{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_martin","slug":"martin","name":"Martin","type":"product","url":"https://www.trymartin.com","page_url":"https://unfragile.ai/martin","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_martin__cap_0","uri":"capability://planning.reasoning.proactive.calendar.conflict.detection","name":"proactive-calendar-conflict-detection","description":"Monitors integrated calendar data in real-time to identify scheduling conflicts, double-bookings, and overlapping commitments before they occur. Martin parses calendar events across multiple sources (Google Calendar, Outlook, etc.) and applies temporal logic to flag conflicts without requiring user action, surfacing alerts through the chat interface with suggested resolutions.","intents":["I want my AI assistant to warn me about calendar conflicts before I accept a meeting invite","I need to see overlapping commitments across multiple calendars automatically","I want proactive alerts about scheduling issues rather than discovering them manually"],"best_for":["executives managing multiple calendars across teams and organizations","busy professionals with back-to-back meetings who need automated conflict detection","remote workers coordinating across time zones"],"limitations":["Conflict detection latency depends on calendar sync frequency — may miss real-time changes if sync interval is >5 minutes","Cannot detect soft conflicts (e.g., travel time between locations) without explicit location data in calendar events","Limited to calendar sources that support OAuth integration; proprietary or legacy calendar systems may not be supported"],"requires":["Active calendar integration (Google Calendar, Microsoft Outlook, or equivalent)","OAuth permissions for calendar read access","Martin account with active subscription or freemium tier"],"input_types":["calendar events (iCalendar format or native API)","event metadata (title, time, attendees, location)"],"output_types":["conflict alerts (text)","structured conflict data (JSON with event IDs, times, severity)","suggested resolutions (text recommendations)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_1","uri":"capability://text.generation.language.email.context.aware.summarization","name":"email-context-aware-summarization","description":"Analyzes incoming and archived email threads to extract actionable insights, summarize conversation threads, and identify key decisions or action items without user prompting. Martin integrates with email providers (Gmail, Outlook) via OAuth, applies NLP-based summarization to thread chains, and surfaces summaries contextually when relevant to the user's current task or calendar.","intents":["I want my AI to summarize long email threads so I can quickly understand the context","I need to identify action items and decisions from email conversations automatically","I want the AI to flag important emails that require my attention based on content analysis"],"best_for":["knowledge workers managing high-volume email (50+ messages/day)","project managers tracking decisions and action items across email threads","executives who need rapid email triage without manual reading"],"limitations":["Summarization quality degrades on highly technical or domain-specific emails without fine-tuning on industry-specific language","Email threading accuracy depends on proper In-Reply-To headers; broken threading in some email clients may cause incorrect context grouping","Cannot access email attachments or embedded content — analysis limited to text body and metadata","Privacy-sensitive: requires full email read access, creating trust and compliance concerns for regulated industries"],"requires":["Email account integration (Gmail, Microsoft Outlook, or equivalent)","OAuth permissions for email read access","Martin account with active subscription"],"input_types":["email messages (MIME format or native API)","email metadata (sender, recipient, timestamp, subject)","email thread chains (linked via In-Reply-To headers)"],"output_types":["thread summaries (text)","action item extraction (structured list)","priority/importance scores (numeric or categorical)","decision logs (structured data)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_2","uri":"capability://search.retrieval.search.activity.based.information.surfacing","name":"search-activity-based-information-surfacing","description":"Monitors user search queries and browsing activity to infer information needs and proactively surface relevant documents, articles, or data before explicit requests. Martin integrates with search providers (Google Search, internal knowledge bases) and applies intent inference to predict what information the user will need next based on calendar events, email context, and historical search patterns.","intents":["I want my AI to find relevant information related to my upcoming meetings without me asking","I need background research on topics I'm searching for to be automatically compiled","I want the AI to learn my information preferences and surface relevant content proactively"],"best_for":["researchers and analysts who need continuous access to relevant information","sales professionals preparing for client meetings who want pre-meeting research","product managers tracking competitive intelligence and market trends"],"limitations":["Search activity monitoring raises significant privacy concerns — requires explicit user consent and transparent data handling","Intent inference accuracy depends on search query quality; ambiguous or short queries may lead to irrelevant suggestions","Cannot access search results behind paywalls or authentication walls; limited to publicly accessible content","Requires integration with search provider APIs (Google Custom Search, Bing Search) which have rate limits and cost implications"],"requires":["Search provider API access (Google Custom Search API, Bing Search API, or equivalent)","Browser extension or search integration (if monitoring browser search activity)","Martin account with active subscription","User consent for search activity monitoring"],"input_types":["search queries (text)","search results (URLs, snippets, metadata)","browsing history (URLs, timestamps)","calendar events (for context)"],"output_types":["curated information summaries (text)","relevant document links (URLs with context)","research compilations (structured data)","trend analysis (text or charts)"],"categories":["search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_3","uri":"capability://memory.knowledge.multi.source.context.aggregation","name":"multi-source-context-aggregation","description":"Unifies data from calendar, email, and search into a coherent context model that enables the AI to understand relationships between events, conversations, and information needs. Martin maintains a temporal and relational graph of user activities, linking calendar events to relevant emails, search queries, and previous conversations to provide holistic context for recommendations and proactive alerts.","intents":["I want my AI assistant to understand how my calendar, email, and research are all connected","I need the AI to provide context-aware suggestions that consider my full activity picture","I want the AI to connect dots between different data sources without me manually linking them"],"best_for":["knowledge workers with complex, interconnected workflows across multiple tools","project managers who need unified visibility across communications and scheduling","executives who want AI insights that synthesize multiple data streams"],"limitations":["Context aggregation latency increases with data volume — may experience delays with >10,000 emails or 500+ calendar events","Relationship inference between disparate data sources relies on heuristics (keyword matching, temporal proximity) which can produce false positives","No built-in data persistence layer — context model may be lost if session terminates; requires external state store for continuity","Privacy complexity increases exponentially with multi-source integration — requires careful data isolation and encryption"],"requires":["Active integrations with calendar provider, email provider, and search provider","Martin account with sufficient storage for context model (likely premium tier)","OAuth permissions for read access across all integrated sources"],"input_types":["calendar events with metadata","email messages with thread chains","search queries and results","user interaction history"],"output_types":["unified context summaries (text)","relationship graphs (structured data)","cross-source insights (text recommendations)","activity timelines (structured data)"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_4","uri":"capability://automation.workflow.proactive.notification.and.alert.generation","name":"proactive-notification-and-alert-generation","description":"Generates contextually relevant notifications and alerts based on analysis of calendar, email, and search data, surfacing them at optimal times through the chat interface. Martin applies priority scoring and timing heuristics to determine when to alert the user (e.g., 15 minutes before a meeting with relevant email context, or when a search result matches an upcoming topic), avoiding alert fatigue through intelligent batching and deduplication.","intents":["I want to be alerted about important calendar conflicts or email insights at the right time","I need the AI to prioritize which alerts are worth interrupting me for","I want alerts batched intelligently so I'm not overwhelmed with notifications"],"best_for":["busy professionals who need intelligent alert prioritization","teams using Martin as a shared assistant who need coordinated notifications","users who want to avoid notification fatigue while staying informed"],"limitations":["Alert timing optimization is heuristic-based and may not match individual user preferences without explicit training","Cannot integrate with native OS notification systems (Windows, macOS, iOS) — alerts limited to Martin chat interface","No built-in do-not-disturb or quiet hours configuration — requires manual user settings","Alert deduplication logic may suppress legitimate duplicate alerts if they occur within the dedup window (typically 5-10 minutes)"],"requires":["Martin account with active subscription","Calendar and email integrations enabled","User preferences configured for alert types and frequency"],"input_types":["calendar events with timing metadata","email messages with priority signals","search results with relevance scores","user interaction history"],"output_types":["alert notifications (text in chat interface)","alert metadata (priority, type, timestamp)","alert summaries (structured data)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_5","uri":"capability://text.generation.language.natural.language.conversation.with.context.awareness","name":"natural-language-conversation-with-context-awareness","description":"Provides a chat interface where users can ask questions and receive responses that are contextually aware of their calendar, email, and search history. Martin's LLM backbone (likely Claude or GPT-4 variant) is augmented with retrieval-augmented generation (RAG) that injects relevant calendar events, email summaries, and search results into the prompt context, enabling the AI to answer questions with specific, personalized information rather than generic responses.","intents":["I want to ask my AI assistant questions and get answers that consider my calendar and email context","I need the AI to reference specific meetings, emails, or research when answering my questions","I want to have natural conversations with my AI butler without manually providing context"],"best_for":["users who prefer conversational interaction over structured UI","professionals who want personalized AI responses based on their specific context","teams using Martin as a collaborative assistant"],"limitations":["RAG context injection adds latency (~500ms-2s per query) due to retrieval and prompt construction overhead","Context window limitations mean only the most relevant calendar/email/search data can be injected; older or less relevant data is excluded","LLM hallucination risk remains even with RAG — the AI may generate plausible-sounding but incorrect information about calendar events or email content","Conversation history is not persistent across sessions without explicit save functionality — context is lost on logout"],"requires":["Martin account with active subscription","Calendar, email, and search integrations enabled","LLM API access (OpenAI, Anthropic, or internal model)"],"input_types":["natural language queries (text)","conversation history (text)","calendar events (for context injection)","email summaries (for context injection)","search results (for context injection)"],"output_types":["natural language responses (text)","conversation history (text)","referenced sources (links to calendar events, emails, search results)"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_6","uri":"capability://tool.use.integration.oauth.based.multi.provider.integration","name":"oauth-based-multi-provider-integration","description":"Manages OAuth 2.0 authentication flows with multiple calendar, email, and search providers (Google, Microsoft, etc.) to securely obtain and maintain access tokens for reading user data. Martin implements a provider abstraction layer that normalizes API differences across providers, allowing the same backend logic to work with Google Calendar, Outlook, Gmail, and other services without provider-specific code duplication.","intents":["I want to connect my calendar and email accounts to Martin securely without sharing passwords","I need Martin to work with my existing Google/Microsoft/other accounts","I want to revoke Martin's access to my data without affecting other integrations"],"best_for":["enterprises with strict OAuth/SSO requirements","users who value security and don't want to share passwords","organizations using multiple email/calendar providers"],"limitations":["OAuth token refresh logic adds complexity — expired tokens must be refreshed before API calls, adding latency if refresh fails","Provider API rate limits apply to all Martin users sharing the same OAuth app credentials — high-volume usage may hit rate limits","Scope creep risk: OAuth scopes must be broad enough to access all needed data, but overly broad scopes create security concerns","Provider API changes (e.g., Google deprecating Calendar API v2) require Martin to update integration code; users may experience outages during migrations"],"requires":["OAuth app credentials registered with each provider (Google Cloud Console, Microsoft Azure, etc.)","User accounts with each provider (Google, Microsoft, etc.)","Martin backend with OAuth token storage and refresh logic"],"input_types":["OAuth authorization codes (from provider)","OAuth scopes (requested permissions)","User credentials (email, account ID)"],"output_types":["OAuth access tokens (stored securely)","OAuth refresh tokens (stored securely)","Provider API responses (calendar events, emails, etc.)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_7","uri":"capability://data.processing.analysis.temporal.event.correlation.and.linking","name":"temporal-event-correlation-and-linking","description":"Automatically identifies and links related events across calendar, email, and search data based on temporal proximity, participant overlap, and semantic similarity. Martin uses a correlation engine that matches calendar events to email threads (e.g., linking a meeting to the email chain that scheduled it), and links search queries to upcoming calendar events (e.g., recognizing that a search for 'Q4 budget' is related to a budget review meeting in 3 days).","intents":["I want the AI to automatically connect related calendar events, emails, and research","I need to see the full context of a meeting including the email thread that scheduled it","I want the AI to recognize when my search activity is related to upcoming calendar events"],"best_for":["professionals with complex, interconnected workflows","project managers tracking decisions across multiple communication channels","executives who need unified visibility across activities"],"limitations":["Correlation accuracy depends on data quality — missing or incomplete metadata (e.g., participant email addresses) reduces linking accuracy","Temporal window for correlation is fixed (typically 7-14 days) — events outside this window may not be linked even if semantically related","Semantic similarity matching relies on keyword overlap and NLP; domain-specific terminology may not be recognized","False positive correlations can occur when unrelated events happen to have temporal or participant overlap"],"requires":["Calendar integration with participant data","Email integration with thread metadata","Search integration with query history","NLP/ML model for semantic similarity (likely transformer-based)"],"input_types":["calendar events with participants and timestamps","email messages with sender, recipient, timestamp, subject","search queries with timestamps","user interaction history"],"output_types":["correlation links (structured data mapping events to related items)","correlation confidence scores (numeric)","unified event summaries (text)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_martin__cap_8","uri":"capability://automation.workflow.freemium.tier.with.limited.integration.depth","name":"freemium-tier-with-limited-integration-depth","description":"Offers a free tier that provides basic functionality (calendar conflict detection, email summarization) with limited integration depth and feature access, while premium tiers unlock advanced features like proactive search surfacing and multi-source context aggregation. The freemium model uses feature gates and API rate limiting to differentiate tiers without requiring separate codebases.","intents":["I want to try Martin without paying to see if it's useful for my workflow","I need basic calendar and email integration without advanced features","I want to upgrade to premium features only if the free tier proves valuable"],"best_for":["individual users evaluating Martin before committing to paid plans","small teams with limited budgets","users who only need basic calendar/email integration"],"limitations":["Free tier may have significant feature limitations (e.g., no search integration, limited email history access) that reduce utility","Rate limiting on free tier (e.g., 10 queries/day) may be too restrictive for active users","Free tier users may experience lower priority in API queues, resulting in slower response times","Freemium conversion funnel may be optimized for upselling rather than genuine user value, leading to frustration"],"requires":["Martin account (free signup)","Calendar and email integrations (may be limited on free tier)"],"input_types":["user account creation data","calendar and email integration requests"],"output_types":["free tier access with feature gates","upgrade prompts and pricing information"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Active calendar integration (Google Calendar, Microsoft Outlook, or equivalent)","OAuth permissions for calendar read access","Martin account with active subscription or freemium tier","Email account integration (Gmail, Microsoft Outlook, or equivalent)","OAuth permissions for email read access","Martin account with active subscription","Search provider API access (Google Custom Search API, Bing Search API, or equivalent)","Browser extension or search integration (if monitoring browser search activity)","User consent for search activity monitoring","Active integrations with calendar provider, email provider, and search provider"],"failure_modes":["Conflict detection latency depends on calendar sync frequency — may miss real-time changes if sync interval is >5 minutes","Cannot detect soft conflicts (e.g., travel time between locations) without explicit location data in calendar events","Limited to calendar sources that support OAuth integration; proprietary or legacy calendar systems may not be supported","Summarization quality degrades on highly technical or domain-specific emails without fine-tuning on industry-specific language","Email threading accuracy depends on proper In-Reply-To headers; broken threading in some email clients may cause incorrect context grouping","Cannot access email attachments or embedded content — analysis limited to text body and metadata","Privacy-sensitive: requires full email read access, creating trust and compliance concerns for regulated industries","Search activity monitoring raises significant privacy concerns — requires explicit user consent and transparent data handling","Intent inference accuracy depends on search query quality; ambiguous or short queries may lead to irrelevant suggestions","Cannot access search results behind paywalls or authentication walls; limited to publicly accessible content","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":"2026-05-24T12:16:31.857Z","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=martin","compare_url":"https://unfragile.ai/compare?artifact=martin"}},"signature":"ZG2wLAHo3a9dftUDRuWT8Ei9AF1xYQziL+V57/eoqzBXzT0R8cIUlR2Y1Uu0dha9K2qYOb04Ddv0VIP+09M6BQ==","signedAt":"2026-06-22T07:55:46.823Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/martin","artifact":"https://unfragile.ai/martin","verify":"https://unfragile.ai/api/v1/verify?slug=martin","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"}}