refreshPulseDashboardTrigger an on-demand data refresh of a Duvo Pulse dashboard. The dashboard regenerates its connection-sourced values in the background — poll GET /artifacts/{artifactId} for status.
| Name | Required | Description | Default |
|---|---|---|---|
| artifactId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate readOnlyHint=false, idempotentHint=false, destructiveHint=false. The description adds the background/asynchronous nature of the refresh and the need to poll the artifact endpoint for status, which is valuable behavioral context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loaded with the key action ('Trigger an on-demand data refresh'). Every word is informative, with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema) and the description covers the core behavior, the asynchronous nature, and the follow-up polling action. It does not discuss edge cases like potential conflicts with an in-progress refresh, but for a simple refresh tool this is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has a single artifactId parameter with uuid format but no description (0% coverage). The description indirectly references artifactId in the polling endpoint, implying it is the dashboard's artifact ID, but does not explicitly define it. Given the simplicity of the parameter, this is partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Trigger' with the resource 'a Duvo Pulse dashboard' and explains the effect ('regenerates its connection-sourced values in the background'). This clearly distinguishes it from read (getPulseDashboard), update (updatePulseDashboard), or create operations in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear use case: performing an on-demand refresh of a dashboard's connection-sourced values. It also instructs to poll GET /artifacts/{artifactId} for status, which is a usage guideline. However, it does not explicitly mention when not to use it or alternatives like getPulseDashboard.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.