studysprint-students is a mobile-first web application for high-school students in the Philippines that turns one uploaded PDF — class notes, a textbook chapter, or lecture material — into three study tools automatically: an easy-to-understand study guide, a set of flashcards for active recall, and a quiz to test understanding after reviewing. The product is delivered under the working name DocFlash.
The problem this product addresses is that students spend hours reading PDFs, textbooks, and lecture notes but often struggle to remember the information, and creating flashcards and practice quizzes manually takes even more time. The product's intent is to remove that manual preparation work so a student can move directly from raw course material to active study.
The audience is high-school students, initially in the Philippines, studying on mobile-first web browsers. The business model is free initially. The first release is deliberately narrow: it proves that students can upload their materials and use the generated learning tools to prepare more effectively for real exams, rather than attempting to be a full AI tutor or an elaborate learning-management system.
DocFlash is a responsive web application with an application-owned student identity, private document storage, and a server-side generation pipeline. A student creates an account, uploads a PDF, and the system extracts the document's text (applying OCR when the PDF is scanned), then generates a study guide, flashcards, and a quiz that are grounded in that document. The student reads the guide, reviews the flashcards — revealing answers and marking concepts they find difficult — takes the quiz, and lands on a results page showing the score and the topics to review.
The single active human actor is the Student. The AI generation service, the PDF text-extraction/OCR component, the private file store, and the persistent database are non-persona system and provider actors that support the student's work; they do not act on their own behalf.
Current scope is the five must-have capabilities — PDF upload, AI study guide, flashcards, quiz generator, and results page — plus the identity and persistence needed to make that workflow usable and resumable. Explicitly deferred to a next version are saved study sets for revisiting previous materials and spaced repetition that schedules reviews based on recall performance. Explicitly out of scope for the first release are a full AI tutor, an elaborate learning-management system, social feeds, followers and leaderboards, video lessons or a full online classroom, an elaborate AI chatbot, complex calendars and school-management systems, and paid subscriptions before demand is validated.
DocFlash is delivered as a first-party, mobile-friendly responsive web application. There is no separate Android or iOS application; the mobile-first web app is the delivery surface, which lets the team test the idea without paying to build separate native apps.
Access is application-owned. Because the product stores a student's uploaded documents and generated study materials privately and lets them return to continue a study workflow, the student establishes their own identity on first use and verifies it on return. The public entry surface and the two identity surfaces are reachable without being signed in; the upload, study guide, flashcards, quiz, and results surfaces require a signed-in student, because each one reads or writes state that belongs to that specific student's private document.
The generation pipeline is server-side and provider-backed: text extraction (with OCR for scanned PDFs) and AI generation with structured output run behind the application, not in the browser. The uploaded file itself is held in private cloud storage and is never publicly addressable.
Current versus future boundary: everything described in this document is current MVP scope. Saved study sets and spaced repetition are next-version features and are not built, surfaced, or accepted in this release. The product is free initially; no paid subscription, entitlement, or billing behavior exists in this release.
The authoritative sources for this project are product plans and an interface demonstration, not a populated content collection. The only concrete content facts supplied are the demonstration study set used to illustrate the flashcard and quiz experience:
This demonstration content is sample biology content only. It is not extracted from an uploaded PDF, and it is not seeded product data. No other verified factual entities, collections, fields, values, dates, contacts, links, or media references were supplied.
FR-1 — PDF upload and text extraction (explicit) As a Student, I should upload a PDF containing class notes, textbook chapters, or lecture materials so that the app can extract its text and turn it into study tools.
FR-2 — Scanned-PDF handling with OCR (explicit) As a Student, I should have scanned PDFs handled with OCR when needed so that a photographed or scanned chapter still produces usable study tools.
FR-3 — AI study guide generation (explicit) As a Student, I should receive an easy-to-understand study guide that summarizes key concepts, definitions, and explanations from my uploaded PDF so that I can read an organized version of my material instead of the raw document.
FR-4 — Flashcard generation (explicit) As a Student, I should receive question-and-answer flashcards generated from my uploaded PDF so that I can practice active recall on the material.
FR-5 — Flashcard review: reveal, navigate, and mark difficult concepts (explicit) As a Student, I should answer each flashcard, reveal its explanation, and mark the concepts I find difficult so that I know which material needs more attention.
FR-6 — Quiz generation with multiple-choice and short-answer questions (explicit) As a Student, I should receive a quiz generated from my uploaded PDF containing multiple-choice and short-answer questions so that I can test my understanding after reviewing.
FR-7 — Grounding in the uploaded document and insufficient-information indication (explicit) As a Student, I should have every generated question and answer grounded in my uploaded document, and I should be told when the PDF does not contain enough information to answer a question, so that I can trust the material and know its limits.
FR-8 — Quiz completion with score and explanations (explicit) As a Student, I should take the generated quiz and receive a score with explanations so that I understand what I got right and why.
FR-9 — Results page with score and topics to review (explicit) As a Student, I should see my quiz score and the topics I need to review so that I know exactly what to revisit before an exam.
FR-10 — Student self-service enrollment (required_inference) As a Student, I should be able to create my own account on first use so that my uploaded documents and generated study materials are private to me and available when I return.
FR-11 — Returning verification (required_inference) As a Student, I should be able to verify my identity on return so that I can continue with my own uploaded documents and generated study materials.
FR-12 — Persistent storage of uploaded-document state and study workflow continuity (required_inference) As a Student, I should have my uploaded document and its generated study materials persist so that I can leave and come back without losing my work.
FR-13 — Private file storage for uploaded PDFs (explicit) As a Student, I should have my uploaded PDF held in private cloud storage so that my course material is not publicly accessible.
Product context. A high-school student in the Philippines preparing for real exams from class notes, textbook chapters, and lecture materials that arrive as PDFs. They study on a mobile-first web browser, often on a modest Android device, and they are not looking for another notes app or a complicated AI tutor — they are looking for the fastest path from a document they already have to material they can actually be tested on.
Primary goal. Turn one uploaded PDF into a study guide, flashcards, and a quiz, work through them, and finish knowing which topics still need attention before the exam.
Distinct accepted responsibilities. The Student is the only active human actor in this product, and their work is a single continuous study workflow with several distinct responsibilities: choosing and uploading a PDF; reading the generated study guide; reviewing flashcards by answering each card, revealing its explanation, and marking the concepts they find difficult; taking the generated quiz, which mixes multiple-choice and short-answer questions; and reading their score and the topics to review on the results page. They also own their own access — creating their account on first use and verifying it on return — because the uploaded documents and generated materials are private to them and must still be there when they come back.
Relevant inputs and decisions. The Student supplies the PDF itself and decides which document to study. During flashcard review they decide which concepts are difficult. During the quiz they decide on each answer, and on the results page they decide what to revisit. They also decide, when the app tells them a PDF does not contain enough information to answer a question, whether to continue with what the document does support or to upload a different document.
Interactions with other accepted participants. The Student is the sole human participant. Their work is carried out with the AI generation service, the PDF text-extraction and OCR component, the private file store, and the persistent database — all of which act only in support of the Student's requests and produce no outcomes on their own behalf.
Observable success. The Student completes the full workflow — upload → study guide → flashcards → quiz → weak topics — and finishes knowing what to revisit. The product's proposed validation targets for this behavior are that 70%+ successfully upload a PDF, 60%+ review generated flashcards, 50%+ finish a quiz, 30%+ return within 7 days, and 70%+ find the study guide useful. These are proposed targets, not proven benchmarks.
Muse and headline. Susan Kare — Charming clarity, one pixel at a time. DocFlash is fundamentally a card system (upload → guide → flashcards → quiz → weak topics), and Kare's craft of the legible, personality-filled card on a small grid gives the product an identity no SaaS template owns while keeping a study tool from feeling like homework-adjacent bureaucracy. The register is "a friendly coach that hands you one small card at a time" — warm, slightly playful, system-like, and honest about what it can and cannot do with a scanned PDF.
Color tokens (light mode).
| Role | Hex | Use |
|---|---|---|
| Background | #F4F1E8 | Warm paper-white ground |
| Surface | #FFFFFF | True-white card surfaces, so flashcards read as physical cards on a desk |
| Text | #1C1B18 | Ink for all body and headings; high contrast on both grounds |
| Primary | #2F6F5E | Deep pine — header bars, active tab, focus ring, the Reveal answer button |
| Accent | #E4572E | Burnt orange — rationed hard; only the current card's index chip, the next arrow, the weak-topic bar on results, and the "not enough info" badge |
| Muted | #8A8578 | Metadata such as "Biology · 25 min", "Card 1 of 3", timestamps |
No blue anywhere. Color proportion is roughly 70% paper/white, 20% pine, 10% orange, and the orange never appears twice in one viewport at the same weight.
Typography. Headings: Silkscreen at 700 for the wordmark, screen titles, and card counters — used at genuinely small sizes (16–28px) so it reads as a system glyph rather than a poster, and never for a string over 30 characters. Body: IBM Plex Sans at 400/600/700 — 700 for card questions and quiz prompts, 400 for study-guide body at 17px/1.65 with a 62-character measure, 600 for buttons and labels. Silkscreen is never set for a paragraph, study-guide prose, or quiz answer text.
Type scale. 1.25 modular: 12 / 14 / 16 / 17 / 20 / 24 / 28 / 40. Screen title clamp(24px, 6vw, 40px); card question clamp(20px, 5.2vw, 28px); study-guide body fixed at 17px; labels and counters 12–14px with 0.08em tracking. Line-height 1.65 for guide prose, 1.25 for card questions.
Shape language. Chunky 2px ink borders on every card, button, and input — a drawn outline, not a shadow. Radii stay at 4px (a nod to the grid, not a squircle) except the flashcard itself, which gets 8px so it reads as a physical object you could pick up. Buttons are pill-shaped only for the single primary action per screen; everything else is a rounded rect. Progress is drawn as a row of small squares — filled, half, empty — never a smooth bar. Icons are 24px and 32px pixel pictograms drawn on a visible 8px grid: a document with a folded corner for PDF, a stack of cards, a checkmark square, a clock face, and a question-mark-in-square for "not enough info". No drop shadows, no glass, no gradients.
Spacing rhythm. A 4px base unit with 8px grid alignment for pictograms and progress squares; 16px gutters on mobile; card padding in multiples of 8px.
Layout. Mobile-first single column at 375px: a compact pine header bar with the DocFlash wordmark in Silkscreen and a 3-step progress row (Upload · Review · Quiz) drawn as three small squares; below it one card occupies the full width with 16px gutters and never scrolls horizontally. At 768px the layout becomes a two-column split: a 200px left rail holding the study-set meta (document name, page count, card index as a vertical square grid) and the card column at a 560px max width. At 1280px the same two-column structure centres inside a 1040px frame with the card column at 620px and the rail gaining a "topics to review" list. The study guide is a reading column, never wider than 62 characters. The quiz is one question per screen with four full-width answer rows (48px min height, thumb-reachable), and the results screen is a score block plus a horizontal array of weak-topic chips that wrap — never a scroll-away.
Imagery style. The imagery is the interface itself. Pixel pictograms on the 8px grid carry every concept: a folded-corner document, a stack of cards, a magnifier over a page for the study guide, a clock for the focus timer, a checkmark square, and a small shrugging figure for "this PDF doesn't contain enough information". One recurring character — a 32px pixel student with a backpack — appears only as a static spot mark beside encouragement lines ("One card at a time. You've got this.") and never animates as a mascot loop. No photography, no gradients, no 3D blobs, no stock students. The uploaded PDF's own first page can appear as a small 1px-border thumbnail in the study-set rail, treated as a document artefact rather than a hero image.
The upload desk. The first screen is not a marketing hero — it is the upload desk. A full-bleed warm paper ground (#F4F1E8) carries a compact pine header bar across the top with the Silkscreen wordmark "DocFlash" and the three-square step row. Directly beneath, offset left rather than centred, sits a single large drop card: a true-white panel with a 2px ink border and 8px radius, roughly 70% of the viewport width on mobile and 560px on desktop, containing a 96px pixel document pictogram on the 8px grid, a 700-weight Plex line at clamp(24px, 6vw, 40px) reading "Turn one PDF into a study guide, flashcards, and a quiz.", a 17px muted subline naming the workflow, and one pine pill button "Choose a PDF" with a small orange arrow chip pinned to its right edge. Behind and to the right of that card, three smaller white cards fan out at slight offsets like a stack mid-deal — one showing a flashcard question, one a quiz option row, one a filled progress grid — cropped by the right viewport edge on mobile and fully visible at 1280px. There is no centred headline, no gradient blob, and no floating dashboard mockup: the composition is a desk with a stack of cards on it. The concept recomposes only accepted content and controls — the entry explanation, the workflow steps, the Choose a PDF action, and the identity routes — and introduces no new behavior or destination.
Interaction Model: Static Motion Tempo: restrained Hero Dimensionality: flat
Landing Hero Motion Brief. The focal subject is the stack of cards on the desk: the large drop card with its pixel document pictogram, and the three smaller cards fanned behind it. The input→transformation→outcome thesis is that a student's raw PDF becomes three study tools — the fanned cards settle into their offsets as the drop card takes focus, expressing "one document in, three tools out" using only the accepted workflow. The motion vocabulary is restrained and frame-based, like an old screen repainting: 120ms steps with linear easing, no bounce and no springs. The composed first frame shows the pine header bar with the three-square step row, the drop card offset left with its pictogram, headline, subline, and pine pill button with the orange arrow chip, and the three fanned cards already in place at their offsets. Under prefers-reduced-motion the hero is a static arrangement: the cards appear at their final offsets with no translation and no stagger, and every readable element — wordmark, headline, subline, button label, and card text — stays whole inside its container at 375px, 768px, and 1280px.
Motion rules across the product. Card flip on Reveal answer is a two-frame swap (question frame → answer frame) with a 60ms ink-flash on the border, not a 3D rotation. Advancing cards slides the new card in from the right by 24px while the old one fades at 100ms. Progress squares fill one at a time with a 40ms stagger. The quiz score counts up in whole numbers, 8 steps of 60ms, then stops. Under prefers-reduced-motion all of this collapses to instant state changes with no translation and no stagger; the progress squares simply appear filled.
NFR-1 — Mobile-first responsive web delivery (explicit) The product is a mobile-friendly responsive web app. There is no separate Android or iOS application. Layout must hold at 375px, 768px, and 1280px, and the card column must never scroll horizontally at 375px — the card fits whole, with readable text and controls fully inside the container. Rationale: the source explicitly chose a mobile-friendly web app so the idea could be tested without paying to build separate native apps.
NFR-2 — Grounding and honesty of generated content (explicit) Generated questions and answers must be grounded in the uploaded document, and the app must indicate when the PDF does not contain enough information to answer a question. Rationale: this is a stated critical requirement; a study tool that invents answers is worse than no tool.
NFR-3 — Private file storage (explicit) Uploaded PDFs are held in private cloud storage and are never publicly addressable. Rationale: explicit constraint; the documents are the student's own course material.
NFR-4 — Persistent storage and workflow continuity (required_inference) Uploaded-document state and the generated study materials must persist against the student's account so the workflow can be resumed. Rationale: the accepted workflow spans multiple sessions and the source explicitly calls for persistent student accounts and persistent data.
NFR-5 — Structured AI output (explicit) Study guide and quiz generation use an AI API with structured output. Rationale: explicit technology choice; structured output is what makes the guide sections, flashcards, and quiz items reliably renderable.
NFR-6 — Scanned-document handling (explicit) Scanned PDFs must be handled with OCR if needed, and processing errors must be shown. Rationale: explicit roadmap requirement for the upload-and-extract phase.
NFR-7 — Legibility on modest mobile screens (explicit, from the creative direction) Body text is set at 17px/1.65 with a 62-character measure; quiz answer rows are at least 48px tall and thumb-reachable; readable text and controls stay entirely inside the viewport and their container at every breakpoint. Rationale: the audience studies on cheap Android screens, and the direction requires that headlines, wordmarks, labels, numbers, and card text and controls stay whole.
NFR-8 — Reduced-motion support (explicit, from the creative direction)
Under prefers-reduced-motion, all motion collapses to instant state changes with no translation and no stagger, and the hero presents a usable static arrangement. Rationale: accessibility requirement carried by the direction.
NFR-9 — No blue or indigo, no generic SaaS template (explicit, from the creative direction)
No blue or indigo anywhere, including #2563EB, #4F46E5, #6366F1, or any blue-to-indigo gradient. Inter, Roboto, Arial, Helvetica, Open Sans, Lato, Poppins, and system-ui are not used for any text role. No gradient-blob heroes, frosted glass, or soft drop shadows. Rationale: the generic indigo/blue-on-white SaaS template is explicitly forbidden for this project.
NFR-10 — Free initially (explicit) The product is free initially; no paid subscription is built before demand is validated. Rationale: explicit business-model constraint.
Source-specified choices are preserved exactly:
Supporting implementation notes:
Constraints (binding).
system-ui for any text role; no gradient-blob heroes, frosted glass, or soft drop shadows; Silkscreen is never set for paragraphs, study-guide prose, or quiz answer text; no smooth percentage progress bar or circular timer ring; no photography of students, stock classroom imagery, or 3D mascot loops; no more than one orange accent element competing in a single viewport; no horizontal scroll on the card column at 375px. (explicit, from the creative direction)Assumptions (narrow, labeled).
Validation targets (proposed, not proven benchmarks). 70%+ of students successfully upload a PDF; 60%+ review generated flashcards; 50%+ finish a quiz; 30%+ return within 7 days; 70%+ find the study guide useful. Student testing is planned with 20–30 students, and students are asked after a week: did the app help you start studying when you didn't feel like it; did it help you remember what you studied; what made you stop using it, if anything.
Two-week roadmap. Days 1–3: upload and extract — accept PDFs, extract text, handle scanned PDFs with OCR if needed, and show processing errors. Days 4–6: study guide — generate summaries, key terms, definitions, and topic sections. Days 7–9: flashcards and quizzes — generate question-answer pairs and multiple-choice quizzes with explanations. Days 10–12: results and storage — save study sets, track quiz results, and identify weak topics. Days 13–14: student testing — test with 20–30 students, fix confusing features, and measure whether students finish their study sessions.
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