{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_iplan-ai","slug":"iplan-ai","name":"iPlan.ai","type":"product","url":"https://iplan.ai","page_url":"https://unfragile.ai/iplan-ai","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_iplan-ai__cap_0","uri":"capability://text.generation.language.conversational.itinerary.generation.from.natural.language","name":"conversational itinerary generation from natural language","description":"Accepts free-form natural language queries about travel preferences (destination, dates, budget, interests, dietary restrictions) and generates multi-day itineraries through a chat interface. Uses conversational context accumulation to maintain user preferences across multiple turns without requiring re-specification, leveraging LLM-based intent extraction and itinerary templating to structure responses into day-by-day activity sequences.","intents":["I want to describe my trip preferences in natural language without filling out forms","I need a quick itinerary suggestion without spending hours researching","I want the AI to remember my travel style and budget across multiple conversation turns"],"best_for":["spontaneous leisure travelers planning 3-7 day trips","users who prefer conversational interaction over structured forms","travelers seeking quick inspiration rather than detailed logistics planning"],"limitations":["No real-time availability checking—recommendations may ignore seasonal closures, sold-out attractions, or current pricing","Conversational context is session-scoped; preference learning doesn't persist across new conversations without explicit account-level storage","No integration with actual booking APIs, so generated itineraries are suggestions only, not actionable reservations","LLM-based generation can produce hallucinated attractions or inaccurate opening hours without external fact-checking"],"requires":["Active internet connection for LLM inference","User account (free tier available)","Destination name or geographic coordinates"],"input_types":["natural language text (destination, dates, preferences, constraints)"],"output_types":["structured itinerary (day-by-day activity list with times and descriptions)","natural language explanations and follow-up suggestions"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_1","uri":"capability://search.retrieval.preference.aware.activity.and.attraction.recommendation","name":"preference-aware activity and attraction recommendation","description":"Recommends specific attractions, restaurants, and activities based on extracted user preferences (budget tier, interests, dietary restrictions, travel pace) from conversational context. Uses semantic matching between user-stated preferences and a curated or LLM-indexed database of attractions to surface personalized suggestions rather than generic top-rated lists, filtering by compatibility with stated constraints.","intents":["I want restaurant recommendations that match my dietary restrictions without having to repeat them","I want activities suggested based on my interests, not just the most popular tourist spots","I want recommendations that fit my budget tier without manually filtering"],"best_for":["travelers with specific dietary needs or niche interests","budget-conscious travelers who want filtering applied automatically","users who want personalized suggestions beyond generic top-10 lists"],"limitations":["Recommendations are not real-time; they don't account for current availability, hours of operation, or seasonal closures","No integration with review aggregators (Google Maps, Yelp, TripAdvisor) means recommendations lack current ratings or recent user feedback","Preference extraction is limited to what users explicitly state in conversation; implicit preferences (e.g., 'I like hidden gems') may be misinterpreted","No booking integration means users must manually verify availability and pricing before committing"],"requires":["User to articulate preferences in natural language (destination, interests, budget, dietary restrictions)","Access to attraction/restaurant database (scope and freshness unknown)"],"input_types":["natural language preference statements","destination name or coordinates"],"output_types":["ranked list of attractions/restaurants with descriptions","structured data (name, category, estimated cost, compatibility notes)"],"categories":["search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_2","uri":"capability://planning.reasoning.day.by.day.itinerary.structuring.with.time.based.sequencing","name":"day-by-day itinerary structuring with time-based sequencing","description":"Organizes recommended activities and attractions into a day-by-day schedule with estimated times and logical geographic/temporal sequencing. Uses heuristic-based or LLM-guided ordering to place activities in a sensible sequence (e.g., morning museum visits before afternoon outdoor activities) and estimates travel time between locations, though without real-time transit data or detailed logistics validation.","intents":["I want my activities organized into a realistic daily schedule, not just a list","I want to know roughly how much time each activity takes and when to do it","I want activities grouped geographically to minimize travel time between them"],"best_for":["travelers who want a rough daily structure without detailed logistics planning","users planning 3-7 day trips where approximate sequencing is sufficient","travelers who don't need minute-by-minute precision or real transit times"],"limitations":["No real-time transit data (public transport, traffic, flight times)—estimated travel times may be inaccurate, leading to impractical schedules","No integration with flight arrival times or hotel check-in/check-out times, so day 1 schedules may assume immediate availability","Time estimates for activities are generic and don't account for crowd levels, seasonal variations, or user pace preferences","Geographic sequencing is approximate; no actual routing optimization (e.g., TSP-style minimization of total travel distance)","No validation against actual opening hours or seasonal closures"],"requires":["List of activities/attractions with estimated durations","Destination geography (implicit in attraction database)","User-stated travel dates and preferences"],"input_types":["list of recommended attractions","user preferences (travel pace, interests)"],"output_types":["structured day-by-day itinerary with times (e.g., '9:00 AM - Museum visit (2 hours)', '12:00 PM - Lunch', '2:00 PM - Park walk')","estimated travel times between activities"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_3","uri":"capability://text.generation.language.multi.turn.preference.refinement.and.itinerary.regeneration","name":"multi-turn preference refinement and itinerary regeneration","description":"Allows users to iteratively refine itineraries through follow-up conversational turns (e.g., 'Make it more budget-friendly', 'Add more nightlife', 'Skip museums') by parsing natural language refinement requests and regenerating the itinerary with updated constraints. Maintains conversation history to apply cumulative preference changes without losing prior context.","intents":["I want to adjust my itinerary based on feedback without starting over","I want to add or remove activity categories without re-specifying my entire trip","I want to see alternative itineraries that emphasize different aspects (budget vs luxury, adventure vs relaxation)"],"best_for":["users who want to explore multiple itinerary variations interactively","travelers who refine preferences as they think through their trip","users who want quick pivots without re-entering all original constraints"],"limitations":["Preference refinement is session-scoped; closing the conversation loses all refinement history","No explicit version control or comparison between itinerary versions—users must manually track changes","Refinement requests are parsed via LLM intent extraction, which may misinterpret ambiguous requests","No rollback mechanism if a refinement produces an undesired result"],"requires":["Active conversation session with prior itinerary generated","Natural language refinement request"],"input_types":["natural language refinement instructions (e.g., 'Make it cheaper', 'Add adventure activities')"],"output_types":["regenerated itinerary with updated constraints applied","explanation of changes made"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_4","uri":"capability://automation.workflow.freemium.access.with.usage.based.tier.differentiation","name":"freemium access with usage-based tier differentiation","description":"Provides a free tier allowing users to generate basic itineraries (likely limited by number of requests, itinerary length, or destination complexity) with a paid upgrade path for advanced features (e.g., longer itineraries, more refinement turns, priority support). Implements usage tracking and tier-based feature gating at the API/backend level to enforce limits.","intents":["I want to test the tool for free before committing to a paid plan","I want to plan a simple domestic trip without paying","I want to upgrade only if I need advanced features"],"best_for":["casual travelers planning straightforward trips","users evaluating the tool before purchase","budget-conscious travelers who don't need premium features"],"limitations":["Free tier limitations are not explicitly detailed in available information—scope of free vs paid features is unclear","No information on upgrade pricing or feature breakdown","Free tier may have rate limits that frustrate users planning multiple trips","Freemium model may incentivize feature limitations in free tier that reduce utility"],"requires":["User account creation","No payment required for free tier"],"input_types":["user tier status (free or paid)"],"output_types":["access to feature set based on tier"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_5","uri":"capability://memory.knowledge.personalization.profile.learning.from.conversation.history","name":"personalization profile learning from conversation history","description":"Builds an implicit user preference profile by extracting and retaining travel style, budget tier, dietary restrictions, activity preferences, and pace from conversational interactions within a session. Uses this profile to contextualize subsequent recommendations and itinerary generation without requiring explicit re-specification, leveraging LLM-based preference extraction and context window management.","intents":["I want the AI to remember my travel style and budget without me repeating it","I want dietary restrictions applied to all restaurant recommendations automatically","I want my activity preferences to influence all suggestions in the conversation"],"best_for":["users planning multiple activities or refinements in a single session","travelers with specific constraints (dietary, budget, accessibility) who don't want to repeat them","users who value personalization and want the AI to learn their preferences"],"limitations":["Profile learning is session-scoped; preferences don't persist across new conversations unless explicitly saved to account","No explicit user control over what preferences are extracted or how they're weighted","Preference extraction relies on LLM interpretation, which may misunderstand or over-generalize from casual statements","No transparency into what preferences have been learned or how they're being applied","No mechanism to correct misunderstood preferences mid-conversation"],"requires":["Active conversation session","User to articulate preferences naturally (not required to be explicit)"],"input_types":["natural language conversation history"],"output_types":["implicit preference profile (used internally for filtering and recommendation)"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_6","uri":"capability://search.retrieval.destination.specific.activity.and.attraction.database.lookup","name":"destination-specific activity and attraction database lookup","description":"Maintains or accesses a database of attractions, restaurants, activities, and points of interest indexed by destination, enabling rapid retrieval of relevant suggestions when a user specifies a location. Database likely includes basic metadata (name, category, estimated cost, description) but lacks real-time availability, current pricing, or live reviews.","intents":["I want suggestions for what to do in a specific destination","I want to know what attractions and restaurants exist in my chosen location","I want activity recommendations filtered by category (museums, outdoor, nightlife)"],"best_for":["travelers planning trips to popular destinations with good database coverage","users who want quick suggestions without external research","travelers planning to well-known cities or regions"],"limitations":["Database coverage is unknown—may be limited to major tourist destinations and sparse for off-the-beaten-path locations","Data freshness is unknown—attractions may have closed, changed hours, or been replaced without database updates","No real-time pricing or availability data; recommendations may be outdated","No integration with review aggregators (Google Maps, Yelp) means recommendations lack current ratings or recent user feedback","Database likely contains generic, well-known attractions rather than hidden gems or niche recommendations"],"requires":["Destination name or geographic coordinates","Access to attraction/restaurant database (backend service)"],"input_types":["destination name or coordinates","optional activity category filter"],"output_types":["list of attractions/restaurants with metadata (name, category, estimated cost, description)"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_7","uri":"capability://text.generation.language.natural.language.itinerary.export.and.sharing","name":"natural language itinerary export and sharing","description":"Generates human-readable itinerary summaries that can be exported or shared in text format, presenting the day-by-day schedule, activity descriptions, and recommendations in a format suitable for reading on mobile devices or sharing with travel companions. Likely uses template-based formatting to structure the output consistently.","intents":["I want to save my itinerary as a readable document","I want to share my itinerary with travel companions","I want to print or view my itinerary on my phone during the trip"],"best_for":["users who want to reference their itinerary offline or on mobile","travelers planning group trips and needing to share plans with companions","users who want a backup of their itinerary outside the app"],"limitations":["Export format is likely text or PDF only; no integration with calendar apps (Google Calendar, Outlook) or shared planning tools (Google Sheets, Notion)","No real-time sync if itinerary is modified after export—exported versions become stale","Sharing mechanism is unknown; likely requires manual copy-paste or email rather than shareable links","No collaborative editing—shared itineraries are read-only snapshots, not live documents"],"requires":["Generated itinerary","Export/sharing feature enabled in UI"],"input_types":["generated itinerary (structured data)"],"output_types":["text or PDF document with formatted itinerary","shareable link or exported file"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_iplan-ai__cap_8","uri":"capability://search.retrieval.budget.aware.activity.and.restaurant.filtering","name":"budget-aware activity and restaurant filtering","description":"Filters attraction and restaurant recommendations based on user-stated budget constraints (e.g., 'budget-friendly', 'mid-range', 'luxury'), applying cost-based filtering to suggestions without requiring users to manually exclude expensive options. Uses estimated cost metadata in the attraction database to match recommendations to budget tier.","intents":["I want restaurant recommendations that fit my budget without manually filtering","I want activities that are affordable for my trip budget","I want to see only mid-range or budget options, not luxury experiences"],"best_for":["budget-conscious travelers who want automatic cost filtering","travelers with fixed daily budgets who want recommendations to respect them","users who don't want to manually exclude expensive options"],"limitations":["Cost estimates in the database are likely generic and may not reflect current pricing or seasonal variations","No real-time pricing integration; estimates may be significantly outdated","Budget filtering is binary (matches tier or doesn't); no granular per-activity budget allocation","No integration with actual booking prices, so recommendations may appear affordable but be unavailable at estimated cost","Currency conversion and regional cost variations are not addressed"],"requires":["User to specify budget tier or constraint in natural language","Attraction database with cost metadata"],"input_types":["budget constraint (e.g., 'budget-friendly', 'mid-range', specific daily budget)"],"output_types":["filtered list of attractions/restaurants matching budget tier"],"categories":["search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":42,"verified":false,"data_access_risk":"high","permissions":["Active internet connection for LLM inference","User account (free tier available)","Destination name or geographic coordinates","User to articulate preferences in natural language (destination, interests, budget, dietary restrictions)","Access to attraction/restaurant database (scope and freshness unknown)","List of activities/attractions with estimated durations","Destination geography (implicit in attraction database)","User-stated travel dates and preferences","Active conversation session with prior itinerary generated","Natural language refinement request"],"failure_modes":["No real-time availability checking—recommendations may ignore seasonal closures, sold-out attractions, or current pricing","Conversational context is session-scoped; preference learning doesn't persist across new conversations without explicit account-level storage","No integration with actual booking APIs, so generated itineraries are suggestions only, not actionable reservations","LLM-based generation can produce hallucinated attractions or inaccurate opening hours without external fact-checking","Recommendations are not real-time; they don't account for current availability, hours of operation, or seasonal closures","No integration with review aggregators (Google Maps, Yelp, TripAdvisor) means recommendations lack current ratings or recent user feedback","Preference extraction is limited to what users explicitly state in conversation; implicit preferences (e.g., 'I like hidden gems') may be misinterpreted","No booking integration means users must manually verify availability and pricing before committing","No real-time transit data (public transport, traffic, flight times)—estimated travel times may be inaccurate, leading to impractical schedules","No integration with flight arrival times or hotel check-in/check-out times, so day 1 schedules may assume immediate availability","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.7300000000000001,"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":"2026-05-24T12:16:31.445Z","last_scraped_at":"2026-04-05T13:23:42.551Z","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=iplan-ai","compare_url":"https://unfragile.ai/compare?artifact=iplan-ai"}},"signature":"Ps0WuCFUSGo4xrve6Ei7+Hpe/Yg1C2EvwM+ZnUn+lGtzLn/Y7pa3/1/THJ/VZvMqlCTuPHytsv+nJI1qup4jCw==","signedAt":"2026-06-20T18:45:03.357Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/iplan-ai","artifact":"https://unfragile.ai/iplan-ai","verify":"https://unfragile.ai/api/v1/verify?slug=iplan-ai","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"}}