getPulseDashboardHtmlServe a Duvo Pulse dashboard's rendered HTML document (text/html, not JSON). 404 until the first generation turn has produced HTML.
| Name | Required | Description | Default |
|---|---|---|---|
| artifactId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds meaningful non-obvious behavior beyond annotations: the 404-until-generation constraint and the explicit text/html response type. This is valuable context for an agent deciding whether and when to call the tool.
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 with no filler. The primary action is front-loaded, and the 404 caveat is a concise, high-value behavioral detail that earns its place.
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?
For a single-parameter read-only HTML fetch, the description covers the essential non-obvious details: response content type and the 404-before-generation behavior. It is mostly complete, though explicit sibling routing and a direct explanation of artifactId would make it fully self-sufficient.
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 describes artifactId as a required UUID with a pattern but provides no description. The tool description never names or explains the parameter, so with 0% schema description coverage it does not compensate. The phrase 'a Duvo Pulse dashboard's rendered HTML' implies artifactId identifies the dashboard, but this is left to inference.
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 clearly states the verb 'Serve' and the resource: a Duvo Pulse dashboard's rendered HTML document, with the content type 'text/html, not JSON'. This distinguishes it from JSON-returning getters, but it does not explicitly differentiate it from close siblings like getPulseDashboardVersionHtml or exportPulseDashboardHtml.
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 gives a useful temporal usage condition: it will 404 until the first generation turn has produced HTML, implying it should be called after generation. However, it provides no explicit guidance about when to choose this tool over version-specific or export-related siblings.
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.