stopClarityProcessSnapshotStop an in-flight snapshot generation for the selected kind. Reads the sandbox id from the process row, kills the sandbox, flips the process back to review, and clears the sandbox marker so any late webhook from the killed run is dropped as stale.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | Yes | Snapshot kind to list | |
| process_id | Yes | The clarity process id |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states destructive actions: 'kills the sandbox, flips the process back to review, and clears the sandbox marker'. However, annotations set destructiveHint=false, which contradicts the described behavior. Despite the description being transparent, the contradiction forces a score of 1 per the rules.
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 two sentences with no redundancy. The first sentence states the primary purpose, and the second details the steps. Every sentence adds value, and the structure is front-loaded for quick understanding.
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?
Given the tool has no output schema, the description explains the actions taken (kill sandbox, flip process, clear marker) but does not mention the return value or response format. For a straightforward action, this is largely complete, though a brief note on what the user receives back would be helpful.
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 input schema covers both parameters (process_id, kind) with descriptions, achieving 100% coverage. The description does not add any additional meaning beyond what the schema provides, so the baseline of 3 is appropriate.
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 a specific verb ('stop') and resource ('in-flight snapshot generation') and clearly distinguishes from siblings like generateClarityProcessSnapshot, getClarityProcessSnapshot, etc. It explains the exact actions taken, leaving no ambiguity about the tool's purpose.
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 states it stops an in-flight snapshot for a selected kind, which implies when to use (during generation). It does not explicitly list alternatives or when-not to use, but the purpose is clear enough given the context of sibling tools that cover other snapshot operations.
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.