{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_r1-by-rabbit","slug":"r1-by-rabbit","name":"r1 by rabbit","type":"product","url":"https://www.rabbit.tech","page_url":"https://unfragile.ai/r1-by-rabbit","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_r1-by-rabbit__cap_0","uri":"capability://text.generation.language.multilingual.real.time.translation.with.contextual.awareness","name":"multilingual real-time translation with contextual awareness","description":"Translates text and speech between multiple languages with context-aware processing that understands domain-specific terminology and colloquialisms. The system likely uses a combination of on-device language models optimized for the r1's hardware constraints and cloud-based translation APIs for complex linguistic patterns, enabling fast turnaround for common phrases while maintaining accuracy for specialized vocabulary.","intents":["I need to quickly translate a phrase while traveling without opening my phone","I want to understand what someone is saying in a foreign language in real-time","I need accurate translation of technical or domain-specific terms while working internationally"],"best_for":["Frequent international travelers and business professionals","Expat communities and multilingual teams","Users prioritizing quick assistance over deep analysis"],"limitations":["Small screen size limits display of long translated passages or side-by-side comparisons","On-device processing constraints may reduce accuracy for rare language pairs or highly specialized terminology","Real-time translation quality depends on network connectivity for cloud fallback"],"requires":["Active internet connection (WiFi or cellular)","Language packs downloaded for offline translation (estimated 50-200MB per language pair)","Device storage capacity of at least 4GB for multilingual support"],"input_types":["text input via keyboard or voice","speech input for real-time audio translation","image text (OCR) for sign/document translation"],"output_types":["translated text","synthesized speech output","phonetic pronunciation guides"],"categories":["text-generation-language","localization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_r1-by-rabbit__cap_1","uri":"capability://planning.reasoning.contextual.task.assistance.with.device.aware.recommendations","name":"contextual task assistance with device-aware recommendations","description":"Provides intelligent suggestions and assistance based on the user's current context, location, and activity patterns. The system maintains a lightweight context model that tracks user behavior, time of day, location signals, and recent interactions to surface relevant help without explicit requests. This likely uses on-device telemetry collection with privacy-preserving aggregation rather than cloud-based tracking.","intents":["I want AI suggestions tailored to what I'm currently doing without asking","I need help with a task but don't want to explicitly describe my situation","I want location-aware recommendations (restaurants, directions, local info) without opening my phone"],"best_for":["Users who value proactive assistance and ambient intelligence","Professionals in fast-paced environments needing quick context switches","Privacy-conscious users who prefer on-device context tracking over cloud profiling"],"limitations":["Context inference accuracy limited by small screen preventing detailed user input or confirmation","On-device processing constraints limit the sophistication of behavioral pattern recognition","Privacy model may not capture full context if user opts out of location/activity tracking","No persistent user profile across devices — context resets if user switches to different hardware"],"requires":["Location services enabled (GPS or network-based geolocation)","Bluetooth connectivity for device pairing and activity detection","User consent for on-device telemetry collection and behavioral tracking"],"input_types":["location data","time/calendar information","recent interaction history","device sensor data (accelerometer for activity detection)"],"output_types":["contextual suggestions","proactive alerts","recommended actions","structured recommendations (JSON or similar)"],"categories":["planning-reasoning","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_r1-by-rabbit__cap_2","uri":"capability://tool.use.integration.smart.connectivity.and.device.integration.via.wireless.protocols","name":"smart connectivity and device integration via wireless protocols","description":"Enables seamless connection and data exchange with smartphones, smartwatches, and IoT devices through Bluetooth, WiFi, and proprietary wireless protocols. The r1 acts as a companion device that can relay information from connected devices, control smart home systems, and synchronize data without requiring manual pairing or complex configuration. This likely uses a device abstraction layer that normalizes different wireless protocols into a unified interface.","intents":["I want my AI assistant to control my smart home devices without pulling out my phone","I need to relay information from my smartwatch to my AI device for processing","I want seamless data sync between my r1 and my smartphone without manual intervention"],"best_for":["Smart home enthusiasts and IoT device owners","Users with multiple connected devices seeking unified control","Professionals wanting to reduce smartphone dependency while maintaining connectivity"],"limitations":["Limited to devices using standard protocols (Bluetooth, WiFi, Zigbee) — proprietary smart home ecosystems may require additional bridges","Small screen prevents complex device configuration or status monitoring workflows","Latency for device control depends on wireless protocol and network congestion","No built-in support for legacy devices without wireless connectivity"],"requires":["Bluetooth 5.0+ or WiFi 6 capable devices for pairing","Compatible smart home hub or bridge (if controlling non-standard devices)","Device firmware that supports standard wireless protocols","Network connectivity (WiFi or cellular) for cloud-based device control"],"input_types":["device discovery signals","wireless protocol handshakes","device status queries","user voice commands for device control"],"output_types":["device control commands","status updates from connected devices","aggregated device information","automation triggers"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_r1-by-rabbit__cap_3","uri":"capability://text.generation.language.voice.based.conversational.interface.with.natural.language.understanding","name":"voice-based conversational interface with natural language understanding","description":"Processes natural language voice input and generates contextually appropriate spoken responses using on-device speech recognition and text-to-speech synthesis. The system likely combines a lightweight speech-to-text model optimized for the r1's processor with a language understanding component that maps user utterances to actionable intents. Voice interaction is the primary interface, designed for quick hands-free operation without requiring screen interaction.","intents":["I want to ask my AI assistant a question without typing or looking at a screen","I need hands-free operation while traveling or multitasking","I want natural conversation with my device without learning command syntax"],"best_for":["Users in mobile or hands-free scenarios (driving, walking, commuting)","Non-technical users preferring natural language over UI navigation","Accessibility-focused users who benefit from voice-first interfaces"],"limitations":["Speech recognition accuracy degrades in noisy environments (public transit, crowded spaces)","On-device speech processing may not support all accents or dialects equally well","No visual feedback for complex queries — users must rely on spoken responses","Latency for speech-to-text processing (estimated 1-3 seconds) may feel slow for rapid back-and-forth conversation"],"requires":["Microphone with noise cancellation (built into r1 hardware)","Speaker or audio output capability","Language packs for supported languages (estimated 50-100MB per language)","Sufficient on-device processing power for real-time speech recognition"],"input_types":["voice/audio input","ambient sound (for context detection)"],"output_types":["synthesized speech","text transcription of user input","spoken responses"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_r1-by-rabbit__cap_4","uri":"capability://automation.workflow.portable.battery.efficient.ai.inference.with.hardware.acceleration","name":"portable battery-efficient ai inference with hardware acceleration","description":"Executes language model inference on dedicated mobile hardware with power-efficient processors and optional accelerators (NPU, GPU) designed for extended battery life. The system uses model quantization, pruning, and knowledge distillation to reduce model size and computational requirements while maintaining acceptable quality. This enables continuous AI assistance without draining the device battery, a key differentiator from smartphone-based AI.","intents":["I want AI assistance throughout the day without worrying about battery drain","I need a dedicated AI device that doesn't compete with my phone's battery","I want always-on AI capabilities without thermal throttling or performance degradation"],"best_for":["Users who use AI assistants frequently throughout the day","Professionals in battery-constrained environments (field work, travel)","Users frustrated with smartphone battery drain from AI apps"],"limitations":["Model size and capability trade-offs — smaller quantized models have reduced reasoning ability compared to full-precision versions","Inference latency varies based on query complexity and available hardware acceleration","Battery life depends on usage patterns — continuous voice interaction drains faster than periodic text queries","No ability to run larger models or fine-tune models on-device due to hardware constraints"],"requires":["Dedicated mobile processor (likely ARM-based with NPU support)","Battery capacity of 1000-2000mAh (estimated based on pocket-sized form factor)","Thermal management system to prevent throttling during sustained use","Optimized inference runtime (likely TensorFlow Lite, ONNX Runtime, or proprietary)"],"input_types":["text queries","voice input","sensor data"],"output_types":["text responses","voice output","structured data"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_r1-by-rabbit__cap_5","uri":"capability://automation.workflow.distraction.free.focused.interface.design.with.minimal.ui.complexity","name":"distraction-free focused interface design with minimal ui complexity","description":"Presents a streamlined user interface optimized for quick interactions and minimal cognitive load, avoiding the notification overload and feature sprawl common in smartphone apps. The design philosophy prioritizes essential functionality over customization options, using a clean layout with large touch targets suitable for the small screen. This likely uses a modal or card-based UI pattern that surfaces one task at a time.","intents":["I want to use my AI assistant without getting distracted by notifications or UI clutter","I need a simple, intuitive interface that doesn't require learning complex menu structures","I want quick access to core features without scrolling through dozens of options"],"best_for":["Users overwhelmed by smartphone app complexity","Professionals seeking focused work environments","Non-technical users who prefer simplicity over customization"],"limitations":["Limited customization options — users cannot rearrange UI elements or create custom shortcuts","Small screen size restricts the amount of information displayed simultaneously","No advanced features or power-user options for users who need them","Single-task focus may feel restrictive for users juggling multiple concurrent queries"],"requires":["Touch screen with minimum 3-4 inch diagonal (estimated based on pocket-sized form factor)","Gesture recognition support for common interactions (swipe, tap, long-press)","Sufficient RAM for smooth UI transitions (estimated 2-4GB)"],"input_types":["touch input","voice commands","physical buttons"],"output_types":["visual UI elements","text and icons","haptic feedback"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_r1-by-rabbit__cap_6","uri":"capability://planning.reasoning.offline.capability.with.local.language.model.inference","name":"offline capability with local language model inference","description":"Maintains core AI functionality without internet connectivity by running lightweight language models directly on the device. The system pre-downloads essential language models and knowledge bases to enable basic question-answering, translation, and task assistance even when WiFi and cellular connections are unavailable. This likely uses a tiered model strategy where simple queries run fully offline while complex requests gracefully degrade or queue for cloud processing when connectivity returns.","intents":["I want AI assistance in areas without internet coverage (flights, remote locations, poor connectivity)","I need privacy assurance that my queries don't leave my device","I want to use my AI assistant without relying on cloud infrastructure"],"best_for":["Frequent travelers in areas with unreliable connectivity","Privacy-conscious users concerned about data transmission","Users in regions with limited or expensive internet access"],"limitations":["Offline models are smaller and less capable than cloud-based versions, reducing reasoning ability and knowledge breadth","Device storage constraints limit the number of languages and knowledge domains available offline","No real-time information access (news, weather, current events) without internet","Offline translation quality may be lower than cloud-based translation services"],"requires":["Sufficient on-device storage for language models (estimated 500MB-2GB depending on model count)","Pre-downloaded language packs before traveling to areas without connectivity","Periodic sync with cloud to update offline models with new knowledge"],"input_types":["text queries","voice input","local documents"],"output_types":["text responses","voice output","local search results"],"categories":["planning-reasoning","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_r1-by-rabbit__cap_7","uri":"capability://search.retrieval.quick.access.information.retrieval.with.semantic.search","name":"quick-access information retrieval with semantic search","description":"Retrieves relevant information from a pre-indexed knowledge base using semantic search rather than keyword matching, enabling users to find answers using natural language queries without exact phrase matching. The system likely uses embedding-based retrieval with a lightweight vector database optimized for mobile hardware, allowing fast similarity search across documents, FAQs, and reference materials. Results are ranked by relevance and presented in a concise format suitable for the small screen.","intents":["I want to quickly find information without typing exact keywords or navigating menus","I need answers to common questions without waiting for cloud API responses","I want semantic search that understands my intent even if I phrase it differently"],"best_for":["Users seeking quick reference information while on-the-go","Professionals needing instant access to domain-specific knowledge","Users in low-connectivity scenarios who need offline information access"],"limitations":["Knowledge base is limited to pre-indexed content — cannot search the entire internet or real-time information","Semantic search quality depends on embedding model quality and knowledge base comprehensiveness","Small screen limits display of search results — users may need to scroll through multiple results","No ability to customize or update the knowledge base without device firmware updates"],"requires":["Pre-indexed knowledge base stored on device (estimated 100MB-500MB depending on scope)","Embedding model for semantic search (estimated 50-100MB)","Vector database engine optimized for mobile (likely FAISS or similar lightweight implementation)"],"input_types":["natural language queries","voice input","partial or fuzzy queries"],"output_types":["ranked search results","snippets or summaries","source references"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Active internet connection (WiFi or cellular)","Language packs downloaded for offline translation (estimated 50-200MB per language pair)","Device storage capacity of at least 4GB for multilingual support","Location services enabled (GPS or network-based geolocation)","Bluetooth connectivity for device pairing and activity detection","User consent for on-device telemetry collection and behavioral tracking","Bluetooth 5.0+ or WiFi 6 capable devices for pairing","Compatible smart home hub or bridge (if controlling non-standard devices)","Device firmware that supports standard wireless protocols","Network connectivity (WiFi or cellular) for cloud-based device control"],"failure_modes":["Small screen size limits display of long translated passages or side-by-side comparisons","On-device processing constraints may reduce accuracy for rare language pairs or highly specialized terminology","Real-time translation quality depends on network connectivity for cloud fallback","Context inference accuracy limited by small screen preventing detailed user input or confirmation","On-device processing constraints limit the sophistication of behavioral pattern recognition","Privacy model may not capture full context if user opts out of location/activity tracking","No persistent user profile across devices — context resets if user switches to different hardware","Limited to devices using standard protocols (Bluetooth, WiFi, Zigbee) — proprietary smart home ecosystems may require additional bridges","Small screen prevents complex device configuration or status monitoring workflows","Latency for device control depends on wireless protocol and network congestion","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":"2026-05-24T12:16:32.438Z","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=r1-by-rabbit","compare_url":"https://unfragile.ai/compare?artifact=r1-by-rabbit"}},"signature":"tovbtJa+fMHhB6cwdXkAqynnbMuL21agBqam6Tob7VmhyTohliMEVDT9vseOG81cEjuJrM0pwb6SFKispw4JDQ==","signedAt":"2026-06-21T05:09:13.853Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/r1-by-rabbit","artifact":"https://unfragile.ai/r1-by-rabbit","verify":"https://unfragile.ai/api/v1/verify?slug=r1-by-rabbit","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"}}