{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"dust","slug":"dust","name":"Dust","type":"agent","url":"https://dust.tt","page_url":"https://unfragile.ai/dust","categories":["ai-agents","app-builders"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"dust__cap_0","uri":"capability://planning.reasoning.no.code.agent.builder.with.visual.workflow.composition","name":"no-code agent builder with visual workflow composition","description":"Enables non-technical users to construct multi-step AI agents through a drag-and-drop interface without writing code. The builder abstracts tool orchestration, model selection, and data flow into visual blocks that chain together semantic search, API calls, and LLM reasoning steps. Agents are deployed immediately to a cloud runtime without compilation or deployment infrastructure.","intents":["I want to build a customer support agent that searches our knowledge base and answers tickets without coding","I need to create a sales agent that pulls CRM data and generates personalized outreach without engineering help","I want to compose multi-tool workflows where one agent's output feeds into another agent's input"],"best_for":["non-technical business users and domain experts building domain-specific agents","teams without dedicated ML/AI engineering resources","enterprises needing rapid agent prototyping and iteration"],"limitations":["No programmatic agent definition — agents must be built through UI, limiting version control and CI/CD integration","Visual builder abstracts underlying model behavior, making fine-tuning model temperature, max tokens, or system prompts difficult or impossible","No custom code execution within agent workflows — limited to pre-built tool integrations and LLM calls"],"requires":["Dust account (free tier available with 14-day trial)","At least one data connector configured (Slack, Google Drive, Notion, etc.)","API key for at least one LLM provider (OpenAI, Anthropic, Google, Mistral)"],"input_types":["natural language task descriptions","structured data from connected sources (Slack messages, Google Drive documents, Notion databases)"],"output_types":["agent execution logs","structured agent responses","tool invocation traces"],"categories":["planning-reasoning","tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_1","uri":"capability://search.retrieval.multi.source.semantic.search.with.knowledge.base.indexing","name":"multi-source semantic search with knowledge base indexing","description":"Indexes documents from 10+ connected data sources (Google Drive, Notion, Confluence, GitHub, Slack, Zendesk, etc.) into a searchable knowledge base using semantic embeddings. Agents query this index with natural language to retrieve relevant context before generating responses, enabling RAG-style information retrieval without manual document management. Search results are ranked by semantic relevance and can be filtered by source or metadata.","intents":["I want my support agent to search across all company documentation (Notion, Confluence, Google Drive) to answer customer questions","I need to build a knowledge base that automatically indexes new documents from Slack channels and GitHub wikis","I want to query company data semantically without writing SQL or knowing exact document locations"],"best_for":["support and customer success teams building knowledge-base-backed agents","organizations with distributed documentation across multiple platforms","teams needing to surface institutional knowledge without manual curation"],"limitations":["Search index is updated on a schedule (frequency not specified) — real-time indexing of new documents may have latency","Semantic search quality depends on embedding model quality and document structure — poorly formatted documents may not retrieve correctly","No explicit control over embedding model selection or fine-tuning — uses Dust's default embeddings","Storage limited to 1GB per user (Pro tier) — large document collections may require Enterprise tier","Search results are unranked beyond semantic similarity — no BM25 hybrid search or custom ranking available"],"requires":["At least one data connector configured and authenticated (Google Drive, Notion, Confluence, etc.)","Documents must be in supported formats (PDFs, Google Docs, Notion pages, Confluence pages, GitHub markdown)","Pro tier or above for advanced search features"],"input_types":["natural language search queries","documents from connected sources (PDFs, markdown, web pages, database records)"],"output_types":["ranked list of relevant documents with excerpts","source metadata (document title, author, last modified date)","relevance scores"],"categories":["search-retrieval","memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_10","uri":"capability://automation.workflow.agent.performance.monitoring.and.cost.tracking","name":"agent performance monitoring and cost tracking","description":"Provides dashboards and metrics for monitoring agent performance (success rate, execution time, tool usage) and tracking costs (API calls, token consumption, model usage). Metrics are aggregated by agent, time period, and data source. Cost tracking shows spending by model provider and helps identify optimization opportunities.","intents":["I want to see which agents are most used and which are failing frequently","I need to track API costs per agent to allocate expenses to teams","I want to identify which tools are most expensive and optimize agent workflows"],"best_for":["operations and finance teams tracking agent ROI and costs","teams optimizing agent performance and resource utilization","organizations with multiple agents needing visibility into aggregate metrics"],"limitations":["Cost tracking granularity is unknown — unclear if costs are tracked per model, per tool, or per agent","Metrics are not specified — unclear what success rate, execution time, or tool usage metrics are available","No cost forecasting or budgeting tools — cannot predict future costs or set spending limits","No integration with external cost management tools (AWS Cost Explorer, GCP Billing, etc.)","Billing transparency is limited — API pricing and overage rates are not publicly documented"],"requires":["Agent deployed and executed multiple times to generate metrics","Access to Dust workspace analytics dashboard"],"input_types":["agent execution data"],"output_types":["performance metrics (success rate, execution time, tool usage)","cost reports (spending by model, agent, time period)","optimization recommendations"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_11","uri":"capability://tool.use.integration.browser.automation.and.web.navigation.for.agents","name":"browser automation and web navigation for agents","description":"Enables agents to navigate websites, fill forms, extract data from web pages, and interact with web applications programmatically. Agents can click buttons, type text, read page content, and follow links to complete multi-step web tasks. Web navigation is sandboxed and does not require agents to manage browser state or handle JavaScript rendering.","intents":["I want my agent to navigate competitor websites and extract pricing information","I need an agent that can fill out web forms and submit applications automatically","I want to scrape data from multiple websites and aggregate it in a report"],"best_for":["teams automating web-based workflows and data extraction","organizations monitoring competitors or market data through web scraping","use cases requiring interaction with web applications that lack APIs"],"limitations":["Web navigation implementation details are not documented — unclear if it uses Selenium, Playwright, or custom browser automation","No specification of JavaScript rendering or dynamic content handling — may fail on heavily JavaScript-dependent sites","No cookie or session management documented — unclear how agents handle authentication or maintain state across requests","Rate limiting and anti-bot detection are not addressed — agents may be blocked by websites with aggressive bot protection","No screenshot or visual feedback — agents cannot see rendered pages, only HTML/text content","Timeout and error handling for web navigation are not specified"],"requires":["Target websites must be publicly accessible","No authentication required (or agents must handle login via form filling)","Compliance with target website's terms of service and robots.txt"],"input_types":["URL and navigation instructions (click, type, extract)","form data to fill"],"output_types":["extracted web page content","form submission results","navigation logs"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_12","uri":"capability://data.processing.analysis.data.analysis.and.querying.without.sql.knowledge","name":"data analysis and querying without sql knowledge","description":"Enables agents to analyze structured data and query databases using natural language without requiring SQL knowledge. Agents can read data from Google Sheets, databases, and other structured sources, perform aggregations and transformations, and generate reports. Natural language is translated to queries internally, abstracting SQL complexity.","intents":["I want my agent to answer questions about sales data without writing SQL queries","I need to generate monthly reports from our database without manual data extraction","I want to analyze customer data and identify trends without data science expertise"],"best_for":["non-technical business users querying data without SQL knowledge","teams automating data analysis and reporting workflows","organizations democratizing data access through natural language interfaces"],"limitations":["Data sources supported are not fully specified — unclear if agents can query arbitrary databases or only Google Sheets","Query complexity limits are unknown — unclear if agents can handle complex joins, subqueries, or window functions","No schema management or data dictionary — agents must infer schema from data, which may fail for complex structures","No data validation or quality checks — agents may generate incorrect results from dirty data","Performance on large datasets is not documented — unclear if there are size limits or timeout policies","No caching or query optimization — repeated queries may be slow"],"requires":["Structured data source (Google Sheets, database, CSV)","Data connector configured for the source","Schema or table structure accessible to agents"],"input_types":["natural language questions about data","data source and table/sheet names"],"output_types":["query results (rows, aggregations, statistics)","generated reports and visualizations","query execution logs"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_13","uri":"capability://automation.workflow.agent.versioning.and.deployment.management","name":"agent versioning and deployment management","description":"Dust enables teams to create and manage multiple versions of agents, test changes in staging environments, and deploy updates to production with rollback capabilities. Users can compare agent versions, track changes, and revert to previous versions if needed. The platform supports gradual rollouts (e.g., deploying to 10% of users first) and A/B testing different agent configurations.","intents":["I want to test a new version of my support agent with a small group of users before rolling out to everyone","I need to revert to a previous agent version if a new deployment causes problems","I want to compare how different agent configurations perform on the same task"],"best_for":["teams iterating on agent design and testing changes","organizations deploying agents to production with safety requirements","teams running A/B tests to optimize agent performance"],"limitations":["Versioning and deployment features not documented — unclear if version control is automatic or manual","Rollback mechanisms and recovery procedures not detailed","A/B testing and gradual rollout capabilities not confirmed","No documented staging environment or testing tools"],"requires":["Deployed agent with active usage","Access to agent configuration and versioning controls"],"input_types":["agent configuration changes","deployment targets (staging, production, user segments)"],"output_types":["versioned agent snapshots","deployment logs and status","comparison metrics between versions","rollback confirmations"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_2","uri":"capability://tool.use.integration.multi.provider.llm.orchestration.with.model.selection","name":"multi-provider llm orchestration with model selection","description":"Abstracts LLM provider differences by supporting GPT-5, Claude, Gemini, and Mistral models through a unified interface. Agents can be configured to use different models for different tasks, and the platform handles API key management, request routing, and error handling across providers. Model selection is configurable per agent or per step within an agent workflow.","intents":["I want to use Claude for reasoning-heavy tasks and GPT-5 for code generation in the same agent","I need to switch between models without rewriting agent logic or managing multiple API clients","I want to use open-source models (Mistral) for cost optimization while keeping proprietary models as fallback"],"best_for":["teams evaluating multiple LLM providers and wanting to avoid vendor lock-in","organizations optimizing for cost by using cheaper models for simple tasks","enterprises requiring model diversity for compliance or performance reasons"],"limitations":["Model selection is static per agent — no dynamic model routing based on task complexity or cost","No built-in fallback logic if a model provider is unavailable — requires manual agent reconfiguration","Advanced model parameters (temperature, top_p, max_tokens) are not exposed in the UI — limited fine-tuning capability","No cost tracking per model — billing is aggregated across all model usage","Model availability depends on Dust's provider agreements — not all models available on all tiers"],"requires":["API keys for at least one LLM provider (OpenAI, Anthropic, Google, Mistral)","Pro tier or above for access to advanced models like GPT-5 and Claude","Model-specific API quotas and rate limits must be respected"],"input_types":["agent configuration specifying model choice","task context and prompts"],"output_types":["model-generated text responses","token usage metrics","model inference latency"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_3","uri":"capability://tool.use.integration.enterprise.data.connector.ecosystem.with.native.integrations","name":"enterprise data connector ecosystem with native integrations","description":"Provides pre-built connectors to 10+ enterprise platforms (Slack, Google Drive, Notion, Confluence, GitHub, Zendesk, Salesforce, Chrome Extension) that handle authentication, data fetching, and schema mapping without custom code. Connectors support both read operations (querying data for agent context) and write operations (creating tickets, posting messages). Generic connectors (API, Google Sheets, Zapier) enable integration with any HTTP endpoint or workflow platform.","intents":["I want my agent to read customer tickets from Zendesk and generate responses without manual API integration","I need to connect to Salesforce to pull account data and generate RFP responses automatically","I want to post agent outputs back to Slack channels without writing webhook code"],"best_for":["enterprises with existing SaaS tool stacks (Slack, Notion, Confluence, Zendesk, Salesforce)","teams lacking API integration expertise","organizations needing rapid agent deployment without custom connector development"],"limitations":["Salesforce connector is Enterprise tier only — not available on Pro tier","Connector capabilities are fixed — no custom field mapping or transformation logic available","Write operations are limited to pre-defined actions (e.g., create ticket, post message) — complex workflows require Zapier or generic API connector","Authentication is connector-specific — no unified SSO for all connectors (SSO available Enterprise-only for user provisioning, not connector auth)","Rate limits and quotas are inherited from underlying services — Dust does not provide buffering or queuing","Data freshness depends on connector polling frequency — real-time updates not guaranteed"],"requires":["Active account with target service (Slack workspace, Notion workspace, Confluence instance, etc.)","OAuth credentials or API keys for authentication","Appropriate permissions in target service (e.g., Slack bot scopes, Zendesk API token with ticket read/write)"],"input_types":["connector configuration (service credentials, workspace/instance selection)","query parameters (search filters, date ranges, record IDs)"],"output_types":["structured data from target service (messages, documents, tickets, accounts)","connector execution logs and error messages"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_4","uri":"capability://automation.workflow.human.in.the.loop.agent.execution.with.approval.workflows","name":"human-in-the-loop agent execution with approval workflows","description":"Agents execute within a supervised model where critical actions (e.g., sending messages, creating records, modifying data) can be configured to require human approval before execution. Execution logs show all tool invocations, model reasoning, and outputs, enabling humans to review and override agent decisions. Approval workflows are configurable per agent or per action type.","intents":["I want my support agent to draft responses but require human approval before sending to customers","I need to audit all agent actions before they modify data in our CRM or knowledge base","I want to gradually increase agent autonomy by removing approval requirements for low-risk actions"],"best_for":["regulated industries (finance, healthcare, legal) requiring audit trails and human oversight","teams deploying agents for the first time and building trust incrementally","customer-facing use cases where agent errors have high business impact"],"limitations":["Approval workflows add latency — agents cannot complete tasks in real-time if human review is required","No automatic escalation or timeout logic — if approver is unavailable, tasks may stall indefinitely","Approval UI and notification mechanism not specified — unclear how approvers are notified or how they interact with pending tasks","No role-based approval routing — cannot specify different approvers for different action types or risk levels","Audit logging granularity is unknown — unclear what metadata is captured (who approved, when, from where, etc.)"],"requires":["Agent configured with approval requirements for specific actions","At least one user with approval permissions in the workspace","Notification mechanism (email, Slack, in-app) to alert approvers of pending tasks"],"input_types":["agent execution request with proposed action","execution context (tool invocations, model reasoning, output)"],"output_types":["approval decision (approve/reject)","audit log entry with approver identity and timestamp","execution result (action executed or blocked)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_5","uri":"capability://automation.workflow.agent.fleet.governance.and.multi.workspace.management","name":"agent fleet governance and multi-workspace management","description":"Enables enterprises to manage multiple agents across multiple workspaces with centralized governance controls. Features include user provisioning via SCIM (Enterprise tier), role-based access control, data residency options (US/EU), and advanced security controls. Workspaces are isolated environments where teams can build and deploy agents independently while maintaining organizational oversight.","intents":["I want to provision users across multiple teams using SCIM without manual account creation","I need to ensure agents in different departments cannot access each other's data or tools","I want to deploy agents in EU data centers to comply with GDPR"],"best_for":["large enterprises (100+ users) with multiple teams and compliance requirements","organizations requiring data residency in specific regions (EU, US)","teams needing centralized governance and audit logging across agent fleets"],"limitations":["Enterprise tier required for SCIM, SSO, and advanced security — not available on Pro tier","Minimum 100 users required for Enterprise tier — smaller organizations cannot access governance features","Role-based access control model is not specified — unclear what roles exist and what permissions they grant","Data residency is binary (US or EU) — no multi-region or hybrid deployment options","Audit logging granularity is unknown — unclear what events are logged and how long logs are retained","No API for programmatic workspace management — workspaces must be created and configured through UI"],"requires":["Enterprise tier subscription (minimum 100 users)","Identity provider supporting SCIM (Okta, Entra ID, Jumpcloud)","Compliance requirements or multi-team structure justifying governance overhead"],"input_types":["user provisioning requests (SCIM protocol)","workspace configuration (data residency, security policies)","role assignments"],"output_types":["user accounts and workspace access","audit logs","compliance reports"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_6","uri":"capability://tool.use.integration.programmatic.agent.invocation.via.api.and.spreadsheet.integration","name":"programmatic agent invocation via api and spreadsheet integration","description":"Exposes agents as HTTP APIs that can be invoked programmatically from external applications, or as formulas in Google Sheets for non-technical users. API requests include task description and optional context, and responses include agent output and execution metadata. Spreadsheet integration enables users to invoke agents on rows of data without writing code, with results populated back into the sheet.","intents":["I want to call my support agent from our ticketing system's webhook to auto-generate responses","I need to run my sales agent on 1000 leads in a Google Sheet and populate the results in a new column","I want to integrate my agent into our internal tools via REST API without custom SDK"],"best_for":["developers integrating agents into existing applications and workflows","non-technical users needing to batch-invoke agents on spreadsheet data","teams building agent-powered automation without custom backend code"],"limitations":["API pricing is unclear — documentation mentions 'free credits included' and 'fixed price for overages' but does not specify per-call costs","No built-in request queuing or batching — high-volume API calls may hit rate limits","Spreadsheet integration is limited to Google Sheets — no Excel, Airtable, or other spreadsheet platforms","API response format is not specified — unclear what metadata is included (execution time, token usage, tool invocations, etc.)","No async/polling pattern documented — unclear if API calls are synchronous or if long-running tasks are supported","Authentication mechanism not specified — unclear if API uses API keys, OAuth, or other methods"],"requires":["Agent deployed and accessible in Dust workspace","API key or authentication credentials for programmatic access","For spreadsheet integration: Google account with access to target Sheet"],"input_types":["HTTP POST request with task description and optional context","spreadsheet rows with data to process"],"output_types":["JSON response with agent output and metadata","spreadsheet cells populated with agent results"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_7","uri":"capability://automation.workflow.agent.execution.logging.and.debugging.with.tool.invocation.traces","name":"agent execution logging and debugging with tool invocation traces","description":"Captures detailed execution logs for every agent run, including tool invocations, model inputs/outputs, reasoning steps, and error messages. Logs are queryable and can be filtered by agent, date range, or status. Execution traces show the exact sequence of tool calls and model reasoning, enabling debugging of agent behavior and understanding of decision-making.","intents":["I want to debug why my agent failed to answer a customer question correctly","I need to understand what tools my agent invoked and in what order to optimize performance","I want to audit all agent executions for compliance and error tracking"],"best_for":["developers and operators debugging agent behavior and performance issues","teams auditing agent decisions for compliance and error analysis","organizations optimizing agent workflows based on execution patterns"],"limitations":["Log retention policy is not specified — unclear how long logs are stored or if they can be exported","Log query interface is not described — unclear if logs can be filtered by tool, model, or custom criteria","Sensitive data handling in logs is unknown — unclear if API keys, user data, or model outputs are redacted","No integration with external logging systems (CloudWatch, Datadog, Splunk) — logs are siloed in Dust","Execution trace granularity is unknown — unclear if traces include token counts, latency per step, or cost per invocation"],"requires":["Agent deployed and executed at least once","Access to Dust workspace to view logs"],"input_types":["agent execution request"],"output_types":["execution logs with timestamps","tool invocation traces showing sequence and parameters","model input/output pairs","error messages and stack traces"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_8","uri":"capability://planning.reasoning.domain.specific.agent.templates.for.common.use.cases","name":"domain-specific agent templates for common use cases","description":"Provides pre-built agent templates for common enterprise use cases (customer support, sales, marketing, HR, legal, IT, engineering) that include pre-configured tools, prompts, and workflows. Templates serve as starting points that teams can customize without building agents from scratch. Each template is optimized for its domain with relevant data connectors and tool integrations.","intents":["I want to quickly deploy a customer support agent without designing the workflow from scratch","I need a sales agent template that already knows how to query CRM and generate outreach","I want to see best practices for HR agents before building my own"],"best_for":["teams new to agent building wanting to accelerate time-to-value","organizations deploying agents across multiple departments with consistent patterns","non-technical users needing guidance on agent design and tool selection"],"limitations":["Template customization options are not specified — unclear how much agents can be modified from templates","Template coverage is limited to 9 domains (sales, marketing, support, knowledge, data, IT, engineering, HR, legal) — other domains require custom agent building","Templates may not reflect organization-specific workflows or data structures — customization effort is unknown","No version control for templates — unclear if templates are updated and how changes are communicated","Template quality and accuracy are not documented — no metrics on template success rates or user satisfaction"],"requires":["Dust account with appropriate tier (template availability by tier not specified)","Data connectors configured for template's required integrations"],"input_types":["template selection and customization parameters"],"output_types":["pre-configured agent ready for deployment","template documentation and best practices"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__cap_9","uri":"capability://safety.moderation.zero.data.retention.privacy.model.with.configurable.data.handling","name":"zero-data-retention privacy model with configurable data handling","description":"Implements a zero-data-retention policy where Dust does not store user data, documents, or agent outputs after task completion. Data is processed in-memory during agent execution and discarded afterward. Organizations can configure data residency (US or EU) to comply with regional regulations. No data is used for model training or improvement without explicit opt-in.","intents":["I want to use Dust for sensitive customer data without worrying about data retention or misuse","I need to comply with GDPR and ensure data is processed only in EU data centers","I want to ensure my proprietary business data is not used to train Dust's models"],"best_for":["organizations handling sensitive data (healthcare, finance, legal, PII)","enterprises with strict data residency requirements (GDPR, HIPAA, SOC2)","teams concerned about data privacy and model training practices"],"limitations":["Zero-data-retention applies only to user data — unclear if execution logs, audit trails, or metadata are retained","Data residency is binary (US or EU) — no multi-region or hybrid options","Data residency is Enterprise-tier only — Pro tier users cannot guarantee data location","Opt-out from model training is not specified — unclear if all users are opted-out by default or if opt-in is required","Data handling during agent execution is not detailed — unclear if data is encrypted in transit/at-rest or if it's shared with LLM providers"],"requires":["Enterprise tier for data residency guarantees","Acceptance of Dust's privacy policy and data handling terms"],"input_types":["user data, documents, and agent context"],"output_types":["agent outputs (not retained)","execution logs (retention policy unclear)"],"categories":["safety-moderation","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"dust__headline","uri":"capability://tool.use.integration.enterprise.ai.assistant.platform","name":"enterprise ai assistant platform","description":"A no-code platform that enables teams to build custom AI agents, integrating with company knowledge bases and tools for enhanced productivity and workflow automation.","intents":["best enterprise AI assistant","AI agents for team collaboration","no-code AI platform for internal tools","custom AI agents for business workflows","AI assistant for enterprise knowledge management"],"best_for":["teams looking to automate workflows","companies with extensive internal data"],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":59,"verified":false,"data_access_risk":"high","permissions":["Dust account (free tier available with 14-day trial)","At least one data connector configured (Slack, Google Drive, Notion, etc.)","API key for at least one LLM provider (OpenAI, Anthropic, Google, Mistral)","At least one data connector configured and authenticated (Google Drive, Notion, Confluence, etc.)","Documents must be in supported formats (PDFs, Google Docs, Notion pages, Confluence pages, GitHub markdown)","Pro tier or above for advanced search features","Agent deployed and executed multiple times to generate metrics","Access to Dust workspace analytics dashboard","Target websites must be publicly accessible","No authentication required (or agents must handle login via form filling)"],"failure_modes":["No programmatic agent definition — agents must be built through UI, limiting version control and CI/CD integration","Visual builder abstracts underlying model behavior, making fine-tuning model temperature, max tokens, or system prompts difficult or impossible","No custom code execution within agent workflows — limited to pre-built tool integrations and LLM calls","Search index is updated on a schedule (frequency not specified) — real-time indexing of new documents may have latency","Semantic search quality depends on embedding model quality and document structure — poorly formatted documents may not retrieve correctly","No explicit control over embedding model selection or fine-tuning — uses Dust's default embeddings","Storage limited to 1GB per user (Pro tier) — large document collections may require Enterprise tier","Search results are unranked beyond semantic similarity — no BM25 hybrid search or custom ranking available","Cost tracking granularity is unknown — unclear if costs are tracked per model, per tool, or per agent","Metrics are not specified — unclear what success rate, execution time, or tool usage metrics are available","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.548Z","last_scraped_at":null,"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=dust","compare_url":"https://unfragile.ai/compare?artifact=dust"}},"signature":"zVNuaLGrAzofANQCY6QEHcQQ6PlzUBN2cP1LnLRNWzoFlJ+0HyOgoUX9K3r2L5+gTiZjby3Bd/ZvGpDk+Gx+Dg==","signedAt":"2026-06-21T07:45:23.830Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/dust","artifact":"https://unfragile.ai/dust","verify":"https://unfragile.ai/api/v1/verify?slug=dust","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"}}