deleteClarityOrganizationInterviewDelete an organization-level Clarity interview
| Name | Required | Description | Default |
|---|---|---|---|
| orgId | Yes | ||
| interviewId | Yes | The organization interview 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?
The annotations already supply destructiveHint=true, idempotentHint=true, and readOnlyHint=false, and the description is consistent with them, so there is no contradiction. However, the description adds no behavioral context beyond the structured hints — it does not say whether deletion cascades to related artifacts, is permanent or recoverable, or affects associated data.
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 single sentence has zero wasted words and front-loads the action verb. But it is essentially a paraphrase of the tool title, so the brevity reflects under-specification rather than deliberate compression of rich content.
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 destructive tool with no output schema and only 50% parameter coverage, the description is too thin to support safe autonomous invocation. Missing are the effect of deletion (permanent vs. reversible), any cascade or scoping behavior, and the meaning of the orgId parameter — all of which an agent needs to invoke this correctly.
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 50%: interviewId has a minimal description ('The organization interview ID') while orgId is entirely undocumented in the schema. The tool description compensates for neither — it contains no information about the parameters, their relationship, or how an agent should obtain valid UUIDs for them.
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 ('Delete') and a scoped resource ('organization-level Clarity interview'), and the 'organization-level' qualifier helps differentiate it from the sibling tools deleteClarityTeamInterview and deleteClarityLandscapeNodeInterview. However, it adds nothing beyond the title and does not explicitly name or contrast those alternatives.
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?
No guidance is provided on when to use this tool versus alternatives such as deleteClarityTeamInterview or deleteClarityLandscapeNodeInterview, nor any preconditions, side-effect warnings, or when-not-to-use conditions. The 'organization-level' scope only weakly implies a selection rule, and no exclusions or sibling references are present.
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.