Duvo MCP

Stop Pulse Dashboard Message

stopPulseDashboardMessage

Stop an in-flight Duvo Pulse generation turn. Requires edit access to the dashboard. Flips the dashboard to 'interrupted' and keeps any streamed-so-far reply; stopping when nothing is generating is a successful no-op.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`artifactId`	Yes
`partial_text`	No	The assistant text streamed so far, kept in the conversation as the partial reply. Omit when calling from an API client without streaming state.

TDQS

A4.2/5.0

Behavior4/5

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

Beyond the annotations (readOnlyHint=false, etc.), the description discloses important behavioral traits: requires edit access, flips the dashboard to 'interrupted', preserves the streamed-so-far reply, and is a no-op when nothing is generating. This adds meaningful context not present in structured fields.

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?

Two sentences, front-loaded with the main action, and every clause adds value. No filler or repetition of schema/annotation information.

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

Completeness4/5

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

For a simple tool with two parameters and no output schema, the description covers purpose, side effects, permissions, and edge case behavior. It is slightly incomplete—it doesn't explicitly mention how the partial_text parameter relates to the 'streamed-so-far reply'—but the overall behavior is well explained.

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?

Schema coverage is 50% (only partial_text has a description). The tool description adds meaning to partial_text by explaining that the streamed reply is kept, but artifactId is not explicitly described. The parameter name and UUID format make it fairly clear, but the description does not fully compensate for the lack of schema detail on the required field.

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 uses a specific verb ('Stop') and identifies the resource ('an in-flight Duvo Pulse generation turn'). It clearly distinguishes from siblings like sendPulseDashboardMessage and listPulseDashboardMessages, and explains the effect (flips dashboard to 'interrupted').

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 gives clear context for when to use the tool: stopping an in-flight generation. It also states a useful edge case (no-op when nothing is generating) and a prerequisite (edit access). However, it does not explicitly mention sibling tools like stopRun as alternatives.

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

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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.

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