answerPulseDashboardQuestionAnswer a pending question the Duvo Pulse agent asked and resume the paused run (creator or team editors). Use the toolCallId from the dashboard's message transcript.
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | ||
| artifactId | Yes | ||
| toolCallId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the mutating nature is known. The description adds behavioral transparency by stating that the run is paused and will be resumed upon answering, and it discloses the authorization boundary ('creator or team editors'). 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 concise, just two sentences, and front-loads the core purpose. It efficiently conveys the action, permission, and the source for the critical toolCallId parameter without any redundant or filler content.
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 description covers the tool's purpose and workflow well but is incomplete regarding parameter semantics. The answers object format and artifactId are essential for correct invocation, and with no output schema and no param descriptions, the description leaves these ambiguous. The permission note and toolCallId hint are helpful, but the tool is more complex than the description acknowledges.
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 input schema has three required parameters (artifactId, toolCallId, answers) with zero description coverage. The description only explains how to find toolCallId, leaving artifactId and the structure/meaning of the answers object entirely unspecified. With such low schema coverage, the description needed to compensate but did not.
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 specifies the action ('Answer a pending question'), the resource ('the Duvo Pulse agent'), and the effect ('resume the paused run'). It also distinguishes the tool from siblings like sendPulseDashboardMessage and stopPulseDashboardMessage by focusing on answering agent questions, and includes the permission context ('creator or team editors').
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 usage context: it is for pending questions from the Duvo Pulse agent and explains that the run will resume. It gives a concrete source for the required toolCallId ('from the dashboard's message transcript'). However, it does not explicitly state when not to use this tool or mention alternative tools, so it lacks explicit exclusions.
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.