{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_omnisets","slug":"omnisets","name":"OmniSets","type":"product","url":"https://www.omnisets.com","page_url":"https://unfragile.ai/omnisets","categories":["app-builders"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_omnisets__cap_0","uri":"capability://text.generation.language.ai.driven.flashcard.generation.from.unstructured.text","name":"ai-driven flashcard generation from unstructured text","description":"Automatically generates question-answer flashcard pairs from arbitrary text input (paragraphs, articles, documents) using LLM-based extraction and synthesis. The system parses input text, identifies key concepts and relationships, and generates pedagogically-structured cards without manual authoring. Uses prompt engineering or fine-tuned models to extract factual assertions and convert them into testable questions with concise answers.","intents":["I want to convert a textbook chapter into study cards without manually typing each one","I need to quickly create flashcards from lecture notes or research articles","I want to generate cards from multiple sources without copy-pasting content"],"best_for":["High school and early college students studying fact-dense subjects (vocabulary, history, biology terminology)","Self-directed learners who lack time for manual card creation but need rapid study material generation","Students in subjects with high-volume memorization requirements (medical terminology, language learning)"],"limitations":["AI-generated cards frequently miss contextual nuance and interdependencies between concepts, creating superficial Q&A pairs that don't promote deep understanding","No semantic validation of generated cards — may produce factually incorrect or misleading question-answer pairs without human review","Struggles with domain-specific terminology and abstract concepts that require domain expertise to frame properly","Cannot infer learner's prior knowledge level, so generated difficulty may be mismatched to target audience"],"requires":["Text input (minimum ~100 characters for meaningful extraction)","Active internet connection for LLM API calls","Account creation (free tier available)"],"input_types":["plain text","document files (PDF, DOCX inferred from 'documents' mention)","URLs (web content extraction)","pasted text blocks"],"output_types":["structured flashcard objects (question, answer, metadata)","flashcard sets (collections of cards with metadata)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_1","uri":"capability://data.processing.analysis.multi.format.document.ingestion.and.content.extraction","name":"multi-format document ingestion and content extraction","description":"Accepts study material in multiple formats (plain text, PDF documents, DOCX files, URLs) and normalizes them into a unified text representation for card generation. Implements format-specific parsers (PDF text extraction, DOCX parsing, HTML scraping for URLs) that handle encoding, layout preservation, and content filtering before passing to the LLM pipeline. Abstracts format complexity from the user.","intents":["I want to upload a PDF textbook chapter and auto-generate cards from it","I want to paste a URL to an article and have cards created from its content","I want to drag-and-drop a Word document and get instant flashcards"],"best_for":["Students with diverse source materials (textbooks, lecture slides, online articles)","Users who want to consolidate study material from multiple formats into a single study set","Non-technical learners who expect drag-and-drop simplicity"],"limitations":["PDF extraction quality degrades with scanned images, complex layouts, or embedded graphics — may lose context or misparse tables","URL scraping may fail on JavaScript-heavy sites, paywalled content, or sites with aggressive bot detection","No support for audio or video input (mentioned as 'multi-format' but likely limited to text-based formats)","Large documents (>10MB or >50,000 words) may hit API token limits or timeout"],"requires":["File upload capability (browser-based or API endpoint)","PDF/DOCX parsing library (e.g., PyPDF2, python-docx, or equivalent)","HTTP client for URL fetching and parsing (e.g., BeautifulSoup, Selenium for JS-heavy sites)","Text normalization pipeline (whitespace handling, encoding detection)"],"input_types":["plain text (direct paste or text file)","PDF documents","DOCX/Word documents","URLs (web pages)"],"output_types":["normalized plain text","extracted text with metadata (source, page number, section)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_2","uri":"capability://planning.reasoning.spaced.repetition.scheduling.and.review.algorithm","name":"spaced repetition scheduling and review algorithm","description":"Implements an evidence-based spaced repetition algorithm (likely SM-2 or similar) that schedules card reviews at scientifically-optimized intervals based on learner performance. Tracks card difficulty, user responses (correct/incorrect), and review history to compute next review date. Integrates with the study UI to surface cards at the right time, maximizing long-term retention while minimizing study time.","intents":["I want the app to automatically schedule my card reviews so I study the hardest cards more often","I need a study plan that adapts to my performance on each card","I want to optimize my study time by focusing on cards I'm weak on"],"best_for":["Self-directed learners who understand spaced repetition and want evidence-based study scheduling","Students preparing for high-stakes exams (SAT, GRE, medical boards) where retention is critical","Long-term language learners who need consistent, optimized review schedules"],"limitations":["Algorithm assumes consistent user engagement — if user skips reviews for days, the schedule degrades and cards may be forgotten","No customization of spacing parameters in free tier — users cannot adjust aggressiveness of review intervals","Doesn't account for card difficulty interdependencies — treats each card as independent rather than recognizing prerequisite relationships","No export of scheduling data — users cannot analyze or optimize their own learning patterns"],"requires":["User account with persistent storage (database to track review history)","Client-side or server-side timer/scheduler (cron job or client-initiated polling)","Card metadata storage (difficulty factor, interval, ease factor, last review date)"],"input_types":["user response to card (correct/incorrect/partial)","card metadata (current difficulty, review history)"],"output_types":["next review date/time","card queue (ordered list of cards to review today)","scheduling metrics (ease factor, interval, repetition count)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_3","uri":"capability://planning.reasoning.personalized.card.difficulty.and.learning.path.adaptation","name":"personalized card difficulty and learning path adaptation","description":"Tracks user performance on individual cards and adjusts presentation difficulty, review frequency, and card ordering based on learner mastery. Uses performance signals (response time, accuracy, confidence ratings) to infer card difficulty and learner readiness. May implement adaptive questioning where card complexity increases as user demonstrates mastery, or decreases if user struggles.","intents":["I want the app to show me harder cards when I'm doing well and easier ones when I'm struggling","I want a personalized study path that adapts to my learning speed","I want the app to identify my weak areas and focus my study time there"],"best_for":["Learners with varying baseline knowledge who need differentiated difficulty levels","Students preparing for adaptive exams (CAT-style tests) who benefit from difficulty calibration","Self-paced learners who want minimal friction in finding the right difficulty level"],"limitations":["Requires significant performance data before adaptation becomes effective — cold-start problem for new users or new cards","Difficulty inference is heuristic-based and may misclassify cards (e.g., a card that looks easy but requires deep understanding)","No explicit difficulty tagging by content creators — relies entirely on user performance, which may be noisy","Limited customization in free tier — users cannot manually adjust card difficulty or learning path"],"requires":["Performance tracking database (response accuracy, response time, confidence ratings per card per user)","Difficulty estimation algorithm (e.g., IRT-based or simple performance thresholds)","User session tracking (to correlate performance with learning context)"],"input_types":["user response (correct/incorrect)","response metadata (time taken, confidence rating if available)","card performance history"],"output_types":["adjusted card difficulty level","personalized card queue (ordered by difficulty and readiness)","learning progress metrics (mastery percentage, weak areas)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_4","uri":"capability://data.processing.analysis.flashcard.set.creation.and.organization","name":"flashcard set creation and organization","description":"Provides UI and backend infrastructure for users to create, organize, and manage collections of flashcards. Supports set-level metadata (title, description, tags, subject area), card grouping (decks, folders, topics), and set sharing/publishing. Implements CRUD operations for cards and sets with validation, versioning, and conflict resolution for collaborative editing (if supported).","intents":["I want to organize my cards into multiple decks by subject or chapter","I want to create a new study set from scratch or from AI-generated cards","I want to tag and search my cards by topic or difficulty"],"best_for":["Students managing multiple subjects or courses simultaneously","Users who want to organize AI-generated cards into logical groupings","Learners who prefer structured organization over flat card lists"],"limitations":["Free tier likely has limited customization options — may not support custom card fields, templates, or advanced metadata","No collaborative features mentioned — cannot share sets with classmates or instructors for group study","No class management or progress tracking for educators — limits utility for classroom use","Set organization is flat or shallow — no support for complex hierarchies or cross-cutting tags"],"requires":["User account with persistent storage","Database schema for sets, cards, and metadata","UI for CRUD operations (create, read, update, delete)"],"input_types":["set metadata (title, description, tags)","card data (question, answer, optional metadata)","organizational structure (deck/folder assignments)"],"output_types":["set objects with metadata","card collections (organized by deck/folder)","set URLs or IDs for sharing"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_5","uri":"capability://automation.workflow.study.session.ui.and.interactive.card.review","name":"study session ui and interactive card review","description":"Provides a user-facing study interface where learners review flashcards, input responses (reveal answer, mark correct/incorrect), and receive feedback. Implements card presentation logic (front/back reveal, timing, response capture), progress tracking within a session (cards completed, accuracy), and optional gamification elements (streaks, points, difficulty badges). May include multiple study modes (flashcard flip, multiple choice, typing, matching).","intents":["I want to study my cards with a clean, distraction-free interface","I want to see my progress during a study session (cards completed, accuracy rate)","I want different study modes (flashcard flip, multiple choice, typing) to keep learning fresh"],"best_for":["Students who prefer interactive, gamified learning experiences","Learners who benefit from immediate feedback and progress visualization","Users studying on mobile devices who need responsive, touch-friendly interfaces"],"limitations":["Free tier may have limited study modes — likely only basic flashcard flip, not multiple choice or typing","No offline mode mentioned — requires internet connection for spaced repetition scheduling and progress sync","Study session data may not be exportable — users cannot analyze their own learning patterns","Gamification elements (streaks, points) may create false sense of progress without deep learning"],"requires":["Web or mobile client (browser-based or native app)","Real-time session state management (current card, responses, timer)","Backend API for submitting responses and syncing progress"],"input_types":["user response (button click for correct/incorrect, text input for typing mode, multiple choice selection)","session context (current card, study mode, time spent)"],"output_types":["rendered card (question, optional answer reveal)","session progress (cards completed, accuracy, time spent)","feedback (correct/incorrect, explanation if available)"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_6","uri":"capability://automation.workflow.free.tier.with.limited.feature.access","name":"free tier with limited feature access","description":"Implements a freemium business model where core functionality (AI card generation, basic study, spaced repetition) is available at no cost, while premium features (advanced customization, analytics, collaboration) are behind a paywall. Uses account-based access control to enforce feature limits (e.g., max cards per set, max sets, no advanced customization) and upsell premium tiers.","intents":["I want to try the app without paying to see if it works for my learning style","I want basic flashcard functionality without premium features","I want to access the app on multiple devices with a free account"],"best_for":["Students with limited budgets who need functional study tools","Casual learners who don't need advanced features","Users evaluating the app before committing to a paid plan"],"limitations":["Free tier has limited customization — no advanced card templates, custom fields, or difficulty tagging","No collaboration or class management features — limits utility for group study or classroom use","Likely has card/set limits or feature throttling to encourage upgrade (e.g., max 100 cards per set, no advanced analytics)","May include ads or upsell prompts that distract from learning"],"requires":["Account creation (email or social login)","Feature flag or entitlement system to enforce tier-based access control"],"input_types":["user tier/subscription status"],"output_types":["feature access (enabled/disabled per feature)","UI elements (upsell prompts, feature restrictions)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_7","uri":"capability://data.processing.analysis.card.performance.analytics.and.learning.insights","name":"card performance analytics and learning insights","description":"Tracks and visualizes learner performance metrics across cards and study sessions, including accuracy rates, review frequency, time spent, and mastery levels. Generates insights (weak areas, learning trends, predicted retention) to help users understand their learning progress and identify gaps. May include heatmaps, progress charts, or predictive analytics (e.g., 'you'll forget this card in 3 days if you don't review').","intents":["I want to see which topics I'm struggling with so I can focus my study time","I want to track my progress over time and see if I'm improving","I want insights into my learning patterns (e.g., best time of day to study, optimal review frequency)"],"best_for":["Data-driven learners who want to optimize their study approach","Students preparing for high-stakes exams who need detailed progress tracking","Educators (if supported) who want to monitor student progress and identify struggling learners"],"limitations":["Analytics likely limited or unavailable in free tier — premium feature to encourage upgrade","Insights are based on aggregate performance data and may not account for external factors (sleep, stress, prior knowledge)","Predictive analytics (e.g., retention predictions) are heuristic-based and may be inaccurate","No export of analytics data — users cannot analyze or share their learning data with tutors or instructors"],"requires":["Performance tracking database (accuracy, time spent, review history per card per user)","Analytics engine (aggregation, trend analysis, anomaly detection)","Visualization library (charts, heatmaps, progress bars)"],"input_types":["performance data (accuracy, time spent, review history)","card metadata (difficulty, topic, creation date)"],"output_types":["performance metrics (accuracy rate, mastery percentage, review frequency)","visualizations (charts, heatmaps, progress bars)","insights (weak areas, learning trends, predictions)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_omnisets__cap_8","uri":"capability://automation.workflow.cross.device.synchronization.and.account.management","name":"cross-device synchronization and account management","description":"Syncs user data (cards, sets, progress, preferences) across multiple devices (web, iOS, Android) using a centralized backend. Implements account authentication (email/password, social login), session management, and conflict resolution for concurrent edits. Ensures consistent state across devices and allows seamless switching between study on phone, tablet, and desktop.","intents":["I want to study on my phone during my commute and continue on my laptop at home","I want my progress to sync automatically across all my devices","I want to access my flashcards from anywhere without manually uploading files"],"best_for":["Mobile-first learners who study on multiple devices","Students who want flexibility to study anywhere (commute, library, home)","Users who value seamless experience across platforms"],"limitations":["Requires internet connection for sync — no offline mode mentioned, so users cannot study without connectivity","Sync conflicts may occur if user edits cards on multiple devices simultaneously — conflict resolution strategy unclear","Account-based sync means user data is stored on company servers — privacy/data ownership concerns","No local backup or export option mentioned — users cannot easily migrate to other platforms"],"requires":["Backend API for data sync (REST or GraphQL)","Authentication system (OAuth, email/password, session tokens)","Database for user accounts and data","Client-side sync logic (conflict detection, merge strategies, offline queue)"],"input_types":["user authentication credentials","device identifier (for sync tracking)","data changes (card edits, progress updates)"],"output_types":["synced user data (cards, sets, progress)","session tokens (for authentication)","sync status (last sync time, pending changes)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Text input (minimum ~100 characters for meaningful extraction)","Active internet connection for LLM API calls","Account creation (free tier available)","File upload capability (browser-based or API endpoint)","PDF/DOCX parsing library (e.g., PyPDF2, python-docx, or equivalent)","HTTP client for URL fetching and parsing (e.g., BeautifulSoup, Selenium for JS-heavy sites)","Text normalization pipeline (whitespace handling, encoding detection)","User account with persistent storage (database to track review history)","Client-side or server-side timer/scheduler (cron job or client-initiated polling)","Card metadata storage (difficulty factor, interval, ease factor, last review date)"],"failure_modes":["AI-generated cards frequently miss contextual nuance and interdependencies between concepts, creating superficial Q&A pairs that don't promote deep understanding","No semantic validation of generated cards — may produce factually incorrect or misleading question-answer pairs without human review","Struggles with domain-specific terminology and abstract concepts that require domain expertise to frame properly","Cannot infer learner's prior knowledge level, so generated difficulty may be mismatched to target audience","PDF extraction quality degrades with scanned images, complex layouts, or embedded graphics — may lose context or misparse tables","URL scraping may fail on JavaScript-heavy sites, paywalled content, or sites with aggressive bot detection","No support for audio or video input (mentioned as 'multi-format' but likely limited to text-based formats)","Large documents (>10MB or >50,000 words) may hit API token limits or timeout","Algorithm assumes consistent user engagement — if user skips reviews for days, the schedule degrades and cards may be forgotten","No customization of spacing parameters in free tier — users cannot adjust aggressiveness of review intervals","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:31.859Z","last_scraped_at":"2026-04-05T13:23:42.560Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=omnisets","compare_url":"https://unfragile.ai/compare?artifact=omnisets"}},"signature":"tk4zZRRLG6ueGacGZbfWHM5XqU7U4QU6R5wHhh93KLbjeNNmjZu6Oknb8yhFFLuEsFWs0ZBYX/kqAaz2+TA0BA==","signedAt":"2026-06-22T02:47:22.970Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/omnisets","artifact":"https://unfragile.ai/omnisets","verify":"https://unfragile.ai/api/v1/verify?slug=omnisets","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}