{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_howsthisgoing","slug":"howsthisgoing","name":"HowsThisGoing","type":"product","url":"https://howsthisgoing.com","page_url":"https://unfragile.ai/howsthisgoing","categories":["automation"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_howsthisgoing__cap_0","uri":"capability://memory.knowledge.slack.channel.conversation.ingestion.and.indexing","name":"slack channel conversation ingestion and indexing","description":"Automatically connects to Slack workspace via OAuth and continuously indexes message history from specified channels, storing conversation threads with metadata (timestamps, authors, reaction data) in a queryable vector database. Uses Slack's Web API to fetch paginated message history and maintains incremental sync to capture new messages without reprocessing entire channels.","intents":["I want to automatically capture all team discussions without manually copying content elsewhere","I need to ensure the AI has access to recent conversation context without manual data entry","I want to track which channels have rich discussion vs. sparse activity"],"best_for":["Remote teams with active Slack workspaces and channel-based communication patterns","Organizations where conversation history is the primary source of truth for project status"],"limitations":["Only indexes channels the bot has been explicitly invited to; private channels require separate authorization per channel","Message indexing limited by Slack API rate limits (60 requests per minute for most endpoints); large workspaces with 10k+ messages may experience delays","Does not capture threaded replies in older Slack workspaces if thread history is not explicitly fetched","Slack's free tier limits message history to 90 days; teams on free plans will have incomplete historical context"],"requires":["Slack workspace with admin or app installation permissions","Active Slack workspace with at least 1-2 channels containing regular team communication","OAuth token with scopes: channels:read, chat:read, users:read"],"input_types":["Slack channel messages (text)","Message metadata (timestamps, user IDs, reaction counts)","Thread replies and message edits"],"output_types":["Indexed conversation vectors","Structured message metadata (author, timestamp, channel, thread context)"],"categories":["memory-knowledge","slack-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_howsthisgoing__cap_1","uri":"capability://data.processing.analysis.blocker.and.impediment.extraction.from.conversation.text","name":"blocker and impediment extraction from conversation text","description":"Applies NLP and LLM-based analysis to indexed Slack messages to identify and classify blockers, dependencies, and project impediments mentioned in natural conversation. Uses semantic pattern matching (e.g., 'waiting on', 'blocked by', 'can't proceed until') combined with LLM inference to extract structured blocker objects with context, severity, and affected team members.","intents":["I want to automatically surface project blockers without reading every Slack message","I need to identify which team members are blocked and what's blocking them","I want to track blocker resolution over time without manual status meetings"],"best_for":["Teams with frequent, detailed Slack discussions about project status and blockers","Engineering teams where blockers are discussed in channels rather than tracked in separate systems"],"limitations":["Accuracy depends heavily on conversation quality and explicitness; implicit blockers ('we're slow on X') may be missed vs. explicit ones ('blocked on API response')","Requires sufficient context in messages; sparse channels with one-word responses will produce low-quality blocker extraction","May generate false positives if team members discuss hypothetical blockers or past issues without clear resolution status","Cannot distinguish between resolved and ongoing blockers without explicit resolution language in subsequent messages"],"requires":["Slack channels with substantive team discussion (minimum ~5-10 messages per day for meaningful signal)","Team communication style that explicitly mentions blockers or dependencies"],"input_types":["Indexed Slack conversation text","Message context (author, timestamp, thread structure)"],"output_types":["Structured blocker objects: {blocker_text, severity, affected_team_members, mentioned_timestamp, resolution_status}","Blocker summary reports grouped by project or team"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_howsthisgoing__cap_2","uri":"capability://data.processing.analysis.team.sentiment.and.momentum.analysis.from.conversation.tone","name":"team sentiment and momentum analysis from conversation tone","description":"Analyzes the emotional tone, urgency indicators, and momentum signals in Slack conversations using sentiment analysis and linguistic markers (exclamation points, capitalization, urgency words like 'ASAP', 'critical'). Aggregates sentiment across channels and time periods to produce team morale and project momentum scores, identifying conversations with high stress or low engagement.","intents":["I want to gauge team morale and stress levels without conducting surveys","I need to identify which projects are moving forward vs. stalled based on conversation energy","I want early warning signals if team sentiment is declining"],"best_for":["Remote teams where sentiment is harder to gauge without in-person interaction","Organizations wanting to proactively monitor team health without formal pulse surveys"],"limitations":["Sentiment analysis is notoriously unreliable for sarcasm, context-dependent language, and technical discussions that may sound negative but are routine problem-solving","Cannot distinguish between healthy debate/disagreement and genuine team conflict","Aggregated sentiment scores may mask important outliers (e.g., one person's burnout hidden in overall positive team sentiment)","Requires sufficient message volume per channel; channels with <5 messages per week will have noisy sentiment signals"],"requires":["Slack channels with regular team communication","Minimum 1-2 weeks of message history for meaningful trend analysis"],"input_types":["Indexed Slack conversation text","Message metadata (timestamps, author)"],"output_types":["Sentiment scores per channel (positive/neutral/negative)","Momentum indicators (trending up/down/stable)","Urgency/stress level indicators"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_howsthisgoing__cap_3","uri":"capability://tool.use.integration.slack.native.insight.delivery.and.notifications","name":"slack-native insight delivery and notifications","description":"Delivers AI-generated insights (blockers, sentiment, momentum) directly into Slack via bot messages, threaded replies, and scheduled summaries. Uses Slack's message formatting API to create rich, interactive summaries with action buttons for acknowledging blockers or drilling into details; supports both real-time notifications and scheduled digest delivery (daily/weekly summaries).","intents":["I want insights delivered where my team already works without context-switching to a separate dashboard","I need to notify specific team members when blockers affecting them are identified","I want to receive weekly project momentum summaries without leaving Slack"],"best_for":["Teams that live in Slack and want to minimize tool sprawl","Organizations with async-first communication where scheduled summaries are more valuable than real-time alerts"],"limitations":["Slack message formatting limitations restrict visualization complexity; cannot embed interactive dashboards or detailed charts","Real-time notifications may create alert fatigue if blocker detection is overly sensitive; requires tuning to avoid false positives","Threaded replies are limited to 25 messages per thread in Slack's UI; long insight summaries may be truncated","Scheduled summaries require timezone configuration; global teams may receive summaries at inconvenient times"],"requires":["Slack bot with permissions: chat:write, chat:write.public, chat:write.customize","Configured channels or user IDs for insight delivery"],"input_types":["Structured blocker objects","Sentiment and momentum scores","Time period for summary generation"],"output_types":["Slack bot messages with formatted text and action buttons","Threaded replies with detailed context","Scheduled digest messages (daily/weekly)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_howsthisgoing__cap_4","uri":"capability://data.processing.analysis.project.and.team.member.context.extraction.from.conversations","name":"project and team member context extraction from conversations","description":"Identifies and maps project names, team member mentions, and organizational structure from Slack conversations using entity recognition and co-occurrence analysis. Builds a dynamic knowledge graph of which team members are involved in which projects, who is blocked on what, and which projects are mentioned most frequently, without requiring manual configuration.","intents":["I want to automatically understand which projects are being discussed without manual tagging","I need to see which team members are involved in each project based on actual conversation patterns","I want to track project mentions and activity levels over time"],"best_for":["Organizations with multiple concurrent projects discussed across shared Slack channels","Teams without formal project tracking systems who rely on Slack as the source of truth"],"limitations":["Entity recognition may conflate similar project names or miss acronyms/informal project names if not explicitly mentioned","Requires sufficient mention frequency; projects discussed infrequently may not be reliably extracted","Cannot distinguish between active project work vs. historical discussion of past projects without temporal analysis","Team member mentions via @username are reliable, but informal references ('the frontend team') may be missed"],"requires":["Slack channels with regular project discussion and team member mentions","Minimum 2-4 weeks of message history for reliable entity mapping"],"input_types":["Indexed Slack conversation text","Slack user directory (for @mention resolution)"],"output_types":["Project entity list with mention frequency","Team member-to-project mappings","Co-occurrence graph (which projects are discussed together)"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_howsthisgoing__cap_5","uri":"capability://text.generation.language.conversation.based.status.report.generation","name":"conversation-based status report generation","description":"Synthesizes AI-generated status reports from indexed Slack conversations, extracting accomplishments, in-progress work, blockers, and next steps without requiring manual input from team members. Uses LLM-based summarization to produce narrative status updates grouped by project or team, with citations back to original Slack messages for verification.","intents":["I want to generate status reports from Slack conversations without asking team members to write them","I need to create executive summaries of project progress for stakeholders","I want to reduce the overhead of status meeting preparation"],"best_for":["Teams with active Slack discussions about work progress","Organizations that need regular status reporting but want to minimize manual overhead"],"limitations":["Report quality depends entirely on conversation richness; teams that discuss work primarily in DMs or external tools will have incomplete reports","LLM summarization may miss important context or misrepresent priorities if not explicitly stated in conversations","Cannot capture work done outside Slack (e.g., code commits, design work) unless explicitly discussed in channels","Reports may be biased toward high-volume communicators; quiet team members' contributions may be underrepresented"],"requires":["Slack channels with substantive discussion of work progress (minimum ~10-20 messages per day per project)","1-2 weeks of recent message history for meaningful status synthesis"],"input_types":["Indexed Slack conversation text","Project/team context mappings","Time period for report generation"],"output_types":["Narrative status reports (text)","Structured status objects: {accomplishments, in_progress, blockers, next_steps, citations}","Executive summaries with key metrics"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_howsthisgoing__cap_6","uri":"capability://safety.moderation.privacy.scoped.conversation.analysis.with.channel.level.access.control","name":"privacy-scoped conversation analysis with channel-level access control","description":"Implements granular access controls at the channel level, allowing workspace admins to specify which channels the bot can index and analyze. Stores conversation data with encryption at rest and implements audit logging for all data access. Provides data retention policies and deletion capabilities to comply with privacy requirements.","intents":["I want to use HowsThisGoing for public project channels but exclude sensitive channels","I need to ensure compliance with data privacy policies and audit requirements","I want to delete conversation data after a certain retention period"],"best_for":["Organizations with sensitive information in Slack (healthcare, finance, legal)","Teams requiring audit trails and data governance compliance"],"limitations":["Channel-level access control is binary; cannot exclude specific message types or keywords within a channel","Encryption at rest does not prevent analysis of decrypted data in memory; sensitive information can still be extracted if channel is authorized","Audit logging adds latency and storage overhead; high-volume workspaces may see performance degradation","Data deletion is permanent; cannot recover deleted conversation context for historical analysis"],"requires":["Slack workspace admin permissions to configure channel access","Compliance framework documentation (GDPR, HIPAA, SOC2, etc.) if required"],"input_types":["Channel access control lists","Data retention policies","Deletion requests"],"output_types":["Audit logs (JSON format)","Access control configuration","Data deletion confirmations"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_howsthisgoing__cap_7","uri":"capability://automation.workflow.freemium.tier.with.usage.based.scaling","name":"freemium tier with usage-based scaling","description":"Offers a free tier supporting small teams (up to 5 team members, 2 channels, 30-day message history) with limited insight generation (weekly summaries only), scaling to paid tiers with higher channel limits, longer history retention, real-time notifications, and advanced analytics. Implements usage metering at the message-indexing and LLM-inference level to track consumption.","intents":["I want to test HowsThisGoing with my team before committing to a paid plan","I need a solution that scales with my team size without overcommitting to enterprise pricing","I want to understand pricing before adoption"],"best_for":["Small teams and startups evaluating workflow automation tools","Organizations wanting to pilot before full rollout"],"limitations":["Free tier limitations (2 channels, 30-day history) may be insufficient for teams with distributed projects across multiple channels","Weekly-only summaries on free tier limit real-time blocker visibility","Upgrade friction: teams may hit free tier limits and face sudden pricing surprises","Usage metering may be opaque; teams may not understand what drives costs until first bill"],"requires":["Slack workspace with at least 1-2 active channels","No credit card required for free tier"],"input_types":["Team size","Channel count","Message volume"],"output_types":["Pricing tier recommendations","Usage reports and cost projections"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":41,"verified":false,"data_access_risk":"high","permissions":["Slack workspace with admin or app installation permissions","Active Slack workspace with at least 1-2 channels containing regular team communication","OAuth token with scopes: channels:read, chat:read, users:read","Slack channels with substantive team discussion (minimum ~5-10 messages per day for meaningful signal)","Team communication style that explicitly mentions blockers or dependencies","Slack channels with regular team communication","Minimum 1-2 weeks of message history for meaningful trend analysis","Slack bot with permissions: chat:write, chat:write.public, chat:write.customize","Configured channels or user IDs for insight delivery","Slack channels with regular project discussion and team member mentions"],"failure_modes":["Only indexes channels the bot has been explicitly invited to; private channels require separate authorization per channel","Message indexing limited by Slack API rate limits (60 requests per minute for most endpoints); large workspaces with 10k+ messages may experience delays","Does not capture threaded replies in older Slack workspaces if thread history is not explicitly fetched","Slack's free tier limits message history to 90 days; teams on free plans will have incomplete historical context","Accuracy depends heavily on conversation quality and explicitness; implicit blockers ('we're slow on X') may be missed vs. explicit ones ('blocked on API response')","Requires sufficient context in messages; sparse channels with one-word responses will produce low-quality blocker extraction","May generate false positives if team members discuss hypothetical blockers or past issues without clear resolution status","Cannot distinguish between resolved and ongoing blockers without explicit resolution language in subsequent messages","Sentiment analysis is notoriously unreliable for sarcasm, context-dependent language, and technical discussions that may sound negative but are routine problem-solving","Cannot distinguish between healthy debate/disagreement and genuine team conflict","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.35833333333333334,"quality":0.7200000000000001,"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":"2026-05-24T12:16:31.445Z","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=howsthisgoing","compare_url":"https://unfragile.ai/compare?artifact=howsthisgoing"}},"signature":"ZxzLNDYI74TJzpeONCoIWWirA17jfqJCQ3DRdUprxx7wKmlO/rxaJxYVM9/zBzPXAxiaGVe0hhluLWGLzTI2CQ==","signedAt":"2026-06-21T09:02:37.506Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/howsthisgoing","artifact":"https://unfragile.ai/howsthisgoing","verify":"https://unfragile.ai/api/v1/verify?slug=howsthisgoing","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"}}