deleteAgentDelete an agent and cascade-clean its schedules, case triggers, builder runs, and handover targets. Any active jobs are interrupted and their sandboxes paused.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | The agent's unique identifier |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructiveHint, idempotentHint, readOnlyHint), the description discloses significant side effects: cascade deletion of dependent resources, interruption of active jobs, and pausing of sandboxes. This is exactly the kind of contextual behavior an agent needs to predict consequences, and it does not contradict any annotation.
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 only two sentences, front-loaded with the core action ('Delete an agent') and then efficiently listing the cascade effects. Every phrase adds value, with no redundancy or filler.
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, one-parameter tool with no output schema, the description fully specifies the scope of deletion and side effects (interrupted jobs, paused sandboxes). This is sufficient for an agent to safely invoke it, and no return-value details are needed because there is no output schema.
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 already provides 100% coverage for the single parameter (agent_id with a complete description and UUID pattern). The tool description does not add further semantic detail about the parameter, so the baseline 3 is appropriate per the rubric.
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 uses the specific verb 'Delete' and names the resource 'agent', clearly distinguishing it from the many sibling tools like deleteAgentCaseTrigger and deleteAgentFolder. It also explicitly states the cascade-cleaning scope (schedules, case triggers, builder runs, handover targets), making its purpose unmistakable.
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 fully removing an agent and all associated dependencies, which contrasts with the targeted delete tools (deleteAgentCaseTrigger, deleteSchedule). However, it does not explicitly state 'use this when you want to permanently remove an agent' or exclude cases where updateAgent might be more appropriate, so it falls short of explicit when/when-not guidance.
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.