acceptClarityLandscapeNodeAccept a proposed area folder into the active process landscape, so it stops being a proposal and becomes part of the real structure (organization admin+). Only area folders can be accepted; a proposed process becomes real through assignClarityLandscapeNodeTeam instead. Re-accepting an already-active area is a no-op.
| Name | Required | Description | Default |
|---|---|---|---|
| orgId | Yes | ||
| nodeId | Yes | The proposed area folder to accept. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that this is a state-changing mutation (accepting a proposal), not destructive (re-accepting is a no-op), and requires admin privileges. Annotations already indicate destructiveHint=false, but the description adds context about authorization and the no-op behavior, which are valuable beyond the structured fields.
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?
Three concise sentences front-loaded with the core purpose, followed by a clear exclusion and an edge case. No unnecessary words or repetition. Every sentence earns its place.
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 description covers the essential behavior, usage boundaries, and a key edge case. With only 2 parameters, no output schema, and basic annotations, this is largely complete. It does not explain return values or error handling, but for a simple acceptance action, the description provides sufficient context for an agent to select and invoke the tool correctly.
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 50% (only nodeId has a description). The tool description adds meaning by clarifying that nodeId is the proposed area folder, and the overall context explains orgId is the organization (via 'organization admin+'). However, orgId is not explicitly described in the tool description, leaving a slight gap. Still, it adds value beyond the 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 clearly states the verb 'Accept', the resource 'proposed area folder', and the outcome: it stops being a proposal and becomes part of the real structure. It also distinguishes from the sibling tool 'assignClarityLandscapeNodeTeam' by specifying that only area folders are accepted via this tool, while processes go through the other.
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?
Explicitly states when to use this tool (only for area folders) and when not to use it (proposed processes use assignClarityLandscapeNodeTeam instead). Also mentions the authorization requirement ('organization admin+') and the edge case that re-accepting an already-active area is a no-op, providing clear usage boundaries.
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.