generateClarityProcessLandscapeStart a process-landscape generation run for the organization from its eligible Clarity captures (organization executives and owners)
| Name | Required | Description | Default |
|---|---|---|---|
| orgId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, idempotentHint=false, destructiveHint=false, but they do not describe the run behavior. The description adds that it starts a 'generation run' and uses 'eligible Clarity captures', implying an asynchronous, non-read-only operation. However, it does not clarify whether it creates a new landscape, overwrites existing data, or how long the run might take.
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 sentence of about 23 words, front-loaded with the action and resource. It contains no filler or redundant information, making it exceptionally concise and well-structured.
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?
With one parameter, no output schema, and sparse annotations, the description provides the core purpose but leaves gaps: it does not state what the tool returns (e.g., a run ID) or what 'eligible Clarity captures' means. It is adequate for selection but not fully complete for an agent expecting to know the outcome of starting a generation run.
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 0%—the orgId parameter has only format 'uuid' with no description. The description mentions 'for the organization', giving some contextual meaning to the orgId parameter. However, it does not fully compensate by explaining what 'eligible' means or how the orgId is used beyond that.
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 'Start' and a clear resource 'process-landscape generation run', and further specifies the source: 'eligible Clarity captures (organization executives and owners)'. This clearly distinguishes it from siblings like getClarityProcessLandscape or createClarityLandscapeNode by focusing on initiating a generation run.
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 usage (initiate a landscape generation run) and provides context about the source data, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. For example, it does not say 'use getClarityProcessLandscape to retrieve generated results'.
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.