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 |
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 description discloses the full behavioral sequence: reads sandbox id, kills the sandbox, flips the process back to review, clears the sandbox marker, and drops late webhooks as stale. This goes far beyond what the annotations convey and gives the agent an accurate model of the tool's side effects.
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?
Two sentences with no filler. The purpose is front-loaded, and the mechanism/side effects are compactly explained without redundancy.
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 two-parameter mutating action with no output schema, the description fully explains what will happen, what state changes occur, and how stale webhooks are handled. An agent can confidently call this tool and understand its consequences.
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 coverage is 100%, so the baseline is 3. The description adds minimal parameter meaning beyond stating 'selected kind' and referencing the process row/sandbox id. The schema's own 'Snapshot kind to list' description is slightly misleading, but the tool description's verb 'stop' helps disambiguate the intended operation.
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?
States a specific verb and resource: 'Stop an in-flight snapshot generation for the selected kind.' This clearly distinguishes the tool from generate/get/list/promote/revert snapshot siblings and from generic stop tools like stopRun or stopClarityArtifactChatConversation.
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 phrase 'in-flight snapshot generation' provides clear usage context: this tool is for cancelling an ongoing snapshot generation. It does not explicitly mention exclusions or alternatives, but the condition is clear enough to guide selection.
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.