Muse vs Martin

Agent access

1. ai-native userPlug MCP servers into this product so it can use their tools

   weight 3 · round drawn
   Muse—none0/10

   No evidence Muse supports plugging in external MCP servers; it only describes its agent building its own tools internally, which is a different mechanism.

   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”
   • [claimed-docs] “Muse has its own computer, with a file system and a terminal, so it can write its own code and build the tools a task needs.”

   proof ↗⚑ flag

   Martin—none0/10

   Martin's docs describe a fixed set of built-in integrations (calendar, email, Slack, todos, notes) but there is no mention of MCP protocol support or any way for users to plug in arbitrary MCP servers for Martin to use as tools.

   • [claimed-docs] “Have Martin read, create, and update events in your calendar.”
   • [claimed-docs] “Have Martin read, draft, and reply to emails in your inbox.”
   • [claimed-docs] “Have Martin read and send messages in Slack from your account.”
   • [claimed-docs] “You can tell Martin to add, edit, and check off your to-dos on your behalf from any interface.”
   • [claimed-docs] “You can tell Martin to read, add, and edit your notes from any interface.”

   proof ↗⚑ flag

2. ai-native userDrive the product through a documented public API

   weight 3 · round drawn
   Muse—none0/10

   No evidence of a documented public API for developers to programmatically drive Muse; all evidence describes end-user chat/app features and internal agent behavior, not an external API surface.

   ⚑ flag

   Martin—none0/10

   Martin is a personal-assistant product controlled via chat/email/Slack/phone interfaces, but there is no evidence of a documented public API for developers to programmatically drive it — probes for OpenAPI/Swagger specs all returned 404. missing for 10: a documented public API, SDK, or endpoint reference; any developer-facing API authentication or usage docs.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.trymartin.com/openapi.json, https://docs.trymartin.com/swagger.json, https://docs.tryma…”

   proof ↗⚑ flag

3. ai-native userIssue scoped/least-privilege API credentials for an agent

   weight 2 · round drawn
   Muse—none0/10

   Evidence shows Muse has approval cards, activity logs, and permission tracking for connected accounts, but nothing about issuing scoped or least-privilege API credentials/tokens for an agent to use with external services — this is a consumer personal-agent product, not a developer credential-management tool.

   ⚑ flag

   Martin—none0/10

   Martin is a personal assistant that connects to full-access integrations (email, calendar, Slack) but there is no evidence of scoped or least-privilege credential issuance, API key management, or granular permissioning for agent access — no OpenAPI/API docs even exist per probe results.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.trymartin.com/openapi.json, https://docs.trymartin.com/swagger.json, https://docs.tryma…”
   • [claimed-docs] “Once connected, you can tell Martin to read, draft, and reply to emails on your behalf.”
   • [claimed-docs] “Once connected, you can tell Martin to read, send, and reply to Slack messages on your behalf.”

   proof ↗⚑ flag

4. ai-native userBuild against official SDKs

   weight 2 · round drawn
   Muse—none0/10

   No evidence of any official SDK for developers to build against; evidence only covers end-user features (avatars, goals, side chats, agent building its own tools) rather than a developer-facing SDK.

   ⚑ flag

   Martin—none0/10

   Martin's evidence pack covers only end-user integrations (calendar, email, Slack, etc.) and consumer interfaces, with no mention of an SDK, API, or developer library; probes for an OpenAPI/Swagger spec all returned 404s, indicating no public API/SDK surface exists to build against.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.trymartin.com/openapi.json, https://docs.trymartin.com/swagger.json, https://docs.tryma…”
   • [claimed-docs] “Martin is reachable through all your communication channels, including phone, SMS, WhatsApp, email, and Slack.”

   proof ↗⚑ flag

Agentic features

1. ai-native userGet AI-generated insights and suggestions from my data inside the product

   weight 2 · round to Martin
   Muse~partialclaimed5/10

   Muse links personal data sources (email, calendar, social, health, finances) and proactively tracks tasks/goals, implying some data-driven suggestions, but the evidence never explicitly describes AI-generated insights or recommendations derived from that data—most documentation focuses on agentic task execution and tool-building rather than analytic insight generation. missing for 10: explicit description of insight/recommendation generation from user data, independent hands-on validation of this specific capability.

   • [claimed-docs] “Link your email, calendar, Instagram, Facebook, health and fitness data, and finances.”
   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”
   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”

   proof ↗⚑ flag

   Martin~partialclaimed6/10

   Martin generates daily/weekly briefings synthesized from your calendar and inbox data, proactively drafts emails, and triages/labels emails with follow-up suggestions—all forms of AI-generated insights/suggestions surfaced inside the product. However, these are framed as autonomous actions rather than an explicit 'insights' or analytics layer, and there's no dedicated dashboard-style insight generation from broader personal data. Missing for 10: no independent/hands-on evidence corroborating quality of the 'insight' content itself, and no explicit analytics/trend-surfacing feature distinct from task-execution suggestions.

   • [claimed-docs] “Martin can send you daily or weekly briefings via email.”
   • [claimed-docs] “Martin can proactively draft emails for you and send them on your behalf.”
   • [claimed-docs] “Martin can automatically label your emails and take follow up actions on your behalf.”
   • [claimed-docs] “Martin syncs with multiple search engines to find you the most relevant information.”

   proof ↗⚑ flag

2. ai-native userSet up automations that run autonomously in the background

   weight 2 · round to Martin
   Muse!disputedcontradicted5/10

   Muse's Goals tab, activity log, and approval-card workflow (muse-docs-5, muse-docs-8, muse-docs-13) show first-party support for autonomous background task tracking and execution, and muse-docs-7 explicitly describes agents building tools for unattended tasks. However, an independent hands-on stress test found the agent's control plane starts timing out under load, exposing concrete failure points in its background-automation architecture (muse-comm-1), directly undercutting reliability claims for autonomous operation. missing for 10: independent confirmation that background automations run reliably at scale, more detail on scheduling/triggering mechanisms for autonomous runs.

   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”
   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”
   • [claimed-docs] “Tapping on your Muse avatar will show you its full activity log as well as permissions you’ve approved.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”
   • [community] “Blog post title/finding: the author stress-tested Meta Muse until its agent control plane started timing out, exposing failure points in the…”

   proof ↗⚑ flag

   Martin✓fullcommunity8/10

   Martin's docs describe multiple always-on background automations—daily/weekly briefings, proactive email drafting, email triage, wake-up calls, cc-to-schedule meeting booking, and custom multi-step shortcuts—all of which run without direct user prompting, and community reports (e.g., using Martin as a persistent background agent for todos) corroborate real autonomous use. Missing for 10: independent verification of scheduling/configuration UI for these background jobs and long-term reliability data beyond one HN comment about failure rates improving.

   • [claimed-docs] “Create custom shortcuts that trigger multi-step actions.”
   • [claimed-docs] “Martin can send you daily or weekly briefings via email.”
   • [claimed-docs] “Martin can proactively draft emails for you and send them on your behalf.”
   • [claimed-docs] “Martin can automatically label your emails and take follow up actions on your behalf.”
   • [claimed-docs] “Martin can call you at a specific time every morning to wake you up with the weather and your schedule.”
   • [claimed-docs] “Cc Martin on an email to schedule a meeting.”
   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”
   • [community] “A big piece of product feedback we got was 'I don't trust AI to take actions like sending texts/emails on my behalf if it's not 100% reliabl…”

   proof ↗⚑ flag

3. ai-native userDelegate tasks to a built-in AI assistant inside the product

   weight 3 · round drawn
   Muse✓fullclaimed8/10

   Muse is explicitly a built-in AI agent with its own compute, terminal, and file system to build tools and complete delegated tasks (goals, side chats, autonomous tool creation), with approval flows and activity logs for oversight. Missing for 10: independent hands-on verification of delegation quality beyond stress-test edge cases and more detail on task breadth/reliability at scale.

   • [claimed-docs] “Muse has its own computer, with a file system and a terminal, so it can write its own code and build the tools a task needs.”
   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”
   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”
   • [claimed-docs] “Tapping on your Muse avatar will show you its full activity log as well as permissions you’ve approved.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”

   proof ↗⚑ flag

   Martin✓fullcommunity8/10

   Martin IS the built-in AI assistant, and users delegate tasks to it across calendar, email, Slack, reminders, todos, notes, and multi-step shortcuts via chat, phone, SMS, email, or Slack, with hands-on community accounts confirming real task delegation and reliability improvements. missing for 10: independent quality/reliability benchmarking beyond anecdotal HN comments, and no evidence of failure-mode transparency or task-success metrics.

   • [claimed-docs] “Have Martin read, create, and update events in your calendar.”
   • [claimed-docs] “You can tell Martin to add, edit, and check off your to-dos on your behalf from any interface.”
   • [claimed-docs] “You can tell Martin to read, add, and edit your notes from any interface.”
   • [claimed-docs] “Create custom shortcuts that trigger multi-step actions.”
   • [claimed-docs] “Martin is reachable through all your communication channels, including phone, SMS, WhatsApp, email, and Slack.”
   • [community] “I’m impressed. I’ll probably cancel ChatGPT Pro subscription and switch to this... it’s handling some complicated requests correctly the fir…”
   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”
   • [community] “A big piece of product feedback we got was 'I don't trust AI to take actions like sending texts/emails on my behalf if it's not 100% reliabl…”

   proof ↗⚑ flag

4. ai-native userOperate the product with natural-language commands

   weight 2 · round to Martin
   Muse✓fullcommunity7/10

   Muse is designed around a chat interface where users talk to it in natural language to manage goals, tasks, and tool-building ('talk to it about these tasks in chat', side chats for topic-specific NL interaction). This is corroborated by first-party docs describing conversational control as the primary interface. missing for 10: independent hands-on confirmation of broad natural-language command coverage beyond goals/chat, and detail on command reliability at scale (comm-1 notes control-plane timeouts under stress).

   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”
   • [claimed-docs] “some people still wanted separate context for certain topics — which made sense as projects grew more complex. So we built side chats.”
   • [claimed-docs] “Tapping on your Muse avatar will show you its full activity log as well as permissions you’ve approved.”
   • [community] “Blog post title/finding: the author stress-tested Meta Muse until its agent control plane started timing out, exposing failure points in the…”

   proof ↗⚑ flag

   Martin✓fullcommunity8/10

   Martin is explicitly designed around natural-language commands across calendar, email, Slack, reminders, todos, notes, shortcuts, and phone/SMS interfaces, with docs and taglines like 'Text Jon my arrival time' or 'Cc Martin on an email to schedule a meeting' showing conversational control, and community feedback (HN) corroborates real usage of natural-language task delegation. missing for 10: independent hands-on benchmarking of NL command breadth/accuracy beyond anecdotal HN praise, and no formal API/spec confirming NLU robustness.

   • [claimed-docs] “Have Martin read, create, and update events in your calendar.”
   • [claimed-docs] “Tell Martin to remind you to do something, and he will ping you when the time comes.”
   • [claimed-docs] “You can tell Martin to add, edit, and check off your to-dos on your behalf from any interface.”
   • [claimed-docs] “Cc Martin on an email to schedule a meeting.”
   • [claimed-docs] “Text Jon my arrival time.”
   • [claimed-docs] “Martin is reachable through all your communication channels, including phone, SMS, WhatsApp, email, and Slack.”
   • [community] “I’m impressed. I’ll probably cancel ChatGPT Pro subscription and switch to this... it’s handling some complicated requests correctly the fir…”
   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”

   proof ↗⚑ flag

Api quality

1. ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)

   weight 2 · round drawn
   Muse—none0/10

   No evidence Muse publishes any machine-readable API spec (OpenAPI or equivalent) for developers; all evidence concerns end-user agent features, not a documented API surface.

   ⚑ flag

   Martin—none0/10

   Martin is a personal assistant product, not a developer API platform, but the axis of publishing a machine-readable API spec still applies as a fair question; the probe explicitly checked all standard OpenAPI/swagger paths and found only 404s, with no evidence of any downloadable spec.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.trymartin.com/openapi.json, https://docs.trymartin.com/swagger.json, https://docs.tryma…”

   proof ↗⚑ flag

Agent mode

1. power-userDelegate a multi-step task that the assistant works on autonomously in the background and returns for my review

   weight 3 · round to Martin
   Muse!disputedcontradicted6/10

   Muse's docs describe autonomous background task handling via the Goals tab, self-built tools, activity logs and approval cards for review — matching the delegate-and-review story [muse-docs-5][muse-docs-7][muse-docs-8][muse-docs-13][muse-docs-10]. However, an independent hands-on stress test found the agent's control plane timing out under load, exposing failure points in the very autonomous-task architecture being claimed [muse-comm-1], and another commenter notes the assistant is less capable than power-user expectations for building/using tools [muse-comm-2]. Missing for 10: reproducible evidence of reliable long-running multi-step task completion, and resolution/acknowledgment of the reported control-plane timeout issue.

   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”
   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”
   • [claimed-docs] “Tapping on your Muse avatar will show you its full activity log as well as permissions you’ve approved.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”
   • [claimed-docs] “structured approval cards with clear accept/reject actions, and secure storage for your credentials.”
   • [community] “Blog post title/finding: the author stress-tested Meta Muse until its agent control plane started timing out, exposing failure points in the…”
   • [community] “"I, too, have a personal agent but my friends using Muse or Instinct approach the functionality I use mine for quite easily... a sophisticat…”

   proof ↗⚑ flag

   Martin~partialcommunity7/10

   Martin's docs describe multiple background/autonomous capabilities (proactive email drafts, email triage with follow-up actions, cc-to-schedule meeting booking, custom multi-step shortcuts, daily briefings) that match delegating a task for autonomous background work with results delivered back to the user, and community posts corroborate real usage of the cloud-based agent for ongoing tasks (todos) across sessions. However, evidence doesn't clearly show a distinct 'review before finalizing' step for these autonomous actions (e.g., whether drafts are held for approval vs. auto-sent), and independent hands-on validation of the full delegate→work→review loop is thin. Missing for 10: explicit review/approval workflow evidence, and richer independent hands-on accounts of multi-step autonomous task completion.

   • [claimed-docs] “Create custom shortcuts that trigger multi-step actions.”
   • [claimed-docs] “Martin can send you daily or weekly briefings via email.”
   • [claimed-docs] “Martin can proactively draft emails for you and send them on your behalf.”
   • [claimed-docs] “Martin can automatically label your emails and take follow up actions on your behalf.”
   • [claimed-docs] “Cc Martin on an email to schedule a meeting.”
   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”
   • [community] “A big piece of product feedback we got was 'I don't trust AI to take actions like sending texts/emails on my behalf if it's not 100% reliabl…”

   proof ↗⚑ flag

2. power-userHave the assistant operate a web browser on my behalf to research and complete tasks on websites

   weight 3 · round drawn
   Muse—none0/10

   Evidence describes Muse having its own computer/terminal to build tools, task tracking (Goals tab), and permissions/approval cards, but nothing in the pack mentions browser automation or web navigation on the user's behalf. Missing for 10: any mention of browser control, web research execution, or site-task completion capability.

   ⚑ flag

   Martin—none0/10

   Martin's documented capabilities cover calendar, email, Slack, notes, reminders, todos, and search-engine lookups, but nothing in the evidence describes it operating a web browser, navigating websites, or completing multi-step tasks on arbitrary sites on the user's behalf.

   • [claimed-docs] “Martin syncs with multiple search engines to find you the most relevant information.”
   • [claimed-docs] “Have Martin read, create, and update events in your calendar.”
   • [claimed-docs] “Have Martin read, draft, and reply to emails in your inbox.”
   • [claimed-docs] “Have Martin read and send messages in Slack from your account.”
   • [claimed-docs] “Martin is reachable through all your communication channels, including phone, SMS, WhatsApp, email, and Slack.”

   proof ↗⚑ flag

3. power-userLet the assistant see and operate applications on my computer to complete work

   weight 2 · round to Martin
   Muse~partialclaimed4/10

   Muse describes having its own computer/terminal to build tools and links external accounts (email, calendar, social, health, finance) via structured approvals, which lets it act on the user's behalf across services, but the evidence never shows it seeing or directly operating applications on the user's own device (e.g., screen/GUI control) — it operates its own sandboxed environment, not the user's computer. Missing for 10: evidence of direct screen/GUI control of the user's local applications, and independent confirmation that this cross-app automation reliably works beyond linked-account integrations.

   • [claimed-docs] “Muse has its own computer, with a file system and a terminal, so it can write its own code and build the tools a task needs.”
   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”
   • [claimed-docs] “structured approval cards with clear accept/reject actions, and secure storage for your credentials.”
   • [claimed-docs] “Link your email, calendar, Instagram, Facebook, health and fitness data, and finances.”

   proof ↗⚑ flag

   Martin~partialcommunity5/10

   Martin can act inside specific applications via integrations (calendar, email, Slack, notes, to-dos) rather than through general screen/GUI-level control of arbitrary desktop apps — it operates named services via API-like connections, not a computer-use style visual agent. A desktop app exists (martin-comm-4) but evidence only shows it syncing to-dos, not controlling arbitrary programs. Missing for 10: evidence of generic screen/vision-based computer control, ability to operate arbitrary (non-integrated) applications, and independent hands-on proof of this broader 'operate any app' capability.

   • [claimed-docs] “Have Martin read, create, and update events in your calendar.”
   • [claimed-docs] “Have Martin read, draft, and reply to emails in your inbox.”
   • [claimed-docs] “Have Martin read and send messages in Slack from your account.”
   • [claimed-docs] “You can tell Martin to read, add, and edit your notes from any interface.”
   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”

   proof ↗⚑ flag

Tasks

1. power-userSchedule recurring or one-off tasks that run automatically and come back to me with results

   weight 2 · round to Martin
   Muse~partialcommunity5/10

   Muse's Goals tab and activity log suggest it can track and manage ongoing tasks with an audit trail of completed/planned actions, implying some form of persistent task tracking, but there is no explicit documentation of recurring/scheduled triggers or a scheduling UI. Community evidence also shows the agent's control plane can time out under stress, raising doubts about reliability for automated recurring runs. missing for 10: explicit scheduling/recurrence configuration docs, evidence of one-off vs recurring task setup, and independent confirmation that scheduled tasks reliably complete and report back.

   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”
   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”
   • [community] “Blog post title/finding: the author stress-tested Meta Muse until its agent control plane started timing out, exposing failure points in the…”

   proof ↗⚑ flag

   Martin~partialcommunity6/10

   Martin supports recurring background tasks (daily/weekly briefings, wake-up calls, email triage) and one-off scheduled reminders that ping the user via chosen interface, matching the core of the story. However, there's no unified 'task scheduler' concept with arbitrary custom recurring workflows beyond the specific built-in background tasks listed, and no independent verification of reliability for scheduled/recurring runs. missing for 10: evidence of general-purpose custom recurring task scheduling (not just fixed briefings/wake-up-calls), independent hands-on confirmation of reminder/briefing reliability, and any dashboard/management UI for viewing scheduled tasks.

   • [claimed-docs] “Tell Martin to remind you to do something, and he will ping you when the time comes.”
   • [claimed-docs] “Martin can send you daily or weekly briefings via email.”
   • [claimed-docs] “Martin can automatically label your emails and take follow up actions on your behalf.”
   • [claimed-docs] “Martin can call you at a specific time every morning to wake you up with the weather and your schedule.”
   • [claimed-docs] “Tell Martin to remind you to do something, and he will ping you at the specified time, via the specified interface.”
   • [community] “A big piece of product feedback we got was 'I don't trust AI to take actions like sending texts/emails on my behalf if it's not 100% reliabl…”

   proof ↗⚑ flag

Apps

1. power-userUse an official desktop app with OS-level shortcuts and access to what is on my screen

   weight 2 · round drawn
   Muse—none0/10

   Evidence describes Muse as an AI agent with its own computer/file system, chat, and permission tracking, but there is no mention of an official desktop app, OS-level keyboard shortcuts, or screen access/observation capability. This appears to be a mobile/app-based assistant rather than a desktop tool with screen access.

   ⚑ flag

   Martin—none0/10

   Community evidence confirms a Martin desktop app exists (martin-comm-4), and docs mention in-app 'shortcuts' for multi-step actions (martin-docs-7), but there is no evidence of OS-level global keyboard shortcuts or any capability for Martin to read/access what's on the user's screen. missing for 10: evidence of OS-level hotkey integration, evidence of screen-reading/context capture, any documentation describing desktop-native system integration beyond a generic app shell.

   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”
   • [claimed-docs] “Create custom shortcuts that trigger multi-step actions.”

   proof ↗⚑ flag

2. knowledge-workerUse full-featured official mobile apps for iOS and Android

   weight 2 · round to Muse
   Muse~partialclaimed4/10

   There is clear evidence of an iOS app (App Store reviews cited via apps.apple.com), but no evidence at all of an Android app, and no detailed description of feature parity between platforms. missing for 10: Android app existence, feature-completeness claims for either platform, independent verification of app quality.

   • [claimed-docs] “I find it more pleasant than Gemini or ChatGPT which is my default for this type of work.”
   • [claimed-docs] “I’d been curious to try OpenClaw, but didn’t want to deal with the security concerns or headache of setting it up.”

   proof ↗⚑ flag

   Martin—none0/10

   Martin's docs describe channel-based access (phone, SMS, WhatsApp, email, Slack, desktop) but no evidence of dedicated, full-featured native iOS/Android apps; a community comment explicitly asks 'I would try this if it had Android support! Is that planned?' indicating no Android app exists, and no iOS app is mentioned anywhere.

   • [claimed-docs] “Martin is reachable through all your communication channels, including phone, SMS, WhatsApp, email, and Slack.”
   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”
   • [community] “I would try this if it had Android support! Is that planned?”

   proof ↗⚑ flag

Custom bots

1. power-userBuild and share custom assistants with their own instructions and knowledge

   weight 2 · round drawn
   Muse—none0/10

   Evidence shows Muse supports personal customization (avatar naming/style, side chats for separate contexts) but nothing about creating a distinct 'assistant' with its own instructions/knowledge base that can be shared with other users, which is the core of this story.

   ⚑ flag

   Martin—none0/10

   Martin is a personal AI assistant with fixed integrations (calendar, email, Slack, todos, notes, reminders) and shortcuts, but there is no evidence of a feature to build a custom assistant with its own distinct instructions/persona and knowledge base, nor any sharing mechanism for such an assistant. missing for 10: custom assistant creation with configurable instructions/persona, custom knowledge base attachment, and sharing/publishing of a built assistant.

   ⚑ flag

1. ai-native userPerform bulk operations across many items at once

   weight 2 · round to Martin
   Muse—none0/10

   No evidence describes Muse performing bulk operations across many items; docs mention goals tracking, avatars, side chats, and tool-building, but nothing about batch/bulk processing of items. The community stress-test post even highlights the agent timing out under load rather than handling bulk tasks smoothly.

   ⚑ flag

   Martin~partialclaimed4/10

   Martin's docs show a few multi-item behaviors — e.g. forwarding an email with several events and having 'all of them' added to the calendar (martin-docs-23), and automatic email labeling/triage across an inbox (martin-docs-11) — which imply some batch-like processing, but there is no explicit bulk-operations feature (e.g. batch todo updates, mass note edits, multi-item scheduling command) described anywhere in the docs. missing for 10: explicit bulk-action tooling/API for operating on many items at once, first-party documentation of bulk operations, and independent confirmation of bulk-scale reliability.

   • [claimed-docs] “Got an email with events coming up? Forward it to Martin, and he'll add them all to your calendar.”
   • [claimed-docs] “Martin can automatically label your emails and take follow up actions on your behalf.”

   proof ↗⚑ flag

2. ai-native userDefine rules that trigger actions automatically on events

   weight 3 · round to Martin
   Muse—none0/10

   The evidence describes Muse's goal tracking, tool-building, and approval workflows, but there is no mention of user-defined conditional rules or event-triggered automations (e.g., 'when X happens, do Y'). Missing for 10: any documentation of a rules/trigger engine, event-based automation configuration, or examples of users setting conditional actions.

   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”
   • [claimed-docs] “If a task needs a tool that doesn't exist, your agent builds it for you.”

   proof ↗⚑ flag

   Martin~partialclaimed6/10

   Martin ships several automatic, event-triggered behaviors (email triage that auto-labels and follows up, cc-to-schedule meeting creation, forwarded-email calendar parsing, proactive drafts, wake-up calls, briefings) which act like predefined automation rules, and 'custom shortcuts' let users define multi-step action sequences. However, there's no evidence of a general user-defined rule/trigger engine (e.g., 'if email from X arrives then do Y' configurable conditions) — the automations shown are fixed built-in behaviors rather than arbitrary user-authored event rules. Missing for 10: a documented custom rule/condition builder, evidence of arbitrary event-trigger definitions beyond built-in background tasks, and independent confirmation these automations fire reliably in practice.

   • [claimed-docs] “Create custom shortcuts that trigger multi-step actions.”
   • [claimed-docs] “Martin can automatically label your emails and take follow up actions on your behalf.”
   • [claimed-docs] “Cc Martin on an email to schedule a meeting.”
   • [claimed-docs] “Martin can proactively draft emails for you and send them on your behalf.”
   • [claimed-docs] “Martin can call you at a specific time every morning to wake you up with the weather and your schedule.”
   • [claimed-docs] “Got an email with events coming up? Forward it to Martin, and he'll add them all to your calendar.”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round to Martin
   Muse—none0/10

   While Muse has a Goals tab that tracks ongoing tasks and an activity log, there is no evidence describing recurring/scheduled job execution, cron-like automation, or repeat-workflow triggers. missing for 10: explicit scheduling/recurrence feature, evidence of periodic execution, workflow automation configuration.

   ⚑ flag

   Martin~partialclaimed6/10

   Martin ships several built-in recurring background jobs — daily/weekly briefings, daily wake-up calls, and automatic email triage — which are documented recurring workflows, and shortcuts allow custom multi-step actions. However, there's no evidence of a general-purpose, user-defined recurring job scheduler (e.g., custom cadence for arbitrary tasks/workflows beyond the fixed built-in recurring features). Missing for 10: user-configurable custom recurring schedules beyond the fixed briefing/wake-up-call cadence, and independent confirmation these recurring jobs run reliably at scale.

   • [claimed-docs] “Martin can send you daily or weekly briefings via email.”
   • [claimed-docs] “Martin can call you at a specific time every morning to wake you up with the weather and your schedule.”
   • [claimed-docs] “Martin can automatically label your emails and take follow up actions on your behalf.”
   • [claimed-docs] “Create custom shortcuts that trigger multi-step actions.”
   • [claimed-docs] “Tell Martin to remind you to do something, and he will ping you at the specified time, via the specified interface.”

   proof ↗⚑ flag

4. ai-native userVersion, review, and roll back my automations

   weight 1 · round to Muse
   Muse~partialclaimed4/10

   Muse provides an activity log/audit trail and approval cards that support reviewing what the agent has done and plans to do (muse-docs-8, muse-docs-13, muse-docs-10), which covers the 'review' portion of the story. However, there is no evidence of explicit versioning of automations/skills or a rollback mechanism to revert an automation to a prior state — the 'Forget' skill only removes stored information, not automation history. missing for 10: explicit versioning of automations, a rollback/undo feature for agent actions, independent confirmation these review tools work reliably in practice.

   • [claimed-docs] “Tapping on your Muse avatar will show you its full activity log as well as permissions you’ve approved.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”
   • [claimed-docs] “structured approval cards with clear accept/reject actions, and secure storage for your credentials.”
   • [claimed-docs] “You can also use the Forget skill to have Muse forget information about specific topics or people.”

   proof ↗⚑ flag

   Martin—none0/10

   Martin is a personal assistant agent (email, calendar, reminders, shortcuts) with no evidence of version history, review workflows, or rollback for its automations/shortcuts; docs describe creating shortcuts but nothing about versioning or undoing them. Missing for 10: version history UI, review/approval workflow, rollback mechanism.

   • [claimed-docs] “Create custom shortcuts that trigger multi-step actions.”

   proof ↗⚑ flag

Connectors

1. power-userBrowse a directory of third-party apps and connectors and add them to the assistant

   weight 2 · round to Muse
   Muse~partialclaimed3/10

   Muse lets users link specific third-party data sources like email, calendar, Instagram, Facebook, health and finance data (muse-docs-11), which shows some connector-adding capability, but there is no evidence of a browsable directory or marketplace of third-party apps/connectors to explore and add. Missing for 10: an actual app/connector directory UI, discovery/browsing mechanism, and independent confirmation of a marketplace beyond ad-hoc account linking.

   • [claimed-docs] “Link your email, calendar, Instagram, Facebook, health and fitness data, and finances.”

   proof ↗⚑ flag

   Martin—none0/10

   Evidence shows Martin ships a small fixed set of first-party integrations (Calendar, Inbox, Slack) rather than a browsable directory/marketplace of third-party apps and connectors that a power-user can explore and add. No docs, UI, or community mentions describe an app directory or connector marketplace.

   • [claimed-docs] “Have Martin read, create, and update events in your calendar.”
   • [claimed-docs] “Have Martin read, draft, and reply to emails in your inbox.”
   • [claimed-docs] “Have Martin read and send messages in Slack from your account.”

   proof ↗⚑ flag

2. knowledge-workerConnect my cloud drive, email, and calendar so the assistant can search and use them in answers

   weight 3 · round to Muse
   Muse~partialclaimed6/10

   Muse docs explicitly support linking email and calendar (and other data sources) with approval/permission controls, but no evidence mentions a cloud drive connector (e.g., Google Drive/Dropbox), and there's no hands-on confirmation that these connected sources are actually searched/used in answers beyond permission approval cards. missing for 10: explicit cloud drive integration, independent evidence of search/use in answers.

   • [claimed-docs] “Link your email, calendar, Instagram, Facebook, health and fitness data, and finances.”
   • [claimed-docs] “structured approval cards with clear accept/reject actions, and secure storage for your credentials.”
   • [claimed-docs] “Tapping on your Muse avatar will show you its full activity log as well as permissions you’ve approved.”

   proof ↗⚑ flag

   Martin~partialclaimed5/10

   Martin has well-documented calendar and email (inbox) integrations letting it read, draft, reply, and add events on the user's behalf, plus a general search capability across connected sources. However, no evidence mentions a cloud drive (e.g., Google Drive/Dropbox) connector, so the story's full connector set is only partially covered. missing for 10: cloud drive integration, independent verification that search actually spans all connected sources.

   • [claimed-docs] “Have Martin read, create, and update events in your calendar.”
   • [claimed-docs] “Have Martin read, draft, and reply to emails in your inbox.”
   • [claimed-docs] “Martin syncs with multiple search engines to find you the most relevant information.”
   • [claimed-docs] “Once connected, you can tell Martin to add an event to your calendar, and he will add it at the specified time with the specified details.”
   • [claimed-docs] “Once connected, you can tell Martin to read, draft, and reply to emails on your behalf.”
   • [claimed-docs] “Got an email with events coming up? Forward it to Martin, and he'll add them all to your calendar.”

   proof ↗⚑ flag

Files

1. knowledge-workerUpload documents, spreadsheets, and PDFs and get accurate analysis of their contents

   weight 3 · round drawn
   Muse—none0/10

   No evidence in the pack describes Muse handling document/spreadsheet/PDF uploads or analyzing their contents; the material focuses on agent features like avatars, goals, side chats, permissions, and tool-building, not file ingestion or analysis accuracy.

   ⚑ flag

   Martin—none0/10

   Martin is a personal-assistant product focused on calendar, email, Slack, reminders, notes, and todos; no evidence anywhere in the pack mentions document, spreadsheet, or PDF upload/analysis capabilities. This is a plausible axis for an AI assistant but there's no supporting documentation or community mention of file/document analysis features.

   ⚑ flag

Memory

1. power-userHave the assistant remember relevant context from previous chats and apply it in new conversations

   weight 3 · round to Muse
   Muse~partialclaimed5/10

   Muse's docs imply persistent memory (a 'Forget skill' to remove remembered info about topics/people, plus 'side chats' for separate context threads and a Goals tab tracking ongoing tasks) suggesting it retains and reuses context across conversations, but there is no first-party or hands-on description of how memory is surfaced or applied in new chats. Missing for 10: explicit documentation of cross-chat memory recall/application, independent verification that remembered context actually surfaces in new conversations, and detail on memory scope/limits.

   • [claimed-docs] “You can also use the Forget skill to have Muse forget information about specific topics or people.”
   • [claimed-docs] “some people still wanted separate context for certain topics — which made sense as projects grew more complex. So we built side chats.”
   • [claimed-docs] “So we built side chats.”
   • [claimed-docs] “The Goals tab is where Muse keeps track of all this for you, and you can interact directly there or talk to it about these tasks in chat.”

   proof ↗⚑ flag

   Martin~partialclaimed4/10

   Martin's notes, to-dos, and reminders (martin-docs-6, martin-docs-22, martin-docs-5) provide persistent storage that Martin can read back across interfaces, giving it some ability to carry information forward. However, there is no explicit documentation of the assistant automatically recalling relevant context from prior conversations and applying it in new, unrelated chats — memory here is user-invoked (explicit notes) rather than an automatic contextual-memory feature. Missing for 10: explicit memory/context-recall feature description, evidence of automatic application of past-conversation context in new sessions, independent confirmation of this behavior.

   • [claimed-docs] “You can tell Martin to read, add, and edit your notes from any interface.”
   • [claimed-docs] “Call Martin and say "Note down everything we talked about on this call and call it 'Brain Dump'."”
   • [claimed-docs] “You can tell Martin to add, edit, and check off your to-dos on your behalf from any interface.”
   • [claimed-docs] “Tell Martin to remind you to do something, and he will ping you at the specified time, via the specified interface.”

   proof ↗⚑ flag

2. power-userSet persistent custom instructions and preferences that shape every response

   weight 1 · round drawn
   Muse—none0/10

   No evidence describes a persistent custom-instructions or preference-setting feature that shapes all responses; docs mention forget skill, avatars, side chats, and permissions but nothing about setting standing instructions/preferences.

   ⚑ flag

   Martin—none0/10

   No evidence in the pack describes a persistent custom-instructions or preferences feature that shapes all of Martin's responses; the docs cover integrations, reminders, notes, and background tasks but nothing about setting persona/style preferences persistently.

   ⚑ flag

Images

1. knowledge-workerShare screenshots and photos and have the assistant accurately interpret what is in them

   weight 2 · round drawn
   Muse—none0/10

   No evidence in the pack discusses image, screenshot, or photo interpretation capabilities of Muse; all citations focus on agent architecture, avatars, goals, side chats, and privacy controls. Missing for 10: any mention of image/vision input support, screenshot sharing, or accuracy of visual interpretation.

   ⚑ flag

   Martin—none0/10

   No evidence in the pack mentions image, screenshot, or photo interpretation capabilities; Martin's documented features focus on text-based channels (email, Slack, SMS, calendar, notes, reminders) with no mention of vision/multimodal input handling.

   ⚑ flag

Voice

1. knowledge-workerHave a natural, real-time voice conversation with the assistant

   weight 2 · round to Martin
   Muse—none0/10

   No evidence describes real-time voice conversation capability for Muse; the evidence pack focuses on agent tool-building, goals, side chats, avatar, and privacy features, with no mention of voice interaction or speech interface. Missing for 10: any documentation of voice input/output, real-time conversational voice mode, or hands-on account of speaking with Muse.

   ⚑ flag

   Martin~partialclaimed6/10

   Martin supports real phone-call interactions — users can call Martin to dictate notes, and Martin can call users for wake-up briefings — indicating a live voice channel exists (martin-docs-22, martin-docs-24, martin-docs-12). However, there is no documentation or independent evidence describing the naturalness, latency, or conversational fluidity of these voice interactions, and community feedback focuses on text/action reliability rather than voice quality. Missing for 10: hands-on/independent evidence of real-time conversational voice quality, documentation of voice-specific features like interruption handling or natural turn-taking.

   • [claimed-docs] “Call Martin and say "Note down everything we talked about on this call and call it 'Brain Dump'."”
   • [claimed-docs] “Martin is reachable through all your communication channels, including phone, SMS, WhatsApp, email, and Slack.”
   • [claimed-docs] “Martin can call you at a specific time every morning to wake you up with the weather and your schedule.”

   proof ↗⚑ flag

1. ai-native userDo everything through the API that I can do in the UI

   weight 2 · round drawn
   Muse—none0/10

   No evidence pack mentions a public API for Muse at all; all evidence describes UI features (avatars, Goals tab, side chats, activity log) with no mention of programmatic access. Absence of evidence for an applicable capability is 'none'.

   ⚑ flag

   Martin—none0/10

   Martin's documented surface is entirely conversational interfaces (email, Slack, phone, SMS, WhatsApp) with no mention of a public/developer API; explicit probes for an OpenAPI/swagger spec at all standard paths returned 404, indicating no programmatic API exists to mirror these UI capabilities.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.trymartin.com/openapi.json, https://docs.trymartin.com/swagger.json, https://docs.tryma…”
   • [claimed-docs] “Martin is reachable through all your communication channels, including phone, SMS, WhatsApp, email, and Slack.”

   proof ↗⚑ flag

2. ai-native userExport all of my data in open formats and leave

   weight 3 · round drawn
   Muse—none0/10

   There is no evidence of a data export feature or open-format data portability in Muse; the pack only mentions a 'Forget' privacy skill and audit trail, not export/download of user data.

   ⚑ flag

   Martin—none0/10

   No evidence anywhere in the pack of a data export feature or open-format data portability; Martin's docs focus on integrations, reminders, and briefings but never mention exporting user data or account deletion/export tools.

   ⚑ flag

3. ai-native userRead the product's source under an open license

   weight 2 · round drawn
   Muse—none0/10

   No evidence indicates Muse's source code is published under any open license; all evidence describes product features and community discussion, not source availability.

   ⚑ flag

   Martin—none0/10

   No evidence Martin's source code is available under any license; a community comment explicitly calls for Martin to 'make that system open source' as a trust-building step, implying it currently is not.

   • [community] “You should create a system where you cannot access user data, and it can never be shared with third parties. Make that system open source to…”

   proof ↗⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round drawn
   Muse—none0/10

   No evidence anywhere in the pack indicates Muse can be self-hosted; it's described as a cloud/app-based agent product with no mention of open-source release or self-hosting options.

   ⚑ flag

   Martin—none0/10

   Martin is offered exclusively as a cloud-based assistant (email, Slack, calendar interfaces, cloud-based agent per martin-comm-4); no evidence of a self-hostable core product, open-source release, or on-prem deployment option. One community comment (martin-comm-3) even calls for open-sourcing the data-handling system, implying it is not currently available.

   • [community] “oh, martin desktop is finally here! I use Martin to manage my todo list while i'm coding (on an hourly basis) - having it aside VSC is so ha…”
   • [community] “You should create a system where you cannot access user data, and it can never be shared with third parties. Make that system open source to…”

   proof ↗⚑ flag

1. ai-native userChoose where my data is stored (region/residency)

   weight 2 · round drawn
   Muse—none0/10

   No evidence in the pack mentions data residency, region selection, or storage location controls for Muse users.

   ⚑ flag

   Martin—none0/10

   No evidence anywhere in the pack mentions data residency, region selection, or storage location controls; docs focus entirely on assistant features and integrations. Community comments raise general privacy/security concerns but do not address data residency options. missing for 10: any mention of region selection, data residency policy, or storage location controls.

   • [community] “I want this, but very concerned about the security and privacy - you're talking about getting my most personal of personals (email, calendar…”
   • [community] “You should create a system where you cannot access user data, and it can never be shared with third parties. Make that system open source to…”

   proof ↗⚑ flag

2. ai-native userPrevent my data from being used to train AI models

   weight 3 · round drawn
   Muse—none0/10

   The evidence pack covers Muse's agent features, permissions, forget skill, and audit trail, but contains no mention of any opt-out or control over whether user data is used to train AI models. missing for 10: explicit opt-out/consent setting for model training, any privacy policy language addressing training-data usage.

   ⚑ flag

   Martin—none0/10

   No evidence pack item addresses AI-training data opt-out or data-usage policy; community comments explicitly raise privacy/trust concerns without any documented answer or control from Martin. Missing for 10: any privacy policy statement, opt-out setting, or documented no-training-data commitment.

   • [community] “I want this, but very concerned about the security and privacy - you're talking about getting my most personal of personals (email, calendar…”
   • [community] “You should create a system where you cannot access user data, and it can never be shared with third parties. Make that system open source to…”

   proof ↗⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round to Muse
   Muse~partialclaimed6/10

   Muse offers a 'Forget' skill to remove information about specific topics/people and provides an activity log/audit trail of actions, giving users some visibility and control, but there's no documentation of full account/data deletion, export, or granular retention policy settings. Missing for 10: explicit data export/deletion controls, retention period settings, and independent verification that 'Forget' fully purges underlying data rather than just suppressing recall.

   • [claimed-docs] “You can also use the Forget skill to have Muse forget information about specific topics or people.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”
   • [claimed-docs] “Tapping on your Muse avatar will show you its full activity log as well as permissions you’ve approved.”

   proof ↗⚑ flag

   Martin—none0/10

   No evidence describes data retention policies, deletion controls, export tools, or privacy settings; community comments even raise unaddressed concerns about lack of transparency around data handling. Missing for 10: any documentation of data retention periods, user-initiated deletion mechanism, or privacy controls.

   • [community] “I want this, but very concerned about the security and privacy - you're talking about getting my most personal of personals (email, calendar…”
   • [community] “You should create a system where you cannot access user data, and it can never be shared with third parties. Make that system open source to…”

   proof ↗⚑ flag

4. ai-native userOpt out of telemetry and usage tracking

   weight 2 · round drawn
   Muse—none0/10

   No evidence pack items mention a telemetry/usage-tracking opt-out setting; there is a 'Forget skill' for topic memory and privacy page references, but nothing about disabling telemetry or usage analytics collection. Missing for 10: any documentation of a telemetry/analytics opt-out toggle, privacy policy language on usage data collection, or user reports confirming such a control exists.

   • [claimed-docs] “You can also use the Forget skill to have Muse forget information about specific topics or people.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”

   proof ↗⚑ flag

   Martin—none0/10

   No evidence of any telemetry opt-out, privacy settings, or data collection controls; community comments even raise unresolved privacy/trust concerns (martin-comm-2, martin-comm-3) with no documented response or opt-out mechanism.

   • [community] “I want this, but very concerned about the security and privacy - you're talking about getting my most personal of personals (email, calendar…”
   • [community] “You should create a system where you cannot access user data, and it can never be shared with third parties. Make that system open source to…”

   proof ↗⚑ flag

Research

1. knowledge-workerLaunch a deep research run that autonomously searches many sources and returns a cited report

   weight 3 · round drawn
   Muse—none0/10

   No evidence describes Muse performing a deep research run that autonomously searches multiple sources and returns a cited report; the pack focuses on avatar personalization, goals/side chats, permissions, and tool-building, none of which document a research/citation workflow. Missing for 10: any mention of multi-source search, report generation, or citation output.

   ⚑ flag

   Martin—none0/10

   Martin's docs mention a basic search capability that 'syncs with multiple search engines to find relevant information' (martin-docs-8), but there is no evidence of an autonomous multi-source deep-research mode that returns a structured, cited report — no mention of citation formatting, report generation, or a dedicated 'deep research' feature.

   • [claimed-docs] “Martin syncs with multiple search engines to find you the most relevant information.”

   proof ↗⚑ flag

2. knowledge-workerGet answers grounded in current web results with citations back to the sources

   weight 2 · round to Martin
   Muse—none0/10

   No evidence in the pack describes Muse performing web search with cited sources for research answers; the material focuses on agent architecture, avatars, permissions, and goals rather than grounded citation-backed answers.

   ⚑ flag

   Martin~partialclaimed4/10

   Martin claims to sync with multiple search engines to find relevant information (martin-docs-8), suggesting web-grounded answers, but there is no evidence of citation formatting, source linking, or hands-on verification that answers include traceable citations back to web sources. Missing for 10: documentation or examples showing inline citations/source links, independent corroboration of search-grounded answer quality, and detail on which search engines/sources are used.

   • [claimed-docs] “Martin syncs with multiple search engines to find you the most relevant information.”

   proof ↗⚑ flag

Data controls

1. knowledge-workerExport my complete chat history and account data

   weight 1 · round drawn
   Muse—none0/10

   Evidence shows a 'Forget' skill and audit trail/activity log, but there is no mention of a data export or account data download feature for chat history or account data. missing for 10: export/download tool for chat history, account data export functionality, documentation of data portability process.

   • [claimed-docs] “You can also use the Forget skill to have Muse forget information about specific topics or people.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”

   proof ↗⚑ flag

   Martin—none0/10

   No evidence in the pack mentions data export, chat history download, or account data portability features; community comments even raise privacy concerns without any mention of export tools. Missing for 10: any documentation or feature reference to exporting chat history or account data, data portability API, or GDPR-style export mechanism.

   ⚑ flag

2. knowledge-workerControl whether my conversations are used to train models

   weight 3 · round drawn
   Muse—none0/10

   The evidence pack shows privacy-adjacent features like a 'Forget skill' for memory and audit trails/permissions, but nothing addresses whether users can opt their conversations out of model training specifically. This is a fair axis for a personal AI agent product, but no evidence documents a training-data control. Missing for 10: any documentation of a training opt-out setting, data-usage policy toggle, or explicit statement about whether conversations are used for model training.

   • [claimed-docs] “You can also use the Forget skill to have Muse forget information about specific topics or people.”
   • [claimed-docs] “Muse shows people a complete audit trail of everything it has done and plans to do.”

   proof ↗⚑ flag

   Martin—none0/10

   No evidence in the pack mentions any setting, policy, or statement about whether user conversations/data are used for model training; community comments explicitly raise privacy/trust concerns without any documented opt-out or training-control mechanism (martin-comm-2, martin-comm-3).

   • [community] “I want this, but very concerned about the security and privacy - you're talking about getting my most personal of personals (email, calendar…”
   • [community] “You should create a system where you cannot access user data, and it can never be shared with third parties. Make that system open source to…”

   proof ↗⚑ flag