HackStack

Project Info

Slug-Schedule

Devpost

This project did not submit a demo video on Devpost.

Inspiration

Enrolling for classes at UCSC can be tedious and unintuitive. For instance, checking class eligibility or identifying scheduling conflicts often requires extra steps, making the process frustrating. We wanted to create a user-friendly and intuitive application that simplifies scheduling and enhances the overall experience for students.

What it does

Slug Scheduler analyzes your transcript and recommends classes to take for the next quarter based on the current course offerings.

How we built it

We used Next.js as the main framework and designed the interface using Figma. The project was powered by JavaScript, the npm package manager, and the GEMINI API for transcript analysis.

Challenges we ran into

Time management and task prioritization were significant challenges. We underestimated the complexity of certain tasks, which slowed down progress. Additionally, maintaining consistent productivity over extended periods proved difficult as fatigue set in.

Accomplishments we're proud of

We successfully built a web scraper capable of gathering comprehensive course data for a specific quarter. This includes course names, timings, enrollment numbers, and available slots, providing students with up-to-date and accurate information.

What we learned

We learned the importance of researching and familiarizing ourselves with the technologies we plan to use beforehand. For example, not deciding on a component library or CSS framework early on led to inefficiencies, with only one team member handling the frontend.

What's next

for Slug Scheduler We aim to add features like exporting schedules to Google Calendar for improved usability. Additionally, we plan to integrate Rate My Professor ratings to recommend courses based on professor reviews, helping students make more informed decisions.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • JavaScriptIn code
  • Next.jsIn code
  • ReactIn code
  • Tailwind CSSIn code
  • Google GeminiClaimed

5 of 6 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

48 KB

Source files

25

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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