Duvo MCP

Create Pulse Dashboard

createPulseDashboard

Create a new Duvo Pulse dashboard from a natural-language prompt (e.g. 'open cases by queue this week') and dispatch the first generation turn. Generation is asynchronous — poll GET /artifacts/{artifactId} until status is completed. The dashboard is private to you unless you set visibility to 'team', which shares it with your whole team straight away — with permission 'view' (teammates see the dashboard) or 'edit' (teammates can also iterate on it).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`message`	Yes
`permission`	No
`visibility`	No
`connection_ids`	No

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is not read-only, not idempotent, and not destructive. The description adds valuable behavioral details: generation is asynchronous and requires polling GET /artifacts/{artifactId}, and visibility defaults to private unless 'team' is set, with permission levels affecting sharing. This exceeds what annotations alone provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, each earning its place: the main action, the asynchronous polling behavior, and the sharing semantics. It is front-loaded with the primary purpose and has no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers key aspects: creation, async polling, and sharing semantics. However, it omits the 'connection_ids' parameter entirely and does not explicitly describe the return format beyond implying an artifact ID. Given the absence of an output schema, these gaps make it incomplete for a tool with 4 parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema_description_coverage, the description must compensate. It explains 'message' as a natural-language prompt, and details the semantics of 'visibility' and 'permission'. However, 'connection_ids' is not mentioned at all, leaving that parameter undocumented. Partial compensation, but not complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a new Duvo Pulse dashboard from a natural-language prompt and dispatches the first generation turn. It uses a specific verb ('create') and resource ('Pulse dashboard'), distinguishing it from sibling tools like updatePulseDashboard or getPulseDashboard.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: to create a new dashboard from a prompt, with explicit mention of asynchronous generation and polling. It does not explicitly name alternative tools or exclusions, but the context strongly implies the intended use case.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Duvo MCP tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.1/5.0

Disambiguation2/5

Despite detailed descriptions, many tool names are highly ambiguous, with multiple tools covering the same conceptual actions (e.g., acceptClarityCaptureSuggestion vs. acceptClarityTeamAssignmentSuggestion, or the many deleteClarity*Interview tools). The set is so large that distinguishing between, say, listClarityFolders, listClarityProcesses, and listClarityProcessSummaries requires reading deep into descriptions, reducing agent selection accuracy.

Naming Consistency4/5

The naming convention is predominantly verb_noun (e.g., createClarityProcess, listAgents, deleteQueue), and is remarkably consistent across the 316 tools. There are only minor deviations, such as 'fileSuggestedClarityProcesses' (verb + adjective noun) and 'bulkUpdateCasePriority' (where 'bulk' could be seen as a prefix), but overall the pattern holds strongly.

Tool Count1/5

With 316 tools, this server is extremely oversized for any single agent to manage effectively. The massive number of tools suggests poor modularization—many of these tools likely belong in separate, smaller servers focused on specific domains (e.g., Clarity, Pulse, Agent management). The cognitive load for an agent to choose from 316 options is very high, leading to frequent misselection.

Completeness4/5

The tool surface covers an extraordinarily wide range of operations across the Duvo platform: agents, runs, cases, queues, Clarity processes, skills, integrations, notifications, teams, and more. Most resource types have full CRUD and lifecycle management. Notable minor gaps exist (e.g., no tools for managing specific notification batch severities dynamically, and some interview management is missing batch operations), but for the platform's scope, coverage is impressively thorough.

Resources

Need Help?