What this prompt does
This prompt directs Claude or ChatGPT to design a fitness and workout tracker app. You set [app_name] and [app_type], then describe the [primary_goal], the [target_users], the [workout_types], the [device_integrations], and the [framework]. The model designs the home dashboard, the exercise library, the workout builder, an active workout mode, progress charts, body measurements, and social sharing, plus the framework implementation.
It works because workout tracking lives or dies on the active-workout screen — logging sets between exercises has to be fast and one-handed. By naming the [primary_goal] (for example progressive overload for strength) and [target_users], the model biases the design toward the right metrics and flows. The [workout_types] variable shapes the builder's supersets and circuits, and [device_integrations] drives the wearable and health-data sync the framework section specifies.
When to use it
- You're building a workout tracker and need the active logging flow designed for speed.
- You want an exercise library with body-diagram navigation and per-exercise personal records.
- You need a workout builder with templates, supersets, circuits, and rest periods.
- You're designing progress charts tuned to a goal like progressive overload.
- You want wearable and health-platform integrations accounted for.
- You need body-measurement tracking and social sharing laid out.
Example output
The model returns a screen-by-screen design document. The home dashboard covers today's plan, a weekly activity ring, streaks, and quick stats. The exercise library details muscle-group and equipment browsing with body-diagram tap zones and per-exercise records. The workout builder specifies templates, drag-to-order, sets and reps, and superset grouping. The active workout mode covers a set logger showing previous performance, an auto-starting rest timer, and exercise navigation. The closing [framework] section adds offline storage and device sync. Expect a detailed app spec, not finished code.
Pro tips
- Set
[primary_goal]clearly; progressive overload, endurance, and weight loss each bias which metrics the dashboard and charts surface. - Match
[target_users]to skill level — advanced lifters want RPE and 1RM detail that beginners don't. - List
[workout_types]so the builder handles supersets, circuits, and timed work correctly. - Name your real
[device_integrations]so the sync notes (Apple Health, Wear OS, heart rate monitors) apply. - Keep the active-workout logger fast and one-handed — showing previous performance inline is the key detail.
- Pin
[framework]to your stack (for example React Native with offline storage) so the offline-first notes are usable.
