What this prompt does
This prompt directs Claude or ChatGPT to design a fitness class booking and gym management interface. You set [business_name] and [business_type], then describe the [class_types], the [membership_tiers], the [facility_count], the [peak_hours], and the [framework]. The model designs a class schedule browser, a class detail and booking view, a member dashboard, waitlist management, membership and pricing, instructor profiles, and the framework implementation.
It works because class booking with live capacity, waitlists, and membership credits is real-time software, not a static calendar. By naming [class_types] and [membership_tiers], the model designs the color-coding and the plan-comparison matrix to match your studio. The [peak_hours] variable informs urgency indicators and waitlist behavior, and the framework section specifies live spot counters over WebSocket, QR check-in, and offline resilience.
When to use it
- You're building a fitness or gym booking app and need live class availability designed.
- You want waitlist auto-promote with a hold window and push notifications laid out.
- You need a member dashboard with attendance history, streaks, and credits remaining.
- You're designing membership tiers with a feature-comparison matrix and freeze flows.
- You want QR check-in and recurring booking specified.
- You need instructor profiles with ratings, following, and personal-training booking.
Example output
The model returns a view-by-view design document. The schedule browser is specified with day, week, and list modes, filters, class cards showing spots remaining, and "filling fast" urgency. The waitlist section details join-with-position, auto-promote, a 15-minute hold, and real-time position updates. The member dashboard covers attendance heatmaps, streaks, and achievement badges. The closing [framework] section adds live availability over WebSocket, a QR check-in scanner, and queued offline bookings. Expect a thorough spec, not finished booking logic.
Pro tips
- List
[class_types]fully so the category color-coding and filters reflect your actual schedule. - Spell out
[membership_tiers]with prices and inclusions so the plan-comparison matrix is accurate. - Use
[peak_hours]to justify the urgency indicators and stronger waitlist behavior at busy times. - Set
[facility_count]honestly — multiple locations require a location filter the model will add. - The auto-promote hold window is the trickiest part; keep the "15-minute hold then next person" rule explicit.
- Ask the model to expand the membership freeze and prorated upgrade flows if billing detail matters to you.
