{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_conker","slug":"conker","name":"Conker","type":"product","url":"https://conker.ai","page_url":"https://unfragile.ai/conker","categories":["app-builders"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_conker__cap_0","uri":"capability://text.generation.language.ai.generated.quiz.question.synthesis.from.learning.materials","name":"ai-generated quiz question synthesis from learning materials","description":"Accepts educational content (text, documents, or topic descriptions) and uses LLM-based generation to automatically create multiple-choice, short-answer, and fill-in-the-blank questions with corresponding answer keys. The system likely employs prompt engineering to control question difficulty, cognitive level (Bloom's taxonomy alignment), and question type distribution, reducing manual authoring time from hours to minutes while maintaining pedagogical validity.","intents":["Generate 20 quiz questions from a chapter of textbook content without manually writing each one","Create differentiated question sets at multiple difficulty levels from the same source material","Rapidly prototype quiz content for a new course unit to validate learning objectives"],"best_for":["K-12 teachers with heavy content creation workloads","Higher education instructors designing formative assessments","Curriculum designers building large question banks quickly"],"limitations":["AI-generated questions require manual review and correction; quality varies by source material clarity and LLM model capability","Cannot guarantee alignment with specific curriculum standards or learning outcomes without explicit prompt configuration","Generated answers may contain factual errors or ambiguities requiring educator verification before deployment"],"requires":["Source material in text, PDF, or document format (minimum 100 words for coherent question generation)","Active internet connection for LLM API calls","Educator account with quiz creation permissions"],"input_types":["plain text","PDF documents","topic descriptions","learning objectives"],"output_types":["structured quiz questions (JSON or platform-native format)","answer keys with explanations","difficulty metadata"],"categories":["text-generation-language","education-content-creation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_1","uri":"capability://text.generation.language.customizable.quiz.difficulty.and.cognitive.level.configuration","name":"customizable quiz difficulty and cognitive level configuration","description":"Provides educators with controls to specify question difficulty (basic, intermediate, advanced), cognitive complexity (recall, comprehension, application, analysis), and question type distribution before generation. The system maps these specifications to LLM prompt parameters and generation constraints, enabling creation of differentiated assessments for mixed-ability classrooms without generating separate quizzes manually.","intents":["Create an advanced quiz for honors students and a basic quiz for remedial learners from the same content","Ensure quiz questions target higher-order thinking skills (analysis, synthesis) rather than rote memorization","Balance question types (multiple choice, short answer, matching) according to pedagogical goals"],"best_for":["Inclusive educators serving students with varying ability levels","Teachers implementing differentiated instruction","Assessment designers aligning quizzes to specific cognitive learning objectives"],"limitations":["Difficulty calibration is heuristic-based; actual question difficulty depends on student population and may not match intended level","Cognitive level mapping relies on LLM interpretation of Bloom's taxonomy, which may not align perfectly with educator expectations","No adaptive difficulty adjustment based on student performance during quiz—difficulty is static at creation time"],"requires":["Educator familiarity with difficulty/cognitive level terminology","Quiz creation interface with difficulty configuration UI"],"input_types":["difficulty level selection (enum: basic/intermediate/advanced)","cognitive level selection (enum: recall/comprehension/application/analysis)","question type preferences (array of question types)"],"output_types":["parameterized quiz with difficulty metadata","question set filtered by cognitive level"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_10","uri":"capability://planning.reasoning.adaptive.quiz.branching.based.on.student.performance","name":"adaptive quiz branching based on student performance","description":"Dynamically adjusts quiz difficulty or question selection based on student responses in real-time, presenting easier questions to struggling students and harder questions to high performers. The system uses item response theory (IRT) or Bayesian adaptive testing algorithms to estimate student ability and select next questions with optimal difficulty. Likely stores student ability estimates and question difficulty parameters in a database for ongoing calibration.","intents":["Administer a quiz that automatically adjusts difficulty to match each student's ability level","Reduce quiz length for struggling students while maintaining assessment precision","Identify advanced students who need enrichment without boring them with easy questions"],"best_for":["Teachers implementing personalized learning with adaptive assessments","Schools using computer-adaptive testing (CAT) for placement or diagnostic assessment","Educators wanting to reduce assessment time while maintaining precision"],"limitations":["Adaptive branching requires calibrated question difficulty parameters; new or uncalibrated questions may not branch appropriately","Adaptive quizzes produce non-comparable scores across students (different questions taken); requires IRT-based score scaling","Branching logic is opaque to educators; difficult to predict or explain why a student received a particular question"],"requires":["Question bank with calibrated difficulty parameters (from prior administrations or expert estimation)","Minimum 20-30 questions per quiz for meaningful adaptive branching","Educator understanding of adaptive testing concepts (ability estimation, item difficulty)"],"input_types":["quiz configuration with adaptive branching enabled","question difficulty parameters (IRT difficulty, discrimination)","student responses (correctness, response time)"],"output_types":["adaptive quiz sequence (next question selected based on ability estimate)","ability estimates (theta scores in IRT framework)","comparable scores (IRT-scaled or equated across different question sets)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_2","uri":"capability://text.generation.language.accessibility.first.quiz.content.generation.with.alt.text.and.screen.reader.optimization","name":"accessibility-first quiz content generation with alt text and screen reader optimization","description":"Automatically generates alternative text for images, optimizes question formatting for screen readers, ensures color contrast compliance, and produces adjustable text size variants during quiz creation. The system integrates accessibility checks into the generation pipeline (not as post-processing), producing WCAG 2.1 AA-compliant content by default. Likely uses accessibility metadata standards (ARIA labels, semantic HTML) and image description LLM models to generate contextually appropriate alt text.","intents":["Create quizzes that are immediately accessible to students using screen readers without manual remediation","Generate descriptive alt text for images in quiz questions automatically","Ensure quiz interface meets WCAG accessibility standards for students with visual or motor impairments"],"best_for":["Inclusive educators serving students with disabilities","Schools with legal/compliance requirements for accessible digital content (ADA, Section 508)","Teachers in districts with high populations of students using assistive technology"],"limitations":["Auto-generated alt text quality depends on image complexity; highly technical or abstract images may require manual refinement","Accessibility compliance is limited to platform-controlled elements; third-party integrations or embedded content may not inherit accessibility features","Screen reader optimization is platform-specific; accessibility may degrade if quiz is exported or embedded in non-compliant LMS"],"requires":["Quizzes created within Conker platform (not imported from inaccessible sources)","Student devices with screen reader software (NVDA, JAWS, VoiceOver) for full accessibility benefit"],"input_types":["quiz questions with images","text content","question formatting preferences"],"output_types":["WCAG 2.1 AA-compliant HTML/web content","alt text descriptions","semantic markup with ARIA labels","adjustable text size variants"],"categories":["text-generation-language","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_3","uri":"capability://automation.workflow.quiz.deployment.and.real.time.student.response.collection","name":"quiz deployment and real-time student response collection","description":"Hosts quizzes on Conker's platform and collects student responses in real-time, tracking completion status, response timing, and answer correctness. The system provides educators with live dashboards showing class-wide performance metrics, individual student progress, and question-level analytics. Likely uses WebSocket or polling for real-time updates and stores response data in a relational database with indexing for fast analytics queries.","intents":["Deploy a quiz to a class and monitor student progress in real-time during the assessment","Identify which students are struggling with specific questions while quiz is in progress","Collect detailed response data for post-assessment analysis and intervention planning"],"best_for":["Classroom teachers using quizzes for formative assessment","Educators wanting real-time visibility into student understanding","Teachers analyzing quiz performance data for instructional decisions"],"limitations":["Real-time dashboards may lag under high concurrent user load (100+ simultaneous quiz takers)","Response data is siloed within Conker platform; limited export options for integration with external analytics tools","No built-in adaptive quiz branching—all students see same questions regardless of performance"],"requires":["Student access to Conker platform (web browser or mobile app)","Stable internet connection for real-time response submission","Educator account with quiz deployment permissions"],"input_types":["quiz configuration (questions, answer keys, time limits)","student roster or access codes","student responses (multiple choice selections, text answers)"],"output_types":["real-time performance dashboard (JSON API or web UI)","student response logs (structured data)","class-level and individual analytics"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_4","uri":"capability://memory.knowledge.question.bank.management.and.reusable.content.organization","name":"question bank management and reusable content organization","description":"Allows educators to save generated or manually-created questions to a persistent question bank, organize questions by topic/standard/difficulty, and reuse questions across multiple quizzes. The system provides search and filtering capabilities (by keyword, difficulty, question type, learning objective) and likely uses tagging or metadata indexing to enable fast retrieval. Supports bulk operations (import/export, batch tagging) for managing large question libraries.","intents":["Build a reusable library of 500+ questions organized by unit and difficulty level","Search for questions aligned to a specific learning standard across all past quizzes","Export question bank to backup or migrate to another platform"],"best_for":["Teachers building cumulative question libraries over multiple years","Departments sharing question banks across multiple educators","Educators implementing standards-based assessment with question traceability"],"limitations":["Question bank search is limited to platform-provided metadata; no full-text semantic search across question content","No version control for questions; editing a question updates all quizzes using it retroactively","Sharing question banks across educators may require manual permission management; no built-in role-based access control"],"requires":["Educator account with question bank creation permissions","Minimum storage quota (varies by plan; freemium tier likely limited to 100-500 questions)"],"input_types":["quiz questions (from generation or manual entry)","metadata (topic, difficulty, standard, question type)","bulk import files (CSV, JSON)"],"output_types":["searchable question bank (web UI or API)","filtered question sets","bulk export (CSV, JSON, or platform format)"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_5","uri":"capability://data.processing.analysis.quiz.performance.analytics.and.learning.insights.reporting","name":"quiz performance analytics and learning insights reporting","description":"Analyzes quiz response data to generate reports showing class-wide performance trends, individual student mastery levels, question-level difficulty/discrimination metrics, and learning gap identification. The system calculates statistics (mean score, standard deviation, item difficulty, point-biserial correlation) and visualizes results in dashboards and exportable reports. Likely uses statistical analysis libraries and data aggregation queries to compute metrics from response logs.","intents":["Identify which learning objectives the class has not mastered and needs reteaching","Determine if a quiz question is too easy/hard or poorly discriminating between high/low performers","Generate a performance report for a student's parent showing mastery by learning standard"],"best_for":["Data-driven educators using assessment data for instructional decisions","Teachers implementing standards-based grading with mastery tracking","Administrators monitoring school-wide learning outcomes"],"limitations":["Analytics are limited to quiz performance; no integration with other formative assessment data (classwork, projects, observations)","Statistical calculations assume quiz questions are valid measures of learning; no built-in item analysis validation","Reports are static snapshots; no longitudinal tracking of student growth over time without manual data compilation"],"requires":["Minimum 10-15 student responses per quiz for meaningful statistical analysis","Educator familiarity with assessment terminology (difficulty index, discrimination index, mastery level)"],"input_types":["quiz response data (student answers, response times, correctness)","quiz configuration (answer keys, point values)","learning objective mappings (optional)"],"output_types":["performance dashboards (web UI with charts/tables)","statistical reports (PDF, CSV)","individual student mastery reports","question-level analytics (difficulty, discrimination)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_6","uri":"capability://tool.use.integration.lms.integration.and.single.sign.on.sso.support","name":"lms integration and single sign-on (sso) support","description":"Integrates with learning management systems (Canvas, Google Classroom, Blackboard, Schoology) via LTI (Learning Tools Interoperability) protocol or direct API connections, enabling educators to launch quizzes from within their LMS and automatically sync grades back to the gradebook. Supports SSO via OAuth 2.0 or SAML for seamless authentication without separate login. Likely uses LTI 1.3 standard for secure, standards-based integration.","intents":["Launch a Conker quiz from within Google Classroom without requiring students to log in separately","Automatically sync quiz grades to Canvas gradebook without manual entry","Embed Conker quizzes in Blackboard course content"],"best_for":["Schools using major LMS platforms (Canvas, Google Classroom, Blackboard)","Districts with SSO infrastructure (Google Workspace, Microsoft 365, Okta)","Educators wanting seamless quiz integration without context switching"],"limitations":["LMS integration coverage is limited to major platforms; smaller or proprietary LMS may not be supported","Grade sync is one-way (Conker → LMS); no automatic quiz updates if LMS gradebook is modified","SSO setup requires IT administrator configuration; not available for individual educators without institutional support"],"requires":["School/district LMS account with admin access for LTI configuration","SSO provider (Google Workspace, Microsoft 365, Okta, or other SAML/OAuth provider) for single sign-on","LMS version supporting LTI 1.3 (Canvas 2019+, Google Classroom, Blackboard Learn 3900+)"],"input_types":["LTI launch requests from LMS","OAuth/SAML authentication tokens","quiz configuration from Conker"],"output_types":["LTI launch response (quiz embedded in LMS)","grade sync payload (to LMS gradebook)","user authentication confirmation"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_7","uri":"capability://automation.workflow.mobile.responsive.quiz.interface.with.offline.support","name":"mobile-responsive quiz interface with offline support","description":"Delivers quizzes via responsive web design that adapts to mobile devices (phones, tablets) and desktop browsers, with touch-optimized controls for mobile input. May include limited offline capability (caching quiz content locally) to allow students to complete quizzes without continuous internet connectivity, with response synchronization when connection is restored. Likely uses service workers or progressive web app (PWA) patterns for offline support.","intents":["Allow students to take a quiz on their phones during class without requiring a computer lab","Enable quiz completion on a school bus or other low-connectivity environment with later sync","Ensure quiz interface is usable on tablets and small screens without horizontal scrolling"],"best_for":["Schools with BYOD (bring-your-own-device) policies","Educators in areas with unreliable internet connectivity","Students using mobile devices as primary learning tool"],"limitations":["Offline support is limited to quiz content caching; real-time features (live dashboards, teacher monitoring) require internet connection","Mobile interface may have reduced functionality compared to desktop (e.g., no image upload for short-answer questions)","Offline response data is stored locally; if device is lost/reset before sync, responses may be lost"],"requires":["Modern mobile browser (iOS Safari 12+, Android Chrome 80+) or Conker mobile app","Minimum 50MB free storage for offline quiz caching"],"input_types":["quiz configuration (questions, media, time limits)","student responses (text, multiple choice, image upload)"],"output_types":["responsive HTML/CSS/JavaScript quiz interface","cached quiz data (local storage or IndexedDB)","response payloads (synced to server when online)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_8","uri":"capability://data.processing.analysis.bulk.quiz.import.export.with.format.conversion","name":"bulk quiz import/export with format conversion","description":"Allows educators to import quizzes from external sources (CSV, QTI, Blackboard export, Quizizz export) and export Conker quizzes to standard formats for portability. The system parses source formats, maps question types and metadata to Conker's internal schema, and handles format conversion (e.g., Blackboard XML → Conker JSON). Likely uses format-specific parsers and a canonical internal representation for flexible import/export.","intents":["Migrate 200 quizzes from Quizizz to Conker without manual re-entry","Export a quiz to QTI format for use in a different LMS","Bulk import a CSV file of questions from a textbook publisher"],"best_for":["Educators migrating from competing platforms","Teachers with large question libraries in external formats","Districts standardizing on Conker and needing bulk content migration"],"limitations":["Import quality depends on source format completeness; some metadata (learning objectives, accessibility tags) may be lost in conversion","Unsupported question types (e.g., drag-and-drop, hotspot) may be converted to multiple choice or skipped during import","Export to proprietary formats (Blackboard, Canvas) may require LMS-specific configuration and may not preserve all Conker features"],"requires":["Source file in supported format (CSV, QTI, Blackboard XML, Quizizz JSON, etc.)","Educator account with import/export permissions"],"input_types":["CSV files (with question, answer, difficulty columns)","QTI XML (IMS Question and Test Interoperability standard)","Blackboard export files","Quizizz JSON export","plain text question lists"],"output_types":["Conker quiz format (JSON or platform-native)","QTI XML (for LMS portability)","CSV export (for spreadsheet editing)","PDF quiz document"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_conker__cap_9","uri":"capability://automation.workflow.collaborative.quiz.authoring.with.version.control.and.commenting","name":"collaborative quiz authoring with version control and commenting","description":"Enables multiple educators to work on the same quiz simultaneously, with real-time collaboration features (live editing, presence indicators), version history tracking, and comment threads on specific questions. The system likely uses operational transformation (OT) or conflict-free replicated data types (CRDTs) for concurrent editing, stores version history in a database, and provides rollback capability to previous versions.","intents":["Have two teachers co-author a unit quiz in real-time without overwriting each other's changes","Review a colleague's suggested edits to a question via comments before accepting changes","Revert a quiz to a previous version if an edit introduced an error"],"best_for":["Grade-level or department teams collaborating on assessments","Schools with peer review processes for quiz quality assurance","Educators building shared question banks across multiple classrooms"],"limitations":["Real-time collaboration may have latency issues under high concurrent editing (5+ simultaneous editors)","Version history is limited to platform storage; no integration with external version control (Git)","Comments are quiz-specific; no cross-quiz discussion or annotation features"],"requires":["Multiple educator accounts with quiz editing permissions","Shared quiz access (via sharing settings or team workspace)"],"input_types":["quiz edits (question text, answers, metadata changes)","comments (text annotations on questions)","version rollback requests"],"output_types":["real-time quiz state (JSON or web UI)","version history log (with timestamps and editor info)","comment threads (structured data)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":44,"verified":false,"data_access_risk":"high","permissions":["Source material in text, PDF, or document format (minimum 100 words for coherent question generation)","Active internet connection for LLM API calls","Educator account with quiz creation permissions","Educator familiarity with difficulty/cognitive level terminology","Quiz creation interface with difficulty configuration UI","Question bank with calibrated difficulty parameters (from prior administrations or expert estimation)","Minimum 20-30 questions per quiz for meaningful adaptive branching","Educator understanding of adaptive testing concepts (ability estimation, item difficulty)","Quizzes created within Conker platform (not imported from inaccessible sources)","Student devices with screen reader software (NVDA, JAWS, VoiceOver) for full accessibility benefit"],"failure_modes":["AI-generated questions require manual review and correction; quality varies by source material clarity and LLM model capability","Cannot guarantee alignment with specific curriculum standards or learning outcomes without explicit prompt configuration","Generated answers may contain factual errors or ambiguities requiring educator verification before deployment","Difficulty calibration is heuristic-based; actual question difficulty depends on student population and may not match intended level","Cognitive level mapping relies on LLM interpretation of Bloom's taxonomy, which may not align perfectly with educator expectations","No adaptive difficulty adjustment based on student performance during quiz—difficulty is static at creation time","Adaptive branching requires calibrated question difficulty parameters; new or uncalibrated questions may not branch appropriately","Adaptive quizzes produce non-comparable scores across students (different questions taken); requires IRT-based score scaling","Branching logic is opaque to educators; difficult to predict or explain why a student received a particular question","Auto-generated alt text quality depends on image complexity; highly technical or abstract images may require manual refinement","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.78,"ecosystem":0.25,"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":"2026-05-24T12:16:30.281Z","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=conker","compare_url":"https://unfragile.ai/compare?artifact=conker"}},"signature":"cI1ociMUm0yqoiKjXzHqmjYoxkjuLuiM/d4szOTkwLHLSdna5Yhn9Q8hT81lUSsjEv8eFKGxeFR8aSuOkZeICA==","signedAt":"2026-06-21T07:40:25.318Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/conker","artifact":"https://unfragile.ai/conker","verify":"https://unfragile.ai/api/v1/verify?slug=conker","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"}}