upgradeClarityProcessMove a v1 clarity process into v2. Rows with generated analysis are reset in place and regenerated; rows without analysis migrate in place when not generating.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide only basic mutation flags (readOnlyHint=false, idempotentHint=false, destructiveHint=false). The description adds value by disclosing that rows with generated analysis are reset and regenerated, while rows without analysis migrate in place. This gives important behavioral context, but it omits details on reversibility, error handling, or side effects, which would be useful for a v1-to-v2 migration.
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 long, front-loaded with the core purpose, and includes additional behavioral detail without redundancy. Every sentence contributes meaning, making it efficient and scannable.
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 complexity of a v1-to-v2 upgrade and the lack of annotations and output schema, the description covers the core transformation but leaves gaps: it does not clarify whether the process is mutated in place or a new version is created, nor does it address metadata or other process aspects. It is minimally adequate but not thorough.
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 single required parameter 'id' has no description in the input schema (0% schema description coverage), and the tool description does not explain what the 'id' refers to or how it is used. Since the description must compensate for low schema coverage but fails to do so, this scores very low.
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 clearly states the action: 'Move a v1 clarity process into v2.' It also explains the behavioral difference for rows with and without generated analysis. However, it does not explicitly distinguish this tool from siblings like updateClarityProcess or duplicateClarityProcess, which could serve related but different purposes.
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 that this tool is used for upgrading a v1 process to v2, but it provides no explicit guidance on when to use it versus alternatives, nor does it specify prerequisites or when not to use it. The context of sibling tools suggests a clear niche, but the description itself lacks explicit usage direction.
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.