updateClarityProcessSharingEnable or disable sharing for a clarity process
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Clarity process ID. | |
| enabled | Yes | Whether public process sharing is enabled. | |
| proposalShareEnabled | No | Whether the automation proposal is included. Public sharing must already be enabled when only changing this setting. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / proposalShareEnabled / descriptionPrevious value: -"Whether the transformation proposal is included. Public sharing must already be enabled when only changing this setting."New value: +"Whether the automation proposal is included. Public sharing must already be enabled when only changing this setting."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate this is a mutating operation (readOnlyHint=false) and non-destructive. The description adds no extra behavioral context such as side effects of disabling sharing, permission requirements, or what happens to existing shared links. It essentially restates the action implied by the name and title.
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, front-loaded sentence with no filler. It states the action and object directly and efficiently, leaving parameter details to the schema.
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 schema covers parameter semantics well, and this is a relatively simple mutation tool. Still, the description omits broader context such as prerequisites beyond the schema note and any side effects that disabling sharing may have, which an agent might need before invoking the tool confidently.
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 already describes all three parameters, including the precondition that public sharing must already be enabled when only changing proposalShareEnabled. The description itself adds no parameter-level meaning, so it earns the baseline score for a fully covered schema.
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 ('Enable or disable') and a specific resource ('sharing for a clarity process'). This clearly distinguishes it from sibling tools that update other clarity process aspects such as labels, links, or general process settings.
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 intended use case is implied by the action: call this when you want to change the sharing state of a clarity process. However, it does not explicitly mention alternatives like getClarityProcessSharing for reading current sharing settings, nor does it state when not to use this tool.
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.