{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_questionaid","slug":"questionaid","name":"QuestionAid","type":"product","url":"https://question-aid.com","page_url":"https://unfragile.ai/questionaid","categories":["app-builders"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_questionaid__cap_0","uri":"capability://text.generation.language.content.to.question.generation.with.llm.based.extraction","name":"content-to-question generation with llm-based extraction","description":"Accepts educational content (text, documents, or course materials) and uses large language models to automatically generate assessment questions across multiple formats. The system likely employs prompt engineering or fine-tuned models to extract key concepts and generate pedagogically-structured questions with configurable difficulty levels, then structures outputs as question objects with metadata (difficulty, question type, correct answer, distractors).","intents":["I want to quickly generate 50 multiple-choice questions from my lecture notes without manually writing each one","I need to create questions at varying difficulty levels (Bloom's taxonomy) from course content automatically","I want to generate diverse question types (MC, T/F, short answer) from the same source material in one batch"],"best_for":["K-12 and higher education instructors managing multiple courses with tight timelines","Curriculum designers building large question banks across subjects","Educators who can tolerate 30-50% manual refinement of AI outputs"],"limitations":["AI-generated questions frequently contain factual errors, ambiguous distractors, or misaligned learning objectives requiring substantial manual review","Quality degrades significantly with poorly-structured or domain-specific input content (e.g., technical jargon, specialized vocabulary)","No built-in validation against learning outcomes or curriculum standards — requires external alignment checking","Difficulty level calibration is approximate and may not match intended Bloom's taxonomy levels"],"requires":["Educational content in text, PDF, or document format","API access to LLM provider (likely OpenAI GPT or similar)","Minimum 500 words of source material for meaningful question generation"],"input_types":["text","PDF documents","course syllabi","lecture transcripts"],"output_types":["structured question objects (JSON/XML)","question metadata (difficulty, type, learning objective)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_1","uri":"capability://tool.use.integration.moodle.direct.export.with.format.mapping","name":"moodle direct export with format mapping","description":"Translates generated question objects into Moodle-compatible XML/GIFT format and pushes them directly into Moodle instances via API or file upload, eliminating manual import workflows. The system maintains question metadata (difficulty, tags, learning objectives) during format conversion and handles Moodle-specific constraints (question bank organization, category hierarchies, question type limitations).","intents":["I want to export 100 generated questions directly into my Moodle course without manually importing each one","I need to organize questions into Moodle question banks by topic/difficulty automatically","I want to preserve question metadata (learning objectives, difficulty) when pushing to Moodle"],"best_for":["Moodle administrators managing institutional question banks","Instructors using Moodle as their primary LMS","Teams needing to bulk-populate Moodle courses across multiple sections"],"limitations":["Moodle API access requires administrator-level permissions; not all Moodle instances expose the necessary APIs","Question type support limited to Moodle's native types (MC, T/F, short answer, essay, matching) — custom question types not supported","No bidirectional sync — changes made in Moodle after export are not reflected back in QuestionAid","Requires Moodle 3.9+ for full API compatibility; older versions may require manual GIFT file import"],"requires":["Active Moodle instance (3.9 or later)","Moodle API token or admin credentials","Network access to Moodle server","Generated questions in QuestionAid format"],"input_types":["question objects from generation pipeline","question metadata (difficulty, tags, learning objectives)"],"output_types":["Moodle XML format","GIFT format","direct Moodle question bank entries"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_2","uri":"capability://tool.use.integration.kahoot.quiz.export.with.game.format.adaptation","name":"kahoot quiz export with game-format adaptation","description":"Converts generated questions into Kahoot-compatible format (JSON or Kahoot API calls) with automatic adaptation for game-based learning constraints: enforces 4-option multiple choice, applies time limits, assigns point values, and structures questions for real-time classroom delivery. The system maps question difficulty to Kahoot point multipliers and handles Kahoot's specific metadata requirements (quiz name, description, cover image, player limits).","intents":["I want to turn my generated questions into a Kahoot game for classroom engagement without manually recreating each question","I need to export questions to Kahoot with appropriate difficulty-based point values and time limits","I want to create multiple Kahoot quizzes from different content topics in bulk"],"best_for":["K-12 educators using Kahoot for formative assessment and classroom engagement","Teachers wanting to gamify assessment without manually recreating questions","Instructors managing multiple Kahoot quizzes across grade levels or subjects"],"limitations":["Kahoot enforces 4-option multiple choice only — true/false and short answer questions must be converted or discarded, reducing question type diversity","No support for Kahoot's premium features (team mode, challenge mode) — exports to standard quiz format only","Time limits and point values are auto-assigned based on difficulty heuristics; educators cannot customize per-question timing","Kahoot API rate limits may throttle bulk exports of 100+ questions; requires staggered uploads","No bidirectional sync — Kahoot quiz edits are not reflected back in QuestionAid"],"requires":["Kahoot account with API access (requires Kahoot+ or institutional plan)","Kahoot API credentials","Generated questions in QuestionAid format","Questions must be convertible to 4-option multiple choice format"],"input_types":["question objects from generation pipeline","question metadata (difficulty, learning objectives)"],"output_types":["Kahoot JSON format","Kahoot quiz objects","playable Kahoot quiz URLs"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_3","uri":"capability://data.processing.analysis.difficulty.level.calibration.and.customization","name":"difficulty-level calibration and customization","description":"Allows educators to specify target difficulty levels (e.g., Bloom's taxonomy levels: remember, understand, apply, analyze, evaluate, create) and generates questions aligned to those cognitive levels. The system uses prompt engineering or classification models to ensure generated questions match specified difficulty, then allows post-generation adjustment of difficulty ratings before export to LMS platforms.","intents":["I want to generate questions that test higher-order thinking (analysis, evaluation) rather than just recall","I need a mix of easy, medium, and hard questions for a formative assessment","I want to ensure my generated questions align with Bloom's taxonomy levels for my course"],"best_for":["Educators designing assessments aligned to learning outcomes","Curriculum designers building scaffolded question banks","Instructors wanting to differentiate assessment difficulty by student level"],"limitations":["Difficulty calibration is heuristic-based and approximate — no guarantee that 'hard' questions actually test higher-order thinking vs. just using complex vocabulary","Bloom's taxonomy mapping is not validated against actual student performance data","Difficulty levels are relative to content domain — a 'hard' question in elementary math may be trivial in advanced calculus","No feedback mechanism to refine difficulty calibration based on actual student performance"],"requires":["Source content with clear learning objectives","Specification of target difficulty levels (e.g., Bloom's levels)","Generated questions in QuestionAid format"],"input_types":["difficulty level specification (Bloom's taxonomy or custom scale)","question objects from generation pipeline"],"output_types":["questions tagged with difficulty level","difficulty-adjusted question metadata"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_4","uri":"capability://text.generation.language.question.type.diversification.and.format.control","name":"question-type diversification and format control","description":"Supports generation of multiple question formats (multiple choice, true/false, short answer, matching) from the same source content and allows educators to specify the distribution of question types in bulk exports. The system applies format-specific generation logic: MC questions include plausible distractors, T/F questions avoid ambiguity, short answer questions define acceptable answer variations, and matching questions pair related concepts.","intents":["I want to generate a mix of question types (MC, T/F, short answer) from my lecture notes in one batch","I need to control the ratio of question types in my export (e.g., 60% MC, 30% T/F, 10% short answer)","I want to ensure short answer questions have clear rubrics or acceptable answer variations defined"],"best_for":["Educators designing comprehensive assessments with varied question types","Instructors wanting to reduce assessment fatigue by mixing question formats","Teachers needing to balance objective and subjective assessment items"],"limitations":["Short answer and matching questions require more manual review than MC/T/F because AI-generated acceptable answers may miss valid student responses","Matching questions are limited to small concept sets (typically 4-8 pairs) due to cognitive load constraints","True/false questions often suffer from ambiguity or trick-question phrasing when auto-generated","Question type distribution is specified upfront; no dynamic adjustment based on content analysis","Some LMS platforms (e.g., older Moodle versions) don't support all question types, requiring fallback conversion"],"requires":["Source content with diverse concepts suitable for different question types","Specification of desired question type distribution","Generated questions in QuestionAid format"],"input_types":["question type preferences (MC, T/F, short answer, matching)","question type distribution ratios","source content"],"output_types":["questions in specified formats","format-specific metadata (distractors for MC, acceptable answers for short answer)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_5","uri":"capability://automation.workflow.batch.question.generation.with.progress.tracking","name":"batch question generation with progress tracking","description":"Processes large question batches (50-500+ questions) asynchronously with progress tracking, error reporting, and partial success handling. The system queues generation requests, monitors LLM API usage and rate limits, retries failed generations, and provides educators with real-time or post-completion reports on generation success rates, quality metrics, and any questions requiring manual review.","intents":["I want to generate 200 questions from my course materials and track progress without waiting for completion","I need to know which generated questions failed or require manual review before exporting to Moodle","I want to monitor API usage and costs when generating large question batches"],"best_for":["Educators bulk-populating question banks for multiple courses","Curriculum teams generating questions at scale","Institutions managing question generation across many instructors"],"limitations":["Asynchronous processing adds latency (5-30 minutes for 100+ questions) vs. synchronous generation","Error handling is opaque — educators may not know why specific questions failed to generate","No prioritization or cancellation of in-flight batch jobs — all requests process sequentially","Progress tracking may not be real-time; educators may need to refresh or poll for updates","Large batches (500+) may hit LLM API rate limits or quota restrictions, causing partial failures"],"requires":["Source content for all questions in batch","Sufficient API quota for LLM provider (OpenAI, Anthropic, etc.)","Network connectivity for asynchronous job tracking","Batch size typically limited to 500-1000 questions per job"],"input_types":["batch of source content items","batch generation parameters (question count, types, difficulty)"],"output_types":["progress reports (% complete, success rate)","error logs (failed generations, reasons)","generated question batches","quality metrics (estimated accuracy, ambiguity flags)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_6","uri":"capability://safety.moderation.content.aware.question.validation.and.ambiguity.detection","name":"content-aware question validation and ambiguity detection","description":"Analyzes generated questions against source content to detect factual errors, ambiguous distractors, and misaligned learning objectives. The system uses semantic similarity matching, fact-checking heuristics, and pedagogical rules to flag questions requiring manual review before export. Validation includes checks for: answer key correctness, distractor plausibility, question clarity, and alignment with stated learning outcomes.","intents":["I want to automatically flag generated questions that contain factual errors or ambiguous answers before exporting to Moodle","I need to identify questions where the correct answer is not clearly supported by the source content","I want to catch questions with implausible or misleading distractors before students see them"],"best_for":["Educators wanting to reduce manual review burden for AI-generated questions","Quality assurance teams validating question banks at scale","Institutions with strict assessment quality standards"],"limitations":["Validation is heuristic-based and imperfect — may miss subtle factual errors or flag correct questions as ambiguous","Requires source content to be available for comparison; validation fails if content is missing or poorly structured","Cannot detect domain-specific errors that require subject matter expertise (e.g., a plausible-sounding but incorrect physics explanation)","Ambiguity detection is approximate — may flag legitimate questions as ambiguous due to natural language variability","No feedback loop to improve validation rules based on educator corrections"],"requires":["Source content in structured or semi-structured format","Generated questions with answer keys and distractors","Access to semantic similarity models (embeddings) for content matching"],"input_types":["generated questions with answer keys","source content","learning objectives (optional)"],"output_types":["validation reports (pass/fail per question)","ambiguity flags with severity levels","factual error alerts","alignment warnings"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_7","uri":"capability://memory.knowledge.learning.objective.alignment.mapping","name":"learning-objective alignment mapping","description":"Maps generated questions to specified learning objectives (e.g., BLOOM's taxonomy, state standards, course outcomes) and allows educators to filter, organize, and export questions by learning objective. The system uses semantic matching to align questions with objectives, then provides visibility into which objectives are well-covered and which need additional questions.","intents":["I want to ensure my generated questions cover all stated learning objectives for my course","I need to identify which learning objectives have insufficient question coverage","I want to export questions organized by learning objective for curriculum mapping"],"best_for":["Educators designing standards-aligned assessments","Curriculum teams mapping questions to learning outcomes","Institutions requiring learning objective alignment documentation"],"limitations":["Objective alignment is semantic-based and approximate — may misalign questions with objectives due to natural language variability","Requires explicit learning objectives to be provided upfront; no automatic objective extraction from content","Coverage analysis is quantitative (# questions per objective) but not qualitative (question quality per objective)","No validation that question difficulty matches objective cognitive level (e.g., 'apply' objective should have application-level questions)","Alignment mapping is one-directional (questions → objectives); no reverse mapping to identify gaps"],"requires":["Explicit learning objectives (Bloom's taxonomy, state standards, course outcomes)","Generated questions with content context","Semantic similarity models for objective-question matching"],"input_types":["learning objectives (text descriptions)","generated questions","source content (optional, for context)"],"output_types":["objective-question mappings","coverage reports (# questions per objective)","gap analysis (under-covered objectives)","questions organized by objective"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_questionaid__cap_8","uri":"capability://memory.knowledge.question.bank.organization.and.tagging","name":"question-bank organization and tagging","description":"Organizes generated questions into hierarchical question banks with automatic tagging by topic, difficulty, question type, learning objective, and custom educator-defined tags. The system creates or updates question bank structures in both QuestionAid and target LMS platforms (Moodle, Kahoot), maintaining tag consistency across platforms and enabling educators to search, filter, and export questions by any tag combination.","intents":["I want to organize my 500 generated questions into topic-based question banks automatically","I need to tag questions by difficulty, type, and learning objective so I can find them later","I want to export specific question subsets (e.g., 'Unit 3, hard, MC questions') without manual filtering"],"best_for":["Educators managing large question banks across multiple courses","Curriculum teams building reusable question libraries","Institutions needing searchable, well-organized question repositories"],"limitations":["Automatic tagging is heuristic-based and may misclassify questions (e.g., tagging a question as 'Unit 2' when it spans Units 2-3)","Tag hierarchies are limited by LMS platform constraints (e.g., Moodle question categories are flat, not nested)","Custom tags are not synced across platforms — tags in Moodle don't appear in Kahoot exports","No full-text search across question content; filtering is tag-based only","Large question banks (1000+) may have performance issues with filtering and export"],"requires":["Generated questions with metadata (difficulty, type, learning objective)","Topic or content structure for question organization","Access to LMS question bank APIs (Moodle, Kahoot)"],"input_types":["generated questions","topic/content structure","custom tag definitions"],"output_types":["organized question bank structure","tagged questions","question bank exports by tag"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":41,"verified":false,"data_access_risk":"high","permissions":["Educational content in text, PDF, or document format","API access to LLM provider (likely OpenAI GPT or similar)","Minimum 500 words of source material for meaningful question generation","Active Moodle instance (3.9 or later)","Moodle API token or admin credentials","Network access to Moodle server","Generated questions in QuestionAid format","Kahoot account with API access (requires Kahoot+ or institutional plan)","Kahoot API credentials","Questions must be convertible to 4-option multiple choice format"],"failure_modes":["AI-generated questions frequently contain factual errors, ambiguous distractors, or misaligned learning objectives requiring substantial manual review","Quality degrades significantly with poorly-structured or domain-specific input content (e.g., technical jargon, specialized vocabulary)","No built-in validation against learning outcomes or curriculum standards — requires external alignment checking","Difficulty level calibration is approximate and may not match intended Bloom's taxonomy levels","Moodle API access requires administrator-level permissions; not all Moodle instances expose the necessary APIs","Question type support limited to Moodle's native types (MC, T/F, short answer, essay, matching) — custom question types not supported","No bidirectional sync — changes made in Moodle after export are not reflected back in QuestionAid","Requires Moodle 3.9+ for full API compatibility; older versions may require manual GIFT file import","Kahoot enforces 4-option multiple choice only — true/false and short answer questions must be converted or discarded, reducing question type diversity","No support for Kahoot's premium features (team mode, challenge mode) — exports to standard quiz format only","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.35833333333333334,"quality":0.7200000000000001,"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":"2026-05-24T12:16:32.438Z","last_scraped_at":"2026-04-05T13:23:42.552Z","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=questionaid","compare_url":"https://unfragile.ai/compare?artifact=questionaid"}},"signature":"jcLw3XezlklxU1sMKOeSnzL4lg838TrUIqF7h76C27isEtjOGXUi4XK7SzrcECXeHr5DvF9O++IS0Uxl+sBSCA==","signedAt":"2026-06-22T18:59:26.492Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/questionaid","artifact":"https://unfragile.ai/questionaid","verify":"https://unfragile.ai/api/v1/verify?slug=questionaid","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"}}