{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_todo-is","slug":"todo-is","name":"Todo.is","type":"product","url":"https://todo.is","page_url":"https://unfragile.ai/todo-is","categories":["automation"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_todo-is__cap_0","uri":"capability://text.generation.language.natural.language.task.creation.via.conversational.ai","name":"natural language task creation via conversational ai","description":"Accepts freeform natural language input through a chat interface and parses it into structured task objects with title, description, due date, priority, and assignee fields. Uses NLP to extract temporal references (e.g., 'next Friday', 'in 2 weeks'), priority signals ('urgent', 'low-key'), and implicit task structure from conversational phrasing. The system likely tokenizes input, applies intent classification, and entity extraction to populate task metadata without requiring manual form filling.","intents":["I want to dump tasks into my system as fast as I think them without formatting","I need to capture task details (due date, priority, assignee) from a single conversational sentence","I want to avoid the friction of clicking through dropdown menus and date pickers for every task"],"best_for":["Individual power users who think in prose rather than structured forms","Distributed teams using async communication channels (Slack, Discord) for task capture","Non-technical team members who find traditional task managers intimidating"],"limitations":["Ambiguous natural language may be misinterpreted (e.g., 'review the Q4 report' could be a task or a reference)","No explicit feedback loop shown for correction—unclear if users can train the parser on misclassifications","Temporal parsing likely fails on non-English languages or regional date formats","Complex multi-step tasks may be flattened into a single task rather than decomposed into subtasks"],"requires":["Active internet connection for NLP inference","User account with Todo.is","Modern browser or mobile app with text input capability"],"input_types":["text (freeform natural language)","voice (if mobile app supports dictation)"],"output_types":["structured task object (title, description, due_date, priority, assignee_id)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_todo-is__cap_1","uri":"capability://planning.reasoning.ai.driven.task.prioritization.and.urgency.ranking","name":"ai-driven task prioritization and urgency ranking","description":"Analyzes task attributes (due date, description keywords, project context, team velocity) and user behavior patterns to assign or suggest priority levels and urgency scores. Likely uses a scoring function that weights factors like temporal proximity ('due tomorrow' = high urgency), keyword signals ('critical', 'blocker'), and historical task completion patterns. The system may employ collaborative filtering to infer priority from similar tasks completed by other team members.","intents":["I want the system to automatically surface the most important tasks without manually triaging my backlog","I need to understand why a task was marked as high-priority so I can override if needed","I want to see tasks ranked by impact and urgency, not just due date"],"best_for":["Teams with large backlogs (50+ tasks) where manual prioritization is unsustainable","Managers who want data-driven insights into task urgency across distributed teams","Individual contributors drowning in context-switching who need algorithmic guidance"],"limitations":["Algorithm transparency is opaque—editorial notes that users lack 'clear insight into how the algorithm decides task importance'","No explicit mention of how the system handles conflicting signals (e.g., low due-date urgency but high keyword urgency)","Likely biased toward recent tasks or tasks with verbose descriptions, potentially deprioritizing quiet but critical work","No apparent user feedback loop to retrain the model on misranked tasks","Cold-start problem: new users or teams without historical data may receive poor prioritization"],"requires":["Minimum 10-20 tasks in the system for meaningful pattern detection","Team activity history (task completion, reassignments) for collaborative filtering","Consistent task metadata (due dates, descriptions) across the backlog"],"input_types":["structured task data (title, description, due_date, labels, assignee, project)","user behavior signals (task completion time, reassignments, comment activity)"],"output_types":["priority level (low, medium, high, critical)","urgency score (numeric, 0-100)","ranked task list"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_todo-is__cap_2","uri":"capability://automation.workflow.real.time.collaborative.task.editing.and.presence.awareness","name":"real-time collaborative task editing and presence awareness","description":"Enables multiple team members to view and edit the same task simultaneously with live updates, cursor presence indicators, and conflict-free concurrent edits. Likely uses operational transformation (OT) or conflict-free replicated data types (CRDTs) to merge concurrent edits without requiring explicit locking. The system broadcasts presence state (who is viewing/editing which task) and updates task state across all connected clients in near-real-time via WebSocket or similar persistent connection.","intents":["I want to see when a teammate is editing a task so I don't overwrite their changes","I need to collaborate on task details (description, acceptance criteria) without creating separate documents","I want to avoid the overhead of 'check out' workflows that slow down small team iteration"],"best_for":["Small distributed teams (3-15 people) who need synchronous collaboration without formal change control","Product teams iterating on task descriptions and acceptance criteria in real-time","Remote-first organizations where async-first tools (like Asana) create context-switching friction"],"limitations":["Real-time collaboration scales poorly beyond 5-10 concurrent editors on the same task (WebSocket overhead, conflict resolution complexity)","No apparent version history or rollback mechanism mentioned—unclear if users can recover from accidental deletions","Presence awareness may create false urgency or social pressure in async-first cultures","Network latency can create perception of 'lag' in updates, especially for geographically distributed teams","No mention of offline-first support—users without internet lose collaboration capability"],"requires":["Stable internet connection with low latency (<500ms) for smooth collaboration","Modern browser with WebSocket support","Team members with active Todo.is accounts"],"input_types":["text edits (task title, description, comments)","metadata changes (due date, assignee, priority)"],"output_types":["merged task state","presence indicators (user avatars, cursor positions)","activity feed (who changed what, when)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_todo-is__cap_3","uri":"capability://text.generation.language.conversational.task.clarification.and.decomposition","name":"conversational task clarification and decomposition","description":"Maintains a multi-turn chat context where users can ask the AI to clarify, expand, or break down tasks into subtasks through natural language. The system retains conversation history and task context, allowing users to say 'split this into smaller steps' or 'what are the acceptance criteria?' and receive AI-generated suggestions. This likely uses a retrieval-augmented generation (RAG) pattern where the current task and conversation history are injected into the LLM prompt to generate contextually relevant suggestions.","intents":["I want to ask the AI to break down a vague task into concrete subtasks","I need help defining acceptance criteria for a task without leaving the chat interface","I want to iteratively refine a task description through conversation rather than manual editing"],"best_for":["Individual contributors who struggle with task decomposition and need AI scaffolding","Product managers who want to rapidly prototype task structures before committing to formal specs","Teams without a dedicated project manager who need AI-assisted task structuring"],"limitations":["AI-generated subtasks may not align with actual technical dependencies or team workflows","No apparent validation that suggested subtasks are actually actionable or measurable","Conversation context is likely lost when switching between tasks or closing the chat—no persistent conversation history across sessions","LLM hallucinations could generate plausible-sounding but incorrect acceptance criteria","No mechanism shown for users to provide feedback on quality of suggestions to improve future decompositions"],"requires":["Active LLM API connection (likely OpenAI or similar)","Task context (title, description, project) to seed the conversation","User account with sufficient API quota"],"input_types":["natural language queries ('split this into steps', 'what are the acceptance criteria?')","task context (title, description, labels)"],"output_types":["natural language suggestions (subtask titles, acceptance criteria, estimated effort)","structured subtask objects (if user accepts suggestions)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_todo-is__cap_4","uri":"capability://planning.reasoning.ai.assisted.task.assignment.and.team.routing","name":"ai-assisted task assignment and team routing","description":"Analyzes task attributes (skills required, project context, team member workload, historical assignments) and suggests optimal assignees or automatically routes tasks to team members. The system likely maintains a skill matrix or historical assignment log, uses workload balancing heuristics to avoid overloading individuals, and may apply collaborative filtering to match tasks to team members with similar past assignments. Suggestions are presented to the user before assignment to maintain human oversight.","intents":["I want the system to suggest who should own a task based on their skills and availability","I need to balance workload across the team without manually tracking everyone's capacity","I want to avoid the cognitive overhead of deciding 'who should do this?' for every task"],"best_for":["Team leads and managers who need to distribute work across distributed teams","Agile teams practicing continuous task assignment rather than sprint planning","Organizations with high task volume (100+ tasks/week) where manual assignment is unsustainable"],"limitations":["No mention of how the system handles skill mismatches or learning opportunities (e.g., assigning a task to someone to develop a new skill)","Workload balancing likely uses simple metrics (task count, estimated hours) rather than actual capacity or context-switching cost","No apparent integration with calendar or time-tracking systems to understand true availability","Cold-start problem: new team members without assignment history may receive poor suggestions","Bias risk: if historical assignments reflect organizational biases, the system will perpetuate them","No transparency into why a specific person was suggested"],"requires":["Team member profiles with skill tags or historical assignment data","Task metadata (required skills, project, estimated effort)","Minimum 20-30 historical assignments per team member for meaningful pattern detection"],"input_types":["task attributes (title, description, required skills, project, estimated effort)","team member profiles (skills, past assignments, current workload)","organizational context (team structure, project assignments)"],"output_types":["assignment suggestion (recommended team member with confidence score)","alternative suggestions (ranked list of 2-3 other candidates)","reasoning (optional explanation of why this person was suggested)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_todo-is__cap_5","uri":"capability://automation.workflow.freemium.access.with.usage.based.feature.gating","name":"freemium access with usage-based feature gating","description":"Provides a free tier with core task management functionality (create, view, edit tasks; basic collaboration) and gates advanced AI features (prioritization, assignment suggestions, decomposition) behind a paid subscription. The system likely tracks feature usage and API calls (LLM inference, prioritization scoring) and enforces rate limits or feature availability based on subscription tier. Free tier users can access the product without credit card, reducing friction for individual adoption.","intents":["I want to try Todo.is without committing to a paid plan","I need basic task management for my solo projects without paying","I want to upgrade to AI features only when I've validated the product fits my workflow"],"best_for":["Individual power users and solopreneurs testing the product before team adoption","Small teams with limited budgets who want to start free and upgrade as they scale","Organizations evaluating multiple task management tools and want low-risk trials"],"limitations":["Free tier likely has strict rate limits on AI features (e.g., 5 prioritization runs/month), creating artificial friction for power users","Unclear what features are gated—editorial notes 'unclear what unique value proposition justifies adoption', suggesting free tier may not differentiate enough","Conversion funnel risk: if free tier is too limited, users may not experience enough value to upgrade; if too generous, monetization suffers","No mention of data retention or export policies for free tier users—unclear if free accounts are deleted after inactivity"],"requires":["Email address to create account","No payment method required for free tier"],"input_types":["user signup data (email, name, team size)"],"output_types":["account creation","feature access token (defines which features are available)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_todo-is__cap_6","uri":"capability://automation.workflow.task.activity.feed.and.audit.trail","name":"task activity feed and audit trail","description":"Maintains a chronological log of all changes to tasks (edits, assignments, status changes, comments) with timestamps and attribution to specific users. The system displays this activity feed in the task detail view, allowing team members to understand the evolution of a task and who made what changes. This likely uses an event-sourcing pattern where each change is recorded as an immutable event, enabling both real-time updates and historical queries.","intents":["I want to see who changed a task and when, to understand the decision history","I need to track when a task was reassigned or its priority changed","I want to understand why a task is in its current state by reviewing the activity log"],"best_for":["Teams with formal change control or compliance requirements (e.g., healthcare, finance)","Distributed teams where async communication makes task history critical for context","Project managers who need to audit task changes for accountability"],"limitations":["Activity feeds can become noisy if every minor edit (typo fixes, whitespace changes) is logged","No mention of filtering or search within activity logs—users may struggle to find relevant changes in high-activity tasks","Storage overhead: maintaining full audit trails increases database size, especially for long-lived tasks","No apparent integration with external audit systems or compliance tools","Privacy risk: activity logs expose who is working on what, which may be sensitive in some organizations"],"requires":["Task with at least one change (edit, assignment, comment)","User permissions to view task details"],"input_types":["task change events (edits, assignments, status changes, comments)"],"output_types":["activity feed (chronological list of changes with user, timestamp, change description)","audit trail (exportable log for compliance)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_todo-is__cap_7","uri":"capability://search.retrieval.natural.language.task.search.and.filtering","name":"natural language task search and filtering","description":"Allows users to search and filter tasks using conversational queries (e.g., 'show me all high-priority tasks due this week assigned to Sarah') rather than requiring structured filter syntax. The system parses natural language queries into structured filter expressions (priority=high, due_date<=next_week, assignee=Sarah) using NLP entity extraction and intent classification. Results are returned as a filtered task list with optional sorting and grouping.","intents":["I want to find tasks without remembering filter syntax or clicking through multiple dropdown menus","I need to quickly surface tasks matching multiple criteria (priority, due date, assignee) in one query","I want to ask questions like 'what's overdue?' or 'what's assigned to me?' without navigating UI"],"best_for":["Non-technical team members who find traditional filter UIs intimidating","Power users who want faster task discovery than clicking through filters","Teams with large task backlogs (500+ tasks) where browsing is impractical"],"limitations":["Ambiguous queries may return unexpected results (e.g., 'urgent' could match priority=high or tasks with 'urgent' in the description)","No apparent support for complex boolean logic (AND, OR, NOT) in natural language queries","Temporal parsing may fail on ambiguous references ('next week' is relative and depends on current date)","No mention of saved searches or query history—users must re-enter complex queries each time","Performance may degrade on very large task lists (10,000+ tasks) if search requires full-text indexing"],"requires":["Task list with metadata (priority, due_date, assignee, labels) for filtering","NLP model trained on task-specific vocabulary and filter patterns"],"input_types":["natural language query (text)"],"output_types":["filtered task list (array of tasks matching criteria)","result count","optional sorting/grouping (by due date, assignee, priority)"],"categories":["search-retrieval","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Active internet connection for NLP inference","User account with Todo.is","Modern browser or mobile app with text input capability","Minimum 10-20 tasks in the system for meaningful pattern detection","Team activity history (task completion, reassignments) for collaborative filtering","Consistent task metadata (due dates, descriptions) across the backlog","Stable internet connection with low latency (<500ms) for smooth collaboration","Modern browser with WebSocket support","Team members with active Todo.is accounts","Active LLM API connection (likely OpenAI or similar)"],"failure_modes":["Ambiguous natural language may be misinterpreted (e.g., 'review the Q4 report' could be a task or a reference)","No explicit feedback loop shown for correction—unclear if users can train the parser on misclassifications","Temporal parsing likely fails on non-English languages or regional date formats","Complex multi-step tasks may be flattened into a single task rather than decomposed into subtasks","Algorithm transparency is opaque—editorial notes that users lack 'clear insight into how the algorithm decides task importance'","No explicit mention of how the system handles conflicting signals (e.g., low due-date urgency but high keyword urgency)","Likely biased toward recent tasks or tasks with verbose descriptions, potentially deprioritizing quiet but critical work","No apparent user feedback loop to retrain the model on misranked tasks","Cold-start problem: new users or teams without historical data may receive poor prioritization","Real-time collaboration scales poorly beyond 5-10 concurrent editors on the same task (WebSocket overhead, conflict resolution complexity)","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:33.648Z","last_scraped_at":"2026-04-05T13:23:42.559Z","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=todo-is","compare_url":"https://unfragile.ai/compare?artifact=todo-is"}},"signature":"xAg3LwXIEd8akTu98DcTAcj6kDo00BWCflR3JqwGQcb+xOA4GWdHmLei6dYi9jArYaSQBkeseVrCLtAENYBJDg==","signedAt":"2026-06-21T01:24:01.715Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/todo-is","artifact":"https://unfragile.ai/todo-is","verify":"https://unfragile.ai/api/v1/verify?slug=todo-is","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"}}