{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_good-tripper-guide","slug":"good-tripper-guide","name":"Good Tripper Guide","type":"webapp","url":"https://www.goodtripperguide.com","page_url":"https://unfragile.ai/good-tripper-guide","categories":["research-search"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_good-tripper-guide__cap_0","uri":"capability://text.generation.language.location.aware.historical.narrative.generation","name":"location-aware historical narrative generation","description":"Generates contextual historical narratives by combining geolocation data (GPS coordinates or address input) with a vector-indexed knowledge base of historical events, figures, and cultural significance. The system retrieves relevant historical facts based on spatial proximity and temporal context, then synthesizes them into readable narratives via an LLM, avoiding generic Wikipedia-style summaries by emphasizing local significance and lesser-known details tied to the specific location.","intents":["I want to understand the historical significance of the building I'm standing in front of without opening multiple browser tabs","I need rich cultural context about a neighborhood to appreciate its architecture and street layout","I want to discover lesser-known historical events connected to my current location"],"best_for":["solo travelers and backpackers exploring cities without guidebooks","history enthusiasts seeking depth beyond mainstream tourist narratives","educators designing self-guided historical walking tours"],"limitations":["AI-generated narratives occasionally oversimplify sensitive historical events (colonialism, conflict, marginalized perspectives) due to training data bias","Knowledge base coverage is uneven — well-documented Western cities have richer context than underrepresented regions","No real-time fact-checking against academic sources; relies on static training data with unknown cutoff date","Geolocation accuracy depends on device GPS precision; urban canyons and indoor locations may trigger irrelevant narratives"],"requires":["Device with GPS or browser geolocation API support","Internet connectivity for API calls to LLM and knowledge base","Modern browser (Chrome 90+, Firefox 88+, Safari 14+)","User consent for location access"],"input_types":["geolocation (latitude/longitude)","address (text string)","optional: user-provided context (e.g., 'I'm interested in architecture')"],"output_types":["narrative text (2-5 paragraphs)","structured metadata (dates, key figures, related locations)"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_good-tripper-guide__cap_1","uri":"capability://planning.reasoning.real.time.travel.recommendation.engine.with.contextual.filtering","name":"real-time travel recommendation engine with contextual filtering","description":"Synthesizes multiple real-time data streams (user location, weather conditions, local events, time of day, user preferences) to generate personalized activity recommendations that adapt dynamically as conditions change. The system uses a multi-factor ranking algorithm that weights factors like weather suitability, event availability, crowd patterns, and user interest history to surface recommendations that would be relevant RIGHT NOW rather than generic itinerary suggestions.","intents":["I have 2 hours free and it's raining — what should I do near my current location?","What's happening in this city tonight that matches my interests?","Suggest activities that avoid crowds and tourist traps based on real-time foot traffic data"],"best_for":["independent travelers making spontaneous decisions during trips","travelers with flexible itineraries who want to optimize for current conditions","budget-conscious explorers seeking free or low-cost activities"],"limitations":["Real-time event data coverage depends on local event API availability; smaller cities may have sparse event feeds","Weather-based recommendations are generic (e.g., 'indoor activities when raining') without nuanced understanding of activity-weather fit","No integration with booking systems; recommendations may point to fully-booked or closed venues without real-time availability verification","Crowd pattern data likely sourced from Google Maps or similar; accuracy varies by location and time period","User preference learning is session-based with no persistent user profiles; recommendations reset between visits"],"requires":["Real-time weather API (OpenWeatherMap, WeatherAPI, or similar)","Local events API (Eventbrite, Meetup, or city-specific event feeds)","Geolocation data (GPS or address)","Internet connectivity for real-time data fetching","Optional: user account for preference persistence"],"input_types":["geolocation (latitude/longitude)","user preferences (interests, budget, activity type)","temporal context (time of day, day of week)","environmental data (weather, local events)"],"output_types":["ranked list of activities (5-10 recommendations)","structured activity data (name, type, distance, estimated duration, cost, relevance score)","reasoning explanation (why this recommendation is timely)"],"categories":["planning-reasoning","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_good-tripper-guide__cap_2","uri":"capability://automation.workflow.free.tier.ai.access.without.authentication.barriers","name":"free-tier ai access without authentication barriers","description":"Implements a zero-friction access model where core historical narrative and recommendation features are available without account creation, login, or payment. The system likely uses rate-limiting and request throttling (rather than paywalls) to manage server costs, allowing unlimited free access for individual travelers while potentially implementing usage caps for automated or commercial scraping.","intents":["I want to use this tool immediately without creating an account or entering payment info","I need to access historical context for multiple cities during a multi-week trip without subscription friction","I want to recommend this tool to friends without worrying about paywall barriers"],"best_for":["budget-conscious solo travelers and backpackers","casual users who want to try the tool before committing","educators and tour guides recommending tools to groups"],"limitations":["Sustainability model is unclear; free access raises questions about long-term server cost coverage and development roadmap","No user data persistence without account creation; recommendations and preferences reset between sessions","Rate-limiting may throttle requests during peak travel seasons or high-traffic cities","Lack of monetization may limit feature development velocity compared to subscription-based competitors","No premium tier for power users who might pay for advanced features (offline maps, detailed itineraries, booking integration)"],"requires":["Web browser (no app installation required)","Internet connectivity","No API key, account, or payment method"],"input_types":["geolocation or address (no authentication required)"],"output_types":["historical narratives and recommendations (same as authenticated users)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_good-tripper-guide__cap_3","uri":"capability://planning.reasoning.weather.aware.activity.suitability.filtering","name":"weather-aware activity suitability filtering","description":"Filters and ranks activity recommendations based on real-time weather conditions by mapping weather states (rain, snow, extreme heat, etc.) to activity suitability scores. The system maintains a curated mapping of activity types to weather conditions (e.g., outdoor hiking unsuitable for heavy rain, museums ideal for rainy days) and adjusts recommendation rankings dynamically as weather changes, ensuring users see contextually appropriate suggestions.","intents":["I want activity suggestions that make sense for the current weather, not generic recommendations","Show me indoor activities because it's raining, but outdoor options if it clears up","Suggest activities that are actually enjoyable in this heat/cold, not just technically possible"],"best_for":["travelers in unpredictable climates or seasons","users planning activities with limited time windows","travelers unfamiliar with local climate norms"],"limitations":["Weather-activity mapping is likely rule-based and generic; doesn't account for regional climate norms (e.g., light rain in Seattle vs. rare rain in Phoenix)","No integration with activity-specific weather requirements (e.g., rock climbing requires dry conditions, but system may not know this)","Forecast accuracy depends on underlying weather API; 7+ day forecasts are unreliable for activity planning","Doesn't account for user weather tolerance or preferences (some travelers enjoy rain, others avoid it)"],"requires":["Real-time weather API with current conditions and forecast data","Curated mapping of activity types to weather suitability (maintained by product team)","Geolocation for accurate weather data"],"input_types":["activity type (e.g., 'hiking', 'museum visit', 'outdoor dining')","current weather conditions (temperature, precipitation, wind)","optional: user weather preferences"],"output_types":["suitability score (0-100) for each activity","ranked recommendations filtered by weather appropriateness","explanation of why activity is/isn't suitable for current conditions"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_good-tripper-guide__cap_4","uri":"capability://search.retrieval.local.event.discovery.and.integration","name":"local event discovery and integration","description":"Aggregates real-time event data from local event APIs (Eventbrite, Meetup, city tourism boards, venue calendars) and surfaces relevant events in activity recommendations based on user location, interests, and timing. The system filters events by relevance (matching user interests), proximity (within reasonable travel distance), and timing (happening soon or during user's stay) to surface serendipitous opportunities that wouldn't appear in static guidebooks.","intents":["What events are happening in this city tonight that match my interests?","Show me live music venues or cultural events happening this week","I want to discover local festivals or markets I wouldn't find in a guidebook"],"best_for":["travelers seeking authentic local experiences beyond tourist attractions","users with flexible schedules who can adjust plans for interesting events","travelers interested in specific event types (music, food, cultural, sports)"],"limitations":["Event data coverage is fragmented; major cities have rich event feeds while smaller cities may have sparse data","No real-time availability or capacity data; recommendations may point to sold-out or cancelled events","Event APIs have varying data quality and update frequency; some venues don't publish events digitally","No integration with booking systems; users must navigate to external sites to purchase tickets","Language barriers for non-English event listings in international cities","Spam and low-quality events may appear in feeds without curation or community validation"],"requires":["Access to multiple event APIs (Eventbrite, Meetup, local tourism APIs)","Geolocation data for proximity filtering","User interest profile (explicit or inferred from interaction history)","Real-time event data with frequent updates (ideally hourly or better)"],"input_types":["geolocation (latitude/longitude)","user interests (event types, categories)","temporal context (date range, time of day)","optional: budget constraints"],"output_types":["ranked list of events (5-15 recommendations)","structured event data (name, type, time, location, cost, description)","relevance score and reasoning"],"categories":["search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_good-tripper-guide__cap_5","uri":"capability://planning.reasoning.session.based.preference.learning.and.recommendation.personalization","name":"session-based preference learning and recommendation personalization","description":"Tracks user interactions within a single session (clicked recommendations, viewed historical narratives, activity types explored) to infer preferences and personalize subsequent recommendations without requiring explicit user profiles or account creation. The system uses implicit feedback signals (dwell time, click patterns, activity selections) to build a lightweight preference model that adapts recommendations in real-time as the user explores.","intents":["I want recommendations that get smarter as I use the app, learning what I actually like","Show me more activities similar to the ones I've already clicked on","Personalize recommendations based on my exploration patterns without forcing me to create an account"],"best_for":["casual users who want personalization without account friction","travelers exploring a single city or region during a trip","users with consistent interests within a session"],"limitations":["Preference learning is session-based; recommendations reset when user closes the app or clears browser data","No cross-session learning; returning users don't benefit from previous trip preferences","Implicit feedback signals (clicks, dwell time) are noisy and may not accurately reflect true preferences","No explicit feedback mechanism (ratings, likes) to correct preference inference","Limited personalization depth compared to account-based systems with rich user history","Privacy-first approach (no persistent profiles) prevents sophisticated collaborative filtering"],"requires":["Session storage (browser localStorage or in-memory state)","Interaction tracking (click events, view duration, activity selections)","Preference inference algorithm (likely rule-based or lightweight ML model)"],"input_types":["user interactions (clicks, views, selections)","activity types and categories","historical narrative topics viewed"],"output_types":["personalized recommendation rankings","inferred user preference profile (activity types, interests, budget level)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_good-tripper-guide__cap_6","uri":"capability://text.generation.language.ai.generated.historical.narrative.synthesis.with.source.attribution","name":"ai-generated historical narrative synthesis with source attribution","description":"Synthesizes historical narratives by retrieving relevant facts from a knowledge base and using an LLM to compose readable, contextual narratives that emphasize local significance. The system likely includes source attribution or confidence scoring to indicate which facts are well-documented vs. inferred, though the editorial summary suggests this may be underimplemented, leading to occasional oversimplification of sensitive historical topics.","intents":["I want to understand the historical significance of this location in 2-3 minutes without reading a full Wikipedia article","Explain the cultural importance of this neighborhood's architecture and street layout","Give me context about this historical figure's connection to this specific place"],"best_for":["travelers seeking quick historical context during self-guided exploration","history enthusiasts wanting depth beyond surface-level facts","users exploring unfamiliar cities and cultures"],"limitations":["AI-generated narratives occasionally lack nuance on sensitive historical events (colonialism, conflict, marginalized perspectives) due to training data bias and oversimplification","No explicit source attribution or confidence scoring; users can't distinguish well-documented facts from inferred or speculative content","Knowledge base coverage is uneven; Western cities and well-documented historical periods are overrepresented","No real-time fact-checking against academic sources; relies on static training data with unknown cutoff date","Narrative style is generic; doesn't adapt to user expertise level (beginner vs. historian)","No mechanism for community correction or crowdsourced accuracy improvements"],"requires":["Vector-indexed knowledge base of historical facts and events","LLM API (likely OpenAI GPT or similar) for narrative generation","Geolocation data to retrieve relevant historical context","Internet connectivity for API calls"],"input_types":["geolocation (latitude/longitude) or address","optional: user interest focus (architecture, politics, culture, etc.)"],"output_types":["narrative text (2-5 paragraphs)","structured metadata (dates, key figures, related locations, confidence scores if available)"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_good-tripper-guide__cap_7","uri":"capability://planning.reasoning.distance.aware.activity.proximity.filtering","name":"distance-aware activity proximity filtering","description":"Filters activity recommendations based on travel distance and estimated time to reach each activity from the user's current location. The system calculates walking/transit distances using mapping APIs and ranks activities by proximity, allowing users to discover nearby options without extensive travel time. This is particularly useful for spontaneous decision-making where users have limited time windows.","intents":["Show me activities within walking distance (15 minutes) from where I am right now","What can I do in the next hour without spending 30 minutes on transit?","Find nearby museums or cafes that are actually close enough to visit spontaneously"],"best_for":["travelers making spontaneous decisions with limited time windows","users exploring on foot without transportation","travelers unfamiliar with local geography and transit systems"],"limitations":["Distance calculations depend on mapping API accuracy; routing may not account for pedestrian-only paths or local shortcuts","Transit time estimates are averages; actual travel time varies by time of day, traffic, and transit frequency","No integration with real-time transit data; recommendations may suggest activities that are unreachable due to transit delays","Walking distance is calculated as crow-flies or shortest route; doesn't account for terrain difficulty or safety","Doesn't account for user mobility constraints (accessibility, physical fitness, luggage)"],"requires":["Mapping API (Google Maps, Mapbox, OpenStreetMap) for distance and routing calculations","Geolocation data for user's current position","Activity location data (latitude/longitude for each recommendation)"],"input_types":["user's current geolocation","activity locations","optional: maximum travel time or distance threshold"],"output_types":["ranked activities by proximity","estimated travel time and distance for each activity","transit mode suggestions (walking, transit, etc.)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"low","permissions":["Device with GPS or browser geolocation API support","Internet connectivity for API calls to LLM and knowledge base","Modern browser (Chrome 90+, Firefox 88+, Safari 14+)","User consent for location access","Real-time weather API (OpenWeatherMap, WeatherAPI, or similar)","Local events API (Eventbrite, Meetup, or city-specific event feeds)","Geolocation data (GPS or address)","Internet connectivity for real-time data fetching","Optional: user account for preference persistence","Web browser (no app installation required)"],"failure_modes":["AI-generated narratives occasionally oversimplify sensitive historical events (colonialism, conflict, marginalized perspectives) due to training data bias","Knowledge base coverage is uneven — well-documented Western cities have richer context than underrepresented regions","No real-time fact-checking against academic sources; relies on static training data with unknown cutoff date","Geolocation accuracy depends on device GPS precision; urban canyons and indoor locations may trigger irrelevant narratives","Real-time event data coverage depends on local event API availability; smaller cities may have sparse event feeds","Weather-based recommendations are generic (e.g., 'indoor activities when raining') without nuanced understanding of activity-weather fit","No integration with booking systems; recommendations may point to fully-booked or closed venues without real-time availability verification","Crowd pattern data likely sourced from Google Maps or similar; accuracy varies by location and time period","User preference learning is session-based with no persistent user profiles; recommendations reset between visits","Sustainability model is unclear; free access raises questions about long-term server cost coverage and development roadmap","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3333333333333333,"quality":0.6900000000000001,"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":"2026-05-24T12:16:30.892Z","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=good-tripper-guide","compare_url":"https://unfragile.ai/compare?artifact=good-tripper-guide"}},"signature":"VjqFhKxnRK288XBcy87oP+fV8sb/I8nDn1jRcdpvoi0HOpfEjrJQ3uJXkm60xv3ZEDFFCwq2EhVObSwf1mP3DA==","signedAt":"2026-06-20T23:43:01.935Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/good-tripper-guide","artifact":"https://unfragile.ai/good-tripper-guide","verify":"https://unfragile.ai/api/v1/verify?slug=good-tripper-guide","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"}}