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. |
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?
The description discloses useful context: organization admin+ permission, area-folder-only constraint, and no-op behavior on re-acceptance. However, it directly contradicts the annotation 'idempotentHint: false' by asserting that re-accepting an already-active area is a no-op, which implies idempotent behavior.
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 three sentences with no filler. It front-loads the core purpose, then adds the key constraint, the alternative tool, and the no-op edge case. Every sentence carries useful information.
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 purpose, permissions, constraints, and an alternative, but the idempotency contradiction makes the behavioral model unreliable for an agent. Additionally, orgId is left undocumented in both the schema and the description, leaving a meaningful gap for a two-parameter tool.
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 only 50%, with nodeId described but orgId not. The description adds meaning by clarifying that nodeId refers to a proposed area folder and that only area folders are valid, but it does not explain orgId beyond its parameter name, leaving part of the input semantics underspecified.
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 ('Accept') and resource ('proposed area folder'), clearly explaining the state transition from proposal to active structure. It also distinguishes itself from assignClarityLandscapeNodeTeam, so an agent can tell them apart.
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 explicitly states when to use this tool (accepting proposed area folders) and when not to ('proposed process becomes real through assignClarityLandscapeNodeTeam instead'). It also clarifies the no-op behavior for already-active areas, giving clear operational guidance.
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.