getPulseDashboardVersionHtmlServe a specific version's rendered HTML document for a Duvo Pulse dashboard (text/html, requires edit access).
| Name | Required | Description | Default |
|---|---|---|---|
| artifactId | Yes | ||
| revisionId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable context beyond annotations: the output format ('text/html') and the access requirement ('requires edit access'), which help the agent anticipate invocation results. No contradiction with 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 a single sentence, front-loaded with the verb 'Serve', and includes all essential information (resource, version scoping, output type, access requirement) without any filler or redundancy.
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 simple read-only tool with two parameters, no output schema, and good annotations, the description covers the key aspects: what is returned (rendered HTML), the version scoping, and the access requirement. It could potentially describe return behavior in more detail, but 'Serve' and 'text/html' sufficiently convey the output. Overall, the description is complete enough for an agent to invoke the tool correctly.
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 0% parameter description coverage, requiring the description to compensate. The description mentions 'a specific version' which implies revisionId identifies the version, and 'Duvo Pulse dashboard' maps to artifactId, but it does not explicitly define either parameter. The parameter names are somewhat self-explanatory in context, but the description could be clearer about the exact roles of artifactId and revisionId.
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 a specific verb ('serve') and resource ('a specific version's rendered HTML document for a Duvo Pulse dashboard'), and distinguishes from siblings by emphasizing 'specific version' and MIME type 'text/html'. It effectively conveys the tool's unique scope.
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 clear context that this is for a specific version of a Pulse Dashboard, implying it should be used when a particular revision's HTML is needed. It notes 'requires edit access' as a prerequisite, but does not explicitly state alternatives or when not to use it (e.g., use getPulseDashboardHtml for the current version).
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.