createQueueAggregationCreate an immutable aggregation definition on a queue.
| Name | Required | Description | Default |
|---|---|---|---|
| queue_id | Yes | The queue's unique identifier | |
| definition | Yes | ||
| maximum_stale_age_seconds | No |
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?
The word 'immutable' adds useful behavioral context beyond the annotations, signaling that a created aggregation definition cannot later be modified in-place. However, the description does not mention side effects, permissions, what happens if the queue does not exist, or whether creation replaces any existing definition.
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 or repetition. It is appropriately concise for stating the core action, though it sacrifices useful detail that would require a second sentence, so it is not quite excellent.
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 tool with a highly complex nested input schema and no output schema, one short sentence is insufficient. Missing context includes parameter semantics, lifecycle implications of immutability, relationship to evaluateQueueAggregation/refreshQueueAggregation, and what a successful response looks like.
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 only 33%, so the description needed to compensate for the undocumented parameters, but it does not. It only says 'aggregation definition on a queue' and never explains maximum_stale_age_seconds or the meaning/structure of the definition object's measures, dimensions, filters, or timeDimension.
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 names a specific action ('Create') and a specific resource: an immutable aggregation definition on a queue. It is concise and distinguishable from sibling tools such as listQueueAggregations, evaluateQueueAggregation, and refreshQueueAggregation.
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 implies this tool is for creating a new aggregation definition, but it does not explicitly state when to use it versus related tools like evaluateQueueAggregation or refreshQueueAggregation. No exclusions, prerequisites, or alternative routing guidance are provided.
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.