and edge-case handling
Speed up repetitive frontend component patterns while keeping full design control

One of the biggest advantages was how Copilot CLI helped me iterate faster. We could prototype a session-tracking flow, test it, then ask Copilot to refactor or optimize without breaking the mental flow of development. It felt less like autocomplete and more like having a second engineer handling routine tasks.

Importantly, We was intentional about how I used Copilot. All architectural decisions, burnout scoring logic, UX choices, and visual design direction were made manually. Copilot handled execution assistance not product thinking. That balance ensured the final result feels hand-crafted and production-ready, not auto-generated.

Using Copilot CLI didn’t replace our development process it enhanced it, allowing me to ship a more complete, polished system within a limited timeframe.

Closing Thoughts

Burnout Detector for Coders is a practical experiment in building developer tools that respect human limits. It’s fast, local-first, and designed to fit naturally into a developer’s workflow rather than interrupt it.

This project also reflects how GitHub Copilot CLI can be used responsibly not to shortcut learning, but to remove friction and help developers focus on solving real problems.

Thanks to GitHub and the Copilot team for organizing this challenge. Building this project was both technically rewarding and personally meaningful.

Credits

This project was built collaboratively with shared ownership across product vision, architecture, and implementation.

👨‍💻 @srikartik_mateti_02615805

Core CLI architecture and session tracking logic

Burnout scoring system design and behavioral signal modeling

Backend API structure and analytics processing

System integration and overall product direction

👨‍💻 @manasssk

Frontend dashboard design and implementation

Data visualization, animations, and UI/UX refinement

CLI UX improvements and usability enhancements

Testing, polishing, and demo preparation

Together, we designed Burnout Detector for Coders as a local-first, developer-centric system focused on sustainable productivity. This project reflects both technical collaboration and a shared commitment to building tools that support developer mental health.

Forem: Manasa Krishna

Burnout Detector for Coders