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 |
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?
With annotations already marking this as non-read-only and non-destructive, the description adds useful behavioral context: the tool resumes a paused run and is restricted to creators/team editors. It also explains that toolCallId comes from the dashboard transcript. No contradiction with annotations is present.
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, front-loaded sentence with no filler. It states the action, the governing context, the allowed actors, and the key parameter source in an economical way.
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?
While the description is clear about the tool's purpose and auth scope, it leaves two of three required parameters underspecified in a schema with zero descriptions. There is no output schema, so the description carries the full burden, but it does not explain what artifactId refers to or how the answers object should be populated.
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?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only explains toolCallId's origin. artifactId and the structure/semantics of the answers object are left undefined, leaving an agent to guess what keys and values the answers object expects.
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 states a specific verb and resource: 'Answer a pending question the Duvo Pulse agent asked' and clearly identifies the follow-up effect: 'resume the paused run'. This is not a tautology and is specific enough to differentiate from generic tools like respondToHumanRequest or sendPulseDashboardMessage.
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 on when to use the tool: only for pending Duvo Pulse agent questions on a paused run, and only for 'creator or team editors'. It also gives a concrete source for toolCallId. It stops short of explicitly naming alternatives or saying when not to use it, so it does not reach a 5.
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.