assignClarityLandscapeCaptureRequestAssign an open Process Landscape capture request to a team member, or unassign it by sending userId: null (manager+).
| Name | Required | Description | Default |
|---|---|---|---|
| nodeId | Yes | ||
| userId | Yes | ||
| requestId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the mutating nature (assign/unassign) and adds context beyond annotations by revealing role restrictions (manager+ for unassign) and the null userId unassignment pattern. No contradiction with annotations. It doesn't detail side effects or reversibility, but the tool is simple and the description covers key behavioral traits.
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 that front-loads the verb and resource, includes the unassign pattern, and has zero waste. It is concise while covering the core purpose and key usage nuance.
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 3-parameter mutation without output schema, the description covers the primary behavior and unassign pattern. However, it omits preconditions (e.g., what happens if the request is not open), error states, and the meaning of nodeId and requestId. It is minimally complete but has gaps that could confuse an agent in edge cases.
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 coverage is 0% and the description does not explain the meaning of nodeId or requestId. It only adds value for the userId parameter by specifying that null unassigns. This is insufficient given the low coverage; the agent must guess what nodeId and requestId refer to from context.
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 the verb (assign/unassign) and the specific resource (Process Landscape capture request), and distinguishes from sibling assignment tools by naming the resource explicitly. It also includes the special unassign behavior with 'userId: null'.
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 when-to-use context: assign an open capture request to a team member, or unassign by sending null. It implies the requirement that the tool is for open requests and that unassignment is manager+ only. However, it does not explicitly differentiate from similar sibling tools like assignClarityExtraCaptureRequest or mention when not to use it.
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.