listRevisionIntegrationQueuesList the queues linked to this build's case-queue integration slot. Only meaningful for case-queue-producer and case-queue-consumer integrations.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | Agent ID | |
| build_id | Yes | Build ID | |
| integration_id | Yes | Integration ID |
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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety and mutation profile is covered. The description adds an applicability qualifier but does not disclose return shape, pagination, or what 'linked queues' means. No contradiction with annotations exists.
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?
Two short sentences: the first states the action and resource, the second adds a necessary scope qualifier. There is no filler, repetition of schema details, or unnecessary domain explanation.
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 list operation with fully schema-covered UUID parameters and safety annotations, the description supplies the essential selection context. The only minor gap is that it assumes familiarity with the 'case-queue integration slot' concept and does not describe the response shape, but no output schema exists and the operation is straightforward.
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?
All three parameters are fully described in the schema with UUID formats and 'Agent ID', 'Build ID', and 'Integration ID' labels. The description adds domain context about case-queue integrations but does not meaningfully elaborate on the individual parameters beyond what the schema already provides.
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 a specific verb ('List') and identifies a precise resource: queues linked to a build's case-queue integration slot. It also narrows applicability to case-queue-producer and case-queue-consumer integrations. It does not explicitly contrast itself with siblings like listRevisionIntegrationConnections or listRevisionIntegrations, so it falls just short of a 5.
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 phrase 'Only meaningful for case-queue-producer and case-queue-consumer integrations' provides clear context for when the tool applies and implicitly warns against using it for other integration types. It does not name specific alternative tools or give an explicit 'when not to use' beyond that applicability condition.
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.