duplicateClarityProcessDuplicate a Clarity process with its analysis, captures, message history, and, for v2 processes, its live current map and automation proposal. Requires a team manager role.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Source 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?
Annotations already indicate this is a mutating operation (readOnlyHint=false, destructiveHint=false), and the description adds meaningful behavioral context: what data is included in the duplicate, a version-specific behavior for v2 processes, and the required team manager role. It does not state the outcome format or whether a new process ID is returned, but the role and content details go beyond the annotations.
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 well-structured sentence that front-loads the core action and resource, immediately follows with the key included contents, and adds the role requirement at the end. Every phrase provides useful information, with no filler or repetition.
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 simple single-parameter schema and absence of an output schema, the description gives enough operational context: what is copied, the version-specific scope, and the permission requirement. It could be slightly more complete by noting what is returned or where the duplicate is created, but these are minor gaps for a straightforward duplication operation.
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 covers the single parameter id with a description ('Source Clarity process id'), so the description does not need to add much. The description confirms the parameter refers to the process being duplicated, but it does not add additional semantic detail beyond what the schema already provides. This aligns with the baseline for full schema coverage.
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 'Duplicate' with the clear resource 'Clarity process' and enumerates exactly what gets copied: analysis, captures, message history, and for v2 processes, live current map and automation proposal. This distinguishes it from sibling tools like createClarityProcess, deleteClarityProcess, and duplicateAgent without needing to open their schemas.
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 its use case clearly: when you need to duplicate an existing Clarity process and preserve its associated data. It also adds the role prerequisite 'Requires a team manager role.' However, it does not explicitly state when to use this tool over createClarityProcess or how it differs from other duplication tools such as duplicateAgent.
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.