{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-heymoon-ai","slug":"heymoon-ai","name":"Heymoon.ai","type":"product","url":"https://heymoon.ai/","page_url":"https://unfragile.ai/heymoon-ai","categories":["app-builders"],"tags":[],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-heymoon-ai__cap_0","uri":"capability://memory.knowledge.calendar.event.aggregation.and.normalization","name":"calendar-event-aggregation-and-normalization","description":"Aggregates calendar events from multiple sources (Google Calendar, Outlook, Apple Calendar, etc.) into a unified view by normalizing different calendar API schemas and event formats into a common data model. Implements polling or webhook-based sync mechanisms to keep calendar state current across providers, handling timezone conversions, recurring event expansion, and conflict detection across integrated calendars.","intents":["I want a single view of all my calendar events across multiple email and calendar providers without switching between apps","I need to see when I'm double-booked or have scheduling conflicts across different calendar systems","I want my calendar data synchronized in real-time so I always see the latest event changes"],"best_for":["knowledge workers managing calendars across multiple organizations or email providers","executives with complex scheduling across personal and work calendars","teams using heterogeneous calendar systems (some on Google, some on Outlook)"],"limitations":["Sync latency depends on provider API rate limits — typically 5-15 minute delays for webhook-less providers","Recurring event expansion can be computationally expensive for multi-year recurring patterns","Some calendar providers (e.g., Apple Calendar) have limited API access, requiring workarounds or manual sync triggers","Timezone handling complexity increases with international teams — edge cases around DST transitions may cause display inconsistencies"],"requires":["OAuth 2.0 credentials for at least one calendar provider (Google, Microsoft, Apple, or iCal)","Network connectivity for real-time sync","Calendar provider API access (some require paid tiers for webhook support)"],"input_types":["calendar provider OAuth tokens","calendar event metadata (title, time, attendees, location)","recurring event rules (iCalendar RRULE format)"],"output_types":["unified calendar event objects","conflict/overlap detection results","calendar view (day, week, month formats)"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-heymoon-ai__cap_1","uri":"capability://automation.workflow.task.list.management.with.deadline.tracking","name":"task-list-management-with-deadline-tracking","description":"Manages task creation, assignment, prioritization, and deadline tracking with integration to calendar events. Implements task-to-calendar linking (e.g., creating a task automatically blocks calendar time), deadline reminder logic with escalating notifications, and task status state machines (todo → in-progress → blocked → done). Supports task dependencies and critical path analysis for complex projects.","intents":["I want to create tasks and have them automatically appear on my calendar as time blocks","I need reminders for upcoming task deadlines that escalate in urgency as the deadline approaches","I want to track task dependencies so I know which tasks are blocking others from completion"],"best_for":["project managers tracking multiple concurrent initiatives","individual contributors managing personal productivity with calendar integration","teams needing lightweight task management without heavyweight project management tools"],"limitations":["Task dependency graphs are limited to linear chains — no support for complex DAG structures with multiple dependency paths","Deadline reminders use simple time-based triggers; no intelligent scheduling that considers task duration and calendar availability","No built-in task estimation or burndown tracking — requires external analytics","Task state transitions are not customizable — fixed workflow (todo → in-progress → blocked → done) may not fit all team processes"],"requires":["Calendar integration enabled (at least one provider connected)","User authentication and session management","Persistent storage for task state (database or cloud backend)"],"input_types":["task title and description (text)","deadline date/time","priority level (enum)","assigned user (email or user ID)","task dependencies (task ID references)"],"output_types":["task objects with status and metadata","calendar events (auto-generated from task deadlines)","reminder notifications (push, email, or in-app)","dependency graph visualization"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-heymoon-ai__cap_2","uri":"capability://search.retrieval.information.retrieval.and.context.surfacing","name":"information-retrieval-and-context-surfacing","description":"Surfaces relevant information (emails, documents, notes, previous conversations) contextually based on calendar events, tasks, or user queries. Implements semantic search using embeddings to find related documents, email threading to group conversations, and recency-weighted ranking to prioritize recent information. Integrates with email providers, document storage (Google Drive, OneDrive), and note-taking apps to build a searchable knowledge index.","intents":["Before a meeting, I want to automatically see relevant emails, documents, and notes related to that meeting's topic","I want to search across all my information sources (email, documents, notes) with a single query","I need context about a person or project pulled from my past emails and documents when I interact with them"],"best_for":["busy professionals who need quick context before meetings","knowledge workers managing large volumes of emails and documents","teams collaborating across multiple information sources"],"limitations":["Semantic search quality depends on embedding model quality — may surface irrelevant results for ambiguous queries","Indexing latency for large document collections (10k+ documents) can be 30+ minutes, delaying search freshness","Privacy concerns with embedding sensitive documents — requires careful handling of PII and confidential information","Cross-provider search requires separate API integrations for each source (Gmail, Outlook, Google Drive, OneDrive, Notion, etc.) — not all providers have equivalent API capabilities","Email threading heuristics may incorrectly group unrelated messages with similar subjects"],"requires":["OAuth 2.0 access to email provider (Gmail, Outlook, etc.)","OAuth 2.0 access to document storage (Google Drive, OneDrive, etc.)","Embedding model (local or cloud-based) for semantic search","Vector database or search index for storing embeddings"],"input_types":["calendar event metadata (title, attendees, description)","user search query (natural language text)","email messages (full text and metadata)","documents (PDF, Word, text formats)"],"output_types":["ranked list of relevant documents/emails","email thread summaries","document excerpts with relevance scores","context cards for meetings"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-heymoon-ai__cap_3","uri":"capability://text.generation.language.natural.language.calendar.and.task.interaction","name":"natural-language-calendar-and-task-interaction","description":"Enables users to manage calendar and tasks through natural language commands processed by an LLM. Parses user intent from conversational input (e.g., 'Schedule a meeting with John next Tuesday at 2pm' or 'Remind me to follow up on the Q4 budget'), extracts structured parameters (date, time, attendees, task description), and executes corresponding calendar/task operations. Implements intent classification, entity extraction, and parameter validation before execution.","intents":["I want to create calendar events and tasks by speaking or typing natural language commands instead of using forms","I need to ask questions about my schedule in natural language ('When am I free next week?', 'Do I have conflicts on Friday?')","I want to update or reschedule events conversationally without navigating UI menus"],"best_for":["mobile-first users who prefer voice/chat interaction over UI navigation","busy professionals who want to manage calendar/tasks while multitasking","non-technical users who find traditional calendar UIs complex"],"limitations":["Ambiguous natural language inputs require clarification — 'next Tuesday' is ambiguous if today is Tuesday; system must handle edge cases","Entity extraction errors (e.g., misidentifying attendee names) can lead to incorrect calendar entries — requires confirmation step","LLM hallucination risk — model may invent plausible-sounding but incorrect information (e.g., suggesting a meeting time that doesn't exist)","Context window limitations — cannot handle very long conversation histories without summarization","Timezone handling in natural language is error-prone — 'tomorrow at 2pm' is ambiguous across timezones"],"requires":["LLM API access (OpenAI, Anthropic, or local model)","Calendar and task backend integration","Natural language processing pipeline (tokenizer, intent classifier, entity extractor)","User confirmation/approval step before executing calendar/task mutations"],"input_types":["natural language text or voice transcription","conversation history (for context)","user calendar and task data (for grounding)"],"output_types":["structured calendar event or task object","clarification questions (when input is ambiguous)","confirmation prompts before execution","natural language responses to queries"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-heymoon-ai__cap_4","uri":"capability://text.generation.language.meeting.preparation.and.summary.generation","name":"meeting-preparation-and-summary-generation","description":"Automatically prepares for upcoming meetings by gathering relevant context (attendee info, previous interactions, related documents) and generates post-meeting summaries from meeting notes or recordings. Uses LLM-based summarization to extract action items, decisions, and key discussion points. Integrates with calendar to identify upcoming meetings and with email/document stores to find relevant background information.","intents":["Before a meeting, I want a one-page brief with attendee backgrounds, previous discussion history, and relevant documents","After a meeting, I want an automated summary of decisions, action items, and key points without manual note-taking","I want to track action items from meetings and link them to tasks in my task management system"],"best_for":["executives attending many meetings who need quick context preparation","teams using meeting recordings or transcripts for async documentation","organizations wanting to reduce meeting note-taking overhead"],"limitations":["Summary quality depends on meeting recording/transcript quality — poor audio or transcription errors degrade summaries","Action item extraction is heuristic-based and may miss implicit commitments or misidentify owners","Context gathering is limited by available integrations — if a relevant document is in an unsupported system, it won't be surfaced","Attendee background information is limited to what's available in email/directory — may be incomplete for external attendees","Real-time meeting transcription requires additional infrastructure (speech-to-text service) and introduces latency"],"requires":["Calendar integration to identify upcoming meetings","Email and document storage integration for context gathering","Meeting recording or transcript (audio file, video file, or text transcript)","Speech-to-text service (if processing audio/video recordings)","LLM API for summarization and action item extraction","Task management backend to create action item tasks"],"input_types":["calendar event metadata (title, attendees, time)","meeting recording (audio/video file)","meeting transcript (text)","meeting notes (text)"],"output_types":["pre-meeting brief (text document with context)","meeting summary (text with key points)","action items list (structured data with owners and deadlines)","task objects created from action items"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-heymoon-ai__cap_5","uri":"capability://planning.reasoning.intelligent.scheduling.and.availability.optimization","name":"intelligent-scheduling-and-availability-optimization","description":"Analyzes calendar availability across multiple attendees and suggests optimal meeting times using constraint satisfaction algorithms. Considers time zone differences, preferred working hours, existing meeting load, and travel time between locations. Implements calendar-aware scheduling that respects focus time blocks and meeting-free periods. Can automatically propose times or directly book meetings if permissions allow.","intents":["I want to find a meeting time that works for 5+ people across different time zones without manually checking each person's calendar","I need to schedule meetings while protecting focus time and avoiding back-to-back meeting marathons","I want to automatically book meetings when I find a time that works for all attendees"],"best_for":["meeting organizers scheduling cross-functional or cross-timezone teams","executive assistants managing complex scheduling for multiple executives","distributed teams across multiple time zones"],"limitations":["Requires read access to attendees' calendars — privacy concerns and permission management complexity","Constraint satisfaction algorithms have exponential complexity with many attendees (10+ people) — may timeout or return suboptimal results","Cannot account for implicit preferences (e.g., 'I prefer mornings' unless explicitly marked in calendar)","Travel time estimation requires location data which may not be available or accurate","Focus time blocks are only respected if explicitly marked in calendar — many users don't maintain these","Time zone handling is complex — daylight saving time transitions can cause scheduling errors"],"requires":["Read access to attendees' calendars (requires OAuth 2.0 with calendar read permissions)","Attendee list with email addresses or user IDs","Meeting duration and preferred time window","Constraint satisfaction solver (local or cloud-based)","Time zone database for accurate timezone handling"],"input_types":["list of attendee email addresses","meeting duration (minutes)","preferred time window (date range and time range)","constraints (time zones, focus time blocks, travel time)","meeting location (optional, for travel time calculation)"],"output_types":["ranked list of suggested meeting times","availability heatmap showing conflicts","calendar event (if auto-booking is enabled)","meeting invitation sent to attendees"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-heymoon-ai__cap_6","uri":"capability://automation.workflow.priority.and.urgency.assessment.with.smart.notifications","name":"priority-and-urgency-assessment-with-smart-notifications","description":"Analyzes incoming calendar events, tasks, and information to assess priority and urgency using heuristics and ML models. Implements smart notification routing that filters low-priority items and escalates high-priority notifications. Uses context from calendar (meeting importance based on attendees), task dependencies, and deadline proximity to determine urgency. Supports notification customization (do-not-disturb periods, notification channels) and prevents notification fatigue through intelligent batching and deduplication.","intents":["I want to be notified only about truly important calendar events and tasks, not every minor update","I need urgent items to interrupt me immediately while less important items are batched into a daily digest","I want to set do-not-disturb periods so I'm not interrupted during focus time or after hours"],"best_for":["busy professionals overwhelmed by notifications","knowledge workers needing to maintain focus time","teams with varying notification preferences and urgency levels"],"limitations":["Priority assessment heuristics are rule-based and may not capture domain-specific urgency (e.g., a meeting with the CEO is always high-priority, but system may not know this)","ML-based priority models require training data and may have cold-start problems for new users","Notification channels are limited to what's available (email, push, SMS, Slack) — some users may prefer other channels","Do-not-disturb logic is simple time-based — cannot handle complex rules like 'don't notify during meetings' without calendar integration","Notification deduplication may suppress important repeated reminders"],"requires":["Calendar and task data for context","User notification preferences and do-not-disturb schedule","Notification delivery infrastructure (email, push notifications, SMS, Slack integration)","Priority assessment model (rule-based or ML-based)","User feedback loop for training priority models (optional but recommended)"],"input_types":["calendar event metadata","task metadata and deadline","user notification preferences","do-not-disturb schedule","historical user interaction data (optional, for ML training)"],"output_types":["priority score (numeric or categorical)","urgency level (low, medium, high, critical)","notification (email, push, SMS, Slack message)","notification batches (daily digest)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-heymoon-ai__cap_7","uri":"capability://data.processing.analysis.calendar.and.task.analytics.with.insights","name":"calendar-and-task-analytics-with-insights","description":"Analyzes calendar and task data to generate insights about time usage, productivity patterns, and scheduling habits. Computes metrics like meeting load, focus time availability, task completion rate, and deadline adherence. Identifies patterns (e.g., 'you have 15 hours of meetings every Monday') and generates recommendations (e.g., 'block focus time on Tuesday mornings when you're most productive'). Implements trend analysis over time and comparative analytics (e.g., 'your meeting load increased 30% this quarter').","intents":["I want to understand how I'm spending my time across meetings, tasks, and focus work","I need insights into my productivity patterns to optimize my schedule","I want to see trends in my calendar and task completion over time to identify areas for improvement"],"best_for":["individuals focused on productivity optimization and time management","managers wanting to understand team scheduling patterns and workload distribution","organizations analyzing meeting culture and collaboration patterns"],"limitations":["Analytics are only as good as the data — if users don't consistently mark focus time or task status, insights will be incomplete","Correlation analysis may identify spurious patterns (e.g., 'you're more productive on days with more meetings' may be confounded by other factors)","Privacy concerns with team-level analytics — aggregating individual calendar data raises privacy issues","Recommendations are generic and may not account for domain-specific constraints (e.g., 'block focus time' may be impossible in customer-facing roles)","Trend analysis requires historical data — new users won't have meaningful trends for weeks or months"],"requires":["Historical calendar and task data (at least 4 weeks for meaningful analysis)","Analytics engine for computing metrics and trends","Data visualization library for displaying insights","Optional: ML model for pattern detection and recommendations"],"input_types":["calendar events (with duration and attendee count)","task data (with status and deadline)","focus time blocks (if marked)","user productivity preferences (optional)"],"output_types":["time usage metrics (hours in meetings, focus time, task work)","productivity insights (patterns, trends, recommendations)","visualizations (charts, heatmaps, dashboards)","comparative analytics (vs. previous period, vs. team average)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":23,"verified":false,"data_access_risk":"high","permissions":["OAuth 2.0 credentials for at least one calendar provider (Google, Microsoft, Apple, or iCal)","Network connectivity for real-time sync","Calendar provider API access (some require paid tiers for webhook support)","Calendar integration enabled (at least one provider connected)","User authentication and session management","Persistent storage for task state (database or cloud backend)","OAuth 2.0 access to email provider (Gmail, Outlook, etc.)","OAuth 2.0 access to document storage (Google Drive, OneDrive, etc.)","Embedding model (local or cloud-based) for semantic search","Vector database or search index for storing embeddings"],"failure_modes":["Sync latency depends on provider API rate limits — typically 5-15 minute delays for webhook-less providers","Recurring event expansion can be computationally expensive for multi-year recurring patterns","Some calendar providers (e.g., Apple Calendar) have limited API access, requiring workarounds or manual sync triggers","Timezone handling complexity increases with international teams — edge cases around DST transitions may cause display inconsistencies","Task dependency graphs are limited to linear chains — no support for complex DAG structures with multiple dependency paths","Deadline reminders use simple time-based triggers; no intelligent scheduling that considers task duration and calendar availability","No built-in task estimation or burndown tracking — requires external analytics","Task state transitions are not customizable — fixed workflow (todo → in-progress → blocked → done) may not fit all team processes","Semantic search quality depends on embedding model quality — may surface irrelevant results for ambiguous queries","Indexing latency for large document collections (10k+ documents) can be 30+ minutes, delaying search freshness","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.26,"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":"2026-06-17T09:51:03.041Z","last_scraped_at":"2026-05-03T14:00:10.321Z","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=heymoon-ai","compare_url":"https://unfragile.ai/compare?artifact=heymoon-ai"}},"signature":"rYNcx7N5ImjGPfzWzXutQbRD8E0DnHTYYwD22Ym7KpvgaPZbuUeD520rzSapkbU1PCC97AmG6s+WaxiM7Nm7Cw==","signedAt":"2026-06-22T09:42:39.760Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/heymoon-ai","artifact":"https://unfragile.ai/heymoon-ai","verify":"https://unfragile.ai/api/v1/verify?slug=heymoon-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"}}