What this prompt does
This prompt directs Claude or ChatGPT to design an online tutoring and education booking system. You set [platform_name] and [platform_type], then describe the [subjects], the [student_levels], the [session_formats], the [target_users], and the [framework]. The model designs tutor discovery and matching, the tutor profile page, booking and scheduling, a virtual classroom, progress tracking and reports, a parent or guardian dashboard, and the framework implementation.
It works because a tutoring platform is multi-role — students book and attend, parents manage and pay, tutors teach and earn — and the prompt designs distinct views for each. By naming [subjects] and [student_levels], the model shapes the matching filters and expertise matrices. The [session_formats] variable drives the booking options (1-on-1, small group, async review), and the framework section covers WebRTC video, a collaborative whiteboard, and timezone handling stored in UTC.
When to use it
- You're building a tutoring marketplace and need matching, scheduling, and a classroom designed together.
- You want tutor discovery with a "why this tutor fits" matching display and intro videos.
- You need a booking flow with recurring sessions, pre-session questionnaires, and reminders.
- You're designing a virtual classroom with whiteboard, code editor, and file sharing.
- You need progress tracking with session notes visible to students and parents.
- You want a separate parent dashboard with payment history and spending controls.
Example output
The model returns a module-by-module design document. Discovery is specified with subject and level filters, tutor cards, availability snippets, and intro videos. The booking module covers timezone auto-detection, recurring setup, and reminder sequences. The virtual classroom details video with screen share, a collaborative whiteboard, a syntax-highlighted code editor, and consented recording. The parent dashboard covers multi-child oversight, payment history, and spending caps. The closing [framework] section adds WebRTC, Canvas-based whiteboard tooling, and UTC timezone handling. Expect a detailed spec, not finished code.
Pro tips
- List
[subjects]precisely so the expertise matrix and matching filters reflect what tutors actually teach. - Set
[student_levels]clearly; K-5 and college learners imply different tone and classroom tools. - Use
[session_formats]to switch features on — group sessions and async review change the booking and classroom design. - Name all three roles in
[target_users]so the student, parent, and tutor views each get proper attention. - For programming subjects, keep the code-editor-with-execution requirement explicit in the classroom section.
- Ask the model to expand the progress-tracking module if goal-setting and assessment history matter most.
