Chronos
A timing assistant for course registration that accounts for server time and reaction speed
Not yet published.
Chronos
In a competitive course-registration session, the goal is not to click for the user—it is to help the user click at the right moment.
Chronos is a Manifest V3 Chrome extension that measures the current page’s estimated server time, network round-trip time (RTT), jitter, and the user’s reaction speed. Set a target time and Chronos runs a focused 10-second countdown, then signals the recommended click moment with a visual flash and a short beep.
Core features
- Estimated server time: Uses the page’s HTTP
Dateresponse and round-trip delay to estimate the offset between the local clock and the server clock. - Network monitoring: Calculates median RTT and jitter from multiple samples and labels the connection stable, watch, or unstable.
- Reaction calibration: Measures reaction time over five click tests and stores the result in Chrome local storage.
- Smart trigger: Combines reaction time, estimated one-way network delay, and a safety margin to signal slightly before the target time.
- Focused countdown: Switches to a large countdown during the final 10 seconds.
- Local-first privacy: Measurements and settings stay in the browser and are not sent to an external server.
User flow
- Open Chronos on a course-registration page.
- Let it measure the server clock and network conditions.
- Run reaction calibration if needed.
- Enter a target time and start the countdown.
- When the signal appears, click the registration button yourself.
Deliberate boundaries
Chronos never clicks application buttons, submits forms, sends repeated requests, or attempts to bypass CAPTCHAs or queues. Its timing is a personalized recommendation based on the current environment, not a guarantee of successful registration. Actual request processing still depends on each university’s site and browser conditions.
Status and roadmap
The current release is an early MVP that runs as an unpacked Manifest V3 extension with no build step. Planned work includes university-specific site adapters, confidence and error-range estimates, accessible low-stimulation alerts, result-based personalization, and automated unit, integration, and browser end-to-end tests.