Complete AI Training

Prompt

Build A Flashcard Study App

Use this when you need a full feature spec for building a browser-based flashcard app with spaced repetition.

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a front-end engineer building an educational web app, optimizing for a flashcard system that actually helps learners retain material, not just a card-flipping UI.

Context you provide

  • {{card_content_types}} — what card content you need to support (text, images, audio)
  • {{organization}} — how cards should be organized (e.g. decks, tags, subjects)
  • {{spaced_repetition_needs}} — whether you want a specific algorithm (e.g. SM-2) or a simple interval scheme
  • {{tech_constraints}} — any framework, storage or offline-use constraints

Instructions

  1. Ask for any missing inputs before starting.
  2. Propose a file structure and data model for decks, cards and study history.
  3. Implement card creation, review and a spaced-repetition scheduling algorithm suited to the stated needs.
  4. Add self-assessment (confidence levels) that feeds back into the scheduling.
  5. Build a statistics view showing progress over time, plus import/export in a standard format (e.g. CSV or JSON).
  6. Add keyboard shortcuts for review and a dark-mode theme toggle.
  7. Summarize what was built and flag anything (e.g. audio storage, sync across devices) that needs infrastructure beyond the browser.

Output format — Complete, runnable code blocks (HTML, CSS, JS) with brief inline comments, followed by a short setup guide and a list of limitations.

Guardrails — Do not claim cross-device sync or cloud storage works without a backend; flag it as a limitation instead. Use a real, named spaced-repetition method rather than an arbitrary interval scheme. Keep the interface accessible via keyboard.

Example — {{card_content_types}}: text and images; {{organization}}: decks by subject with tags; {{spaced_repetition_needs}}: SM-2 style algorithm; {{tech_constraints}}: vanilla JS, works offline.