Delete Clarity Capture
deleteClarityCaptureDelete a capture from a clarity process
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The clarity process ID | |
| captureId | Yes | The capture ID to delete |
deleteClarityCaptureDelete a capture from a clarity process
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The clarity process ID | |
| captureId | Yes | The capture ID to delete |
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 carry destructiveHint=true, readOnlyHint=false, and idempotentHint=true. The description adds no behavioral context beyond what the annotations already signal — it doesn't mention permanence, side effects, cascading deletions, or return behavior.
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 clear sentence with no wasted words. It is concise and front-loaded, though it could add a short clause about permanence or side effects without becoming bloated.
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?
The tool is simple (2 params, no output schema), but the description omits consequences of deletion, such as whether it is permanent or whether dependent data is affected. The annotations cover the destructive nature, making this minimally sufficient but not complete for an agent that needs to anticipate side effects.
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 100%, with both id and captureId fully documented as UUIDs with clear meanings ('The clarity process ID', 'The capture ID to delete'). The description adds no additional parameter meaning, so baseline 3 applies.
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 and resource: 'Delete a capture from a clarity process.' This distinguishes it from sibling tools like deleteClarityProcess or deleteClarityFolder, though it doesn't clarify what a 'capture' is or how it differs from a 'suggestion' in sibling tools like dismissClarityCaptureSuggestion.
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?
There is no guidance on when to use this tool versus alternatives such as getClarityCapture, listClarityLandscapeCaptures, or dismissClarityCaptureSuggestion. No prerequisites, exclusions, or context are provided to help an agent choose this tool correctly.
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.