listOrgTeamsList teams belonging to an organization you are a member of, including your membership and role in each.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of teams per page (1-100, default 50) | |
| orgId | Yes | Organization ID | |
| offset | No | Number of teams to skip | |
| search | No | Filter teams by name (case-insensitive substring match) | |
| sortBy | No | Sort order: createdAt (newest first, default) or name (alphabetical) | createdAt |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is known. The description adds valuable context by noting that the response includes the user's membership and role in each team, and that the organization must be one the user belongs to, implying an authorization requirement. This goes beyond the annotations without contradicting them.
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, tightly written sentence that is front-loaded with the primary purpose ('List teams belonging to an organization') and immediately adds the membership/role qualifier. There is no redundant or filler content; every word 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?
For a read-only list operation with rich schema descriptions and safety annotations, the description is nearly complete. It clarifies the org membership requirement and the inclusion of membership/role in results. However, given the presence of similar sibling tools like listMyTeams and the lack of an output schema, a brief note about pagination or a direct contrast with listMyTeams would have made it fully unambiguous. Overall, it is adequate but not exhaustive.
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 input schema covers all parameters with descriptions (100% coverage), including limit, offset, search, and sortBy. The description adds semantic value to orgId by specifying that the organization must be one the user is a member of, which is not stated in the schema's simple 'Organization ID' description. This extra context justifies a score above the baseline of 3.
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 tool's function: listing teams belonging to an organization the user belongs to, and specifically mentions that membership and role are included. This differentiates it from siblings like listMyTeams, which likely lists teams across all organizations, and listMyOrganizations. The verb 'list' plus the resource 'teams' and the scope 'organization you are a member of' make the purpose unambiguous.
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 the tool is used when you need teams for a specific organization you belong to, and the required orgId parameter confirms this. However, it does not explicitly state alternatives or when not to use it, such as pointing to listMyTeams for cross-organization views or listMyOrganizations for org discovery. The guidance is implied rather than explicit.
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.