{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_autoresponder-ai","slug":"autoresponder-ai","name":"AutoResponder.ai","type":"product","url":"https://www.autoresponder.ai","page_url":"https://unfragile.ai/autoresponder-ai","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_autoresponder-ai__cap_0","uri":"capability://tool.use.integration.multi.platform.message.ingestion.and.routing","name":"multi-platform message ingestion and routing","description":"Automatically receives incoming messages from WhatsApp, Facebook Messenger, Instagram, and email through unified webhook/API integrations, normalizing message metadata (sender, timestamp, platform origin) into a common internal format before routing to the AI response generation pipeline. Uses platform-specific SDKs and OAuth token management to maintain authenticated connections without exposing credentials in the application layer.","intents":["I want to handle customer messages from multiple channels without manually checking each platform separately","I need incoming messages from different platforms to be processed through a single automation workflow","I want to maintain audit trails showing which platform each message originated from"],"best_for":["small e-commerce teams managing sales inquiries across multiple social channels","service-based businesses with customers using different preferred communication methods","support departments consolidating ticket intake from email, WhatsApp, and social media"],"limitations":["Platform API rate limits may cause message processing delays during traffic spikes (e.g., WhatsApp Business API limits ~1000 messages/second per account)","Webhook delivery is asynchronous—no guarantee of sub-second message arrival at AutoResponder servers","Platform-specific message formats (rich media, buttons, interactive elements) may not normalize cleanly across all channels"],"requires":["Active business account on at least one supported platform (WhatsApp Business, Facebook Business, Instagram Business, or email server)","API credentials/OAuth tokens for each platform to be configured in AutoResponder dashboard","Webhook URL whitelisting on platform side (varies by platform, typically 24-48 hour approval)"],"input_types":["text messages","media attachments (images, documents)","structured message metadata (sender ID, timestamp, thread context)"],"output_types":["normalized message object with platform-agnostic schema","routing decision (auto-reply vs escalation vs human review)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_1","uri":"capability://text.generation.language.context.aware.ai.response.generation.with.tone.adaptation","name":"context-aware ai response generation with tone adaptation","description":"Analyzes incoming message content, sender history (if available), and conversation context to generate contextually appropriate replies using a fine-tuned or prompt-engineered LLM (likely GPT-3.5/4 or similar). Applies tone modulation based on detected sentiment (frustrated customer vs. casual inquiry) and message classification (support request vs. sales lead vs. out-of-office notification) to avoid generic robotic responses. Uses prompt templates with variable substitution for business name, sender name, and context snippets.","intents":["I want auto-replies that sound natural and match the tone of the incoming message, not robotic","I need the AI to understand if a customer is angry vs. casual and adjust response tone accordingly","I want replies that reference the customer's specific issue or question, not generic templates"],"best_for":["e-commerce teams wanting to acknowledge orders and shipping inquiries with personalized language","service businesses needing intelligent triage responses that acknowledge customer urgency","support teams handling mixed inquiry types (billing, technical, general) with appropriate response styles"],"limitations":["Free tier likely uses generic prompt templates with minimal customization—responses may feel generic despite tone adaptation","No information on how the system handles complex, multi-part customer issues—may generate oversimplified responses requiring escalation","Sentiment detection accuracy depends on message length and clarity; sarcasm, cultural context, and ambiguous language may be misclassified","No explicit mention of brand voice training—responses may not reflect unique company personality or terminology"],"requires":["API key for underlying LLM provider (OpenAI, Anthropic, or proprietary model)","Message content in text format (minimum ~10 characters for meaningful sentiment analysis)","Optional: historical conversation context or customer profile data for improved personalization"],"input_types":["incoming message text","sender metadata (name, previous interaction history if available)","conversation thread context (prior messages in same thread)"],"output_types":["generated response text (typically 1-3 sentences)","confidence score for response appropriateness","tone classification (friendly, professional, urgent, etc.)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_2","uri":"capability://automation.workflow.automated.response.delivery.with.platform.native.formatting","name":"automated response delivery with platform-native formatting","description":"Takes generated AI response text and formats it according to platform-specific requirements (WhatsApp message length limits, Facebook Messenger rich text, Instagram DM character limits, email headers/footers) before delivering through the appropriate platform API. Handles platform-specific constraints like character limits, supported formatting (bold, italics, links), and media attachment compatibility. Implements retry logic with exponential backoff for failed deliveries and maintains delivery status logs.","intents":["I want auto-replies to be sent immediately without manual formatting for each platform","I need to ensure responses comply with platform-specific character limits and formatting rules","I want visibility into which replies were successfully delivered vs. failed"],"best_for":["teams managing high-volume customer inquiries across multiple platforms simultaneously","businesses needing guaranteed delivery tracking for compliance or audit purposes","support teams that need to know when auto-replies fail so they can escalate manually"],"limitations":["Platform API outages or rate limiting may cause delivery delays—no guaranteed delivery SLA mentioned","Rich formatting (buttons, quick replies, media) may not be supported in free tier, limiting response expressiveness","Delivery status tracking is only as reliable as platform webhook callbacks—some platforms have inconsistent delivery confirmation","No mention of scheduling or delay options—responses are sent immediately, which may not be appropriate for all use cases (e.g., out-of-office hours)"],"requires":["Active API credentials for each platform where responses will be sent","Generated response text from prior AI generation step","Platform-specific sender IDs or phone numbers configured in AutoResponder"],"input_types":["generated response text","target platform identifier","recipient ID/phone number/email address"],"output_types":["delivery confirmation (success/failure status)","platform-specific message ID for tracking","delivery timestamp and retry attempt count"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_3","uri":"capability://memory.knowledge.conversation.thread.context.preservation.and.escalation.routing","name":"conversation thread context preservation and escalation routing","description":"Maintains conversation history and thread context for each customer across multiple interactions, allowing the AI response generator to reference prior messages and understand conversation continuity. Implements escalation logic to route complex or unresolved issues to human agents based on configurable rules (e.g., if confidence score < threshold, if customer mentions specific keywords like 'refund' or 'urgent', if conversation has been ongoing for >N messages). Stores conversation state in a database with indexed lookups by sender ID and platform.","intents":["I want the AI to understand the full conversation history, not just the latest message","I need complex customer issues to be automatically escalated to a human agent instead of getting a generic auto-reply","I want to set rules for when auto-replies should NOT be sent and instead wait for human review"],"best_for":["support teams handling mixed-complexity inquiries where some need human judgment","businesses wanting to avoid embarrassing auto-reply failures on sensitive issues (refunds, complaints, account issues)","teams needing conversation continuity across multiple customer touchpoints"],"limitations":["Escalation rules are likely static/rule-based rather than ML-driven—may miss nuanced cases requiring human review","No mention of how long conversation history is retained—older messages may be pruned, losing context for long-running issues","Escalation routing destination (human agent queue, email, Slack) not clearly specified—may require manual configuration","No information on escalation SLA or notification mechanism—agents may not be alerted immediately when escalation occurs"],"requires":["Database or persistent storage to maintain conversation history (likely included in paid tiers)","Configurable escalation rules (threshold scores, keyword lists, message count limits)","Integration with human agent queue or ticketing system for escalation destination"],"input_types":["incoming message text","sender ID for conversation history lookup","prior conversation messages (retrieved from database)"],"output_types":["conversation context object with full thread history","escalation decision (auto-reply vs. escalate)","escalation reason/metadata for agent review"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_4","uri":"capability://text.generation.language.brand.voice.customization.and.response.templating","name":"brand voice customization and response templating","description":"Allows users to define brand voice guidelines, tone preferences, and response templates that the AI uses to generate contextually appropriate replies. Likely implemented as a system prompt or fine-tuning data that shapes the LLM's output style. May include template variables for dynamic content injection (customer name, order number, business name). Free tier likely offers limited customization (generic templates), while paid tiers enable custom brand voice training or detailed prompt engineering.","intents":["I want auto-replies to sound like my brand, not generic AI","I need to enforce consistent tone and terminology across all auto-replies","I want to include specific information (order numbers, links, contact details) in auto-replies without manual editing"],"best_for":["brands with strong voice/personality wanting to maintain consistency in automated responses","businesses needing to include dynamic information (order details, tracking links) in auto-replies","teams wanting to avoid generic-sounding responses that damage brand perception"],"limitations":["Free tier likely offers minimal customization—responses may feel generic and not reflect brand voice","No information on how brand voice is trained or updated—may require manual prompt engineering or fine-tuning","Template variable support unclear—may be limited to basic substitutions (name, order ID) rather than complex logic","No mention of A/B testing or performance metrics for different brand voice styles"],"requires":["Brand voice guidelines or examples provided by user (text descriptions or sample responses)","Template variables defined for dynamic content (customer name, order number, business name, etc.)","Paid tier subscription for advanced customization (free tier likely has limited options)"],"input_types":["brand voice description or guidelines (text)","sample response templates (text with variable placeholders)","customer/order data for template variable substitution"],"output_types":["customized response text reflecting brand voice","template with substituted variables"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_5","uri":"capability://planning.reasoning.message.classification.and.intent.detection","name":"message classification and intent detection","description":"Automatically categorizes incoming messages into predefined classes (support request, sales inquiry, complaint, out-of-office notification, spam, etc.) using text classification (likely rule-based keyword matching or lightweight ML model). Uses detected intent to determine appropriate response strategy (e.g., sales inquiries get promotional response, complaints get escalation, out-of-office notifications get acknowledgment). Classification results inform both response generation and escalation routing decisions.","intents":["I want different types of customer messages to get different types of responses","I need to automatically identify complaints or urgent issues so they can be escalated","I want to route sales inquiries differently than support requests"],"best_for":["businesses receiving mixed message types (sales, support, general inquiries) that need different handling","support teams wanting to prioritize urgent or complaint messages for faster human review","sales teams wanting to identify and respond to sales inquiries with appropriate messaging"],"limitations":["Classification accuracy depends on message clarity and length—ambiguous or very short messages may be misclassified","Predefined classification categories may not match all business use cases—customization options unclear","No mention of confidence scores or fallback handling for uncertain classifications","Language support unclear—may only work well for English, limiting international use"],"requires":["Predefined message classification schema (support, sales, complaint, etc.)","Training data or keyword lists for each classification category (may be provided by AutoResponder)","Minimum message length for reliable classification (typically 10+ characters)"],"input_types":["incoming message text","optional: sender metadata or conversation history"],"output_types":["message classification/intent label","confidence score for classification","recommended response strategy"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_6","uri":"capability://automation.workflow.out.of.office.and.scheduled.response.automation","name":"out-of-office and scheduled response automation","description":"Enables users to configure automatic responses for specific time periods (e.g., weekends, holidays, vacation) or based on business hours settings. Likely uses scheduled jobs or time-based rules to activate/deactivate auto-reply behavior. May include different response templates for out-of-office scenarios (e.g., 'We'll respond Monday') vs. normal business hours. Stores schedule configuration and applies time-zone-aware logic for multi-region teams.","intents":["I want different auto-replies during business hours vs. after hours","I want to set up vacation auto-replies that activate on specific dates","I need to acknowledge messages received outside business hours without committing to immediate response"],"best_for":["small teams or solo entrepreneurs wanting to manage customer expectations outside business hours","service businesses with defined operating hours needing to set expectations for response timing","teams taking vacations or holidays wanting to acknowledge messages without manual intervention"],"limitations":["Schedule configuration may be limited to simple time ranges—no mention of complex scheduling (e.g., different hours per day of week)","Time-zone handling unclear—may not work well for distributed teams across multiple regions","No mention of how scheduled responses interact with escalation logic—urgent messages may still get out-of-office reply","Switching between schedules may have latency—messages arriving during transition periods may get wrong response"],"requires":["Business hours or schedule configuration in AutoResponder dashboard","Separate response templates for out-of-office scenarios","Time-zone setting for accurate schedule application"],"input_types":["schedule configuration (start time, end time, days of week)","out-of-office response template","incoming message timestamp"],"output_types":["scheduled response text (if within out-of-office period)","schedule status (active/inactive)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_7","uri":"capability://data.processing.analysis.analytics.and.response.performance.tracking","name":"analytics and response performance tracking","description":"Tracks metrics on auto-reply performance including delivery rates, response times, customer satisfaction signals (if available), and escalation rates. Likely provides dashboards showing message volume, auto-reply vs. escalation breakdown, and platform-specific metrics. May include A/B testing capabilities to compare different response templates or tone styles. Data is aggregated and stored for historical analysis and trend identification.","intents":["I want to see how many messages are being auto-replied vs. escalated","I need to understand if auto-replies are actually reducing response time","I want to identify which response templates or tones perform best"],"best_for":["teams wanting to measure ROI of auto-reply automation","businesses optimizing response strategies based on performance data","support managers needing visibility into automation effectiveness"],"limitations":["Customer satisfaction metrics likely not available—no mention of feedback collection or sentiment analysis on responses","A/B testing capabilities unclear—may not support statistical significance testing or automated winner selection","Analytics retention period not specified—historical data may be limited to recent period (e.g., 30 days)","No mention of custom metrics or integration with external analytics platforms"],"requires":["Active auto-reply usage to generate metrics","Dashboard access in AutoResponder UI","Optional: integration with external analytics tools for deeper analysis"],"input_types":["auto-reply delivery events","escalation events","response generation metrics"],"output_types":["dashboard visualizations (charts, tables)","performance metrics (delivery rate, escalation rate, response time)","trend analysis and historical comparisons"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_8","uri":"capability://text.generation.language.multi.language.message.handling.and.response.generation","name":"multi-language message handling and response generation","description":"Detects the language of incoming messages and generates responses in the same language, or translates messages for processing if needed. Likely uses language detection library (e.g., langdetect, TextBlob) to identify message language, then routes to appropriate LLM or translation service. May support a limited set of languages (common ones like Spanish, French, German, Portuguese) with fallback to English for unsupported languages. Translation quality and language coverage unclear.","intents":["I want to handle customer messages in multiple languages without manually translating","I need auto-replies to be generated in the customer's language, not English","I want to serve international customers without language barriers"],"best_for":["e-commerce businesses serving international customers","global service providers needing to respond in customer's preferred language","teams without multilingual staff wanting to automate responses across languages"],"limitations":["Language detection accuracy depends on message length and clarity—short messages may be misidentified","Supported languages likely limited to major ones (Spanish, French, German, Portuguese, etc.)—less common languages may fall back to English","Translation quality varies by language pair—some languages may have poor translation quality","No mention of cultural context or localization—responses may be grammatically correct but culturally inappropriate","Language-specific tone adaptation may be limited—AI may not understand cultural communication norms"],"requires":["Incoming message in supported language (or English as fallback)","LLM or translation service with multi-language support","Language detection library"],"input_types":["message text in any supported language","optional: language hint or customer language preference"],"output_types":["detected language identifier","response text in detected language"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_autoresponder-ai__cap_9","uri":"capability://tool.use.integration.api.based.response.customization.and.webhook.integration","name":"api-based response customization and webhook integration","description":"Exposes APIs or webhooks allowing developers to customize response generation logic, inject custom data, or integrate with external systems (CRM, ticketing, inventory). May support pre-generation hooks (to inject context before AI generation) and post-generation hooks (to modify or validate responses before delivery). Enables advanced use cases like pulling customer history from CRM, checking inventory before responding to product inquiries, or logging responses to external systems.","intents":["I want to inject custom data from my CRM into auto-reply context","I need to check inventory or order status before generating a response","I want to log all auto-replies to my ticketing system for audit purposes"],"best_for":["developers building custom integrations with existing business systems","teams needing to inject real-time data (inventory, order status, customer history) into responses","enterprises requiring audit logging and compliance tracking"],"limitations":["API documentation and webhook support unclear—may be limited to paid tiers","Webhook delivery reliability depends on AutoResponder infrastructure—no SLA mentioned","Custom logic execution may add latency to response generation—no performance guarantees","Error handling for failed webhook calls unclear—may cause response generation to fail or timeout"],"requires":["API key or authentication token for AutoResponder API","Webhook endpoint URL for receiving events (must be publicly accessible)","Understanding of AutoResponder API schema and webhook payload format"],"input_types":["webhook event (incoming message, pre-generation, post-generation)","message context and metadata","generated response (for post-generation hooks)"],"output_types":["custom context data (from pre-generation hook)","modified response (from post-generation hook)","webhook acknowledgment"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":44,"verified":false,"data_access_risk":"high","permissions":["Active business account on at least one supported platform (WhatsApp Business, Facebook Business, Instagram Business, or email server)","API credentials/OAuth tokens for each platform to be configured in AutoResponder dashboard","Webhook URL whitelisting on platform side (varies by platform, typically 24-48 hour approval)","API key for underlying LLM provider (OpenAI, Anthropic, or proprietary model)","Message content in text format (minimum ~10 characters for meaningful sentiment analysis)","Optional: historical conversation context or customer profile data for improved personalization","Active API credentials for each platform where responses will be sent","Generated response text from prior AI generation step","Platform-specific sender IDs or phone numbers configured in AutoResponder","Database or persistent storage to maintain conversation history (likely included in paid tiers)"],"failure_modes":["Platform API rate limits may cause message processing delays during traffic spikes (e.g., WhatsApp Business API limits ~1000 messages/second per account)","Webhook delivery is asynchronous—no guarantee of sub-second message arrival at AutoResponder servers","Platform-specific message formats (rich media, buttons, interactive elements) may not normalize cleanly across all channels","Free tier likely uses generic prompt templates with minimal customization—responses may feel generic despite tone adaptation","No information on how the system handles complex, multi-part customer issues—may generate oversimplified responses requiring escalation","Sentiment detection accuracy depends on message length and clarity; sarcasm, cultural context, and ambiguous language may be misclassified","No explicit mention of brand voice training—responses may not reflect unique company personality or terminology","Platform API outages or rate limiting may cause delivery delays—no guaranteed delivery SLA mentioned","Rich formatting (buttons, quick replies, media) may not be supported in free tier, limiting response expressiveness","Delivery status tracking is only as reliable as platform webhook callbacks—some platforms have inconsistent delivery confirmation","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.78,"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":"2026-05-24T12:16:29.133Z","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=autoresponder-ai","compare_url":"https://unfragile.ai/compare?artifact=autoresponder-ai"}},"signature":"Z5byj/nkHY20y4BmaaT5G6fkqjhGVRaim88idoHvB52k+UBm3y5+iEVBbcwVcE+ACdMb0iyIQIDi8I8zMDq0Dw==","signedAt":"2026-06-23T06:44:55.343Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/autoresponder-ai","artifact":"https://unfragile.ai/autoresponder-ai","verify":"https://unfragile.ai/api/v1/verify?slug=autoresponder-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"}}