finalizeClarityOrganizationInterviewManually mark an in-progress organization interview as complete without requiring final media uploads
| Name | Required | Description | Default |
|---|---|---|---|
| orgId | Yes | ||
| interviewId | Yes | The organization interview ID |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful behavioral context beyond the annotations by noting this is a manual override that does not require final media uploads. However, it does not disclose side effects, such as whether the interview becomes immutable, whether this action can be reversed, or what happens if the interview is already complete.
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 wasted words. Every phrase—'manually', 'in-progress', 'as complete', 'without requiring final media uploads'—adds meaningful detail that helps an agent understand the tool's purpose.
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 two-parameter state-transition tool with no output schema, the description captures the core action and the key condition. Yet it omits details an agent might need, such as the success/return behavior, whether finalizing is irreversible, and any validation constraints beyond the interview being in-progress.
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 schema documents 'interviewId' but leaves 'orgId' completely undescribed, and the description does not compensate by explaining the role of either parameter. The phrase 'organization interview' hints at the resource type, but the description adds no meaning beyond the property names and the one existing schema description.
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 action ('mark as complete'), a specific resource ('organization interview'), and a distinctive condition ('without requiring final media uploads'). This clearly differentiates it from related tools like updateClarityOrganizationInterview or the upload-completion flow.
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 gives clear context: this is for manually finalizing an in-progress interview, bypassing the usual media upload requirement. However, it does not explicitly state when not to use it or name alternatives, such as updateClarityOrganizationInterview for other edits or the normal upload-based completion path.
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.