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Glama

Duvo MCP

by io.github.duvoai

Move Agent

moveAgent

Move an agent (and its connected workspace) to a different team. Pass dry_run=true to preview the closure without applying changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoWhen true, preview the closure and warnings without applying any changes.
agent_idYesThe ID of the agent to move.
target_team_idYesThe ID of the team to move the agent into.
bypass_standalone_gateNoWhen true, move the agent together with every connected queue, trigger, and handover peer instead of rejecting a non-standalone agent. Defaults to false.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds meaningful behavior beyond annotations by revealing that the connected workspace is moved and that the operation involves a 'closure' that can be previewed with dry_run. Annotations already signal mutation through readOnlyHint=false, and the description enriches this with concrete side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with no filler. The core action is front-loaded, and the dry-run guidance is placed second as a natural follow-up. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with full schema coverage and annotations, the description gives enough context: what is moved, what to preview, and that the operation can be dry-run. It does not explain return values or deeper closure consequences, but the absence of an output schema and the presence of the bypass_standalone_gate parameter in the schema make this acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all four parameters. The description mentions dry_run=true but does not add meaning beyond the schema. Baseline 3 is appropriate because the structured data already carries the parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific action ('Move'), a specific resource ('an agent and its connected workspace'), and the target ('to a different team'). This clearly differentiates it from siblings like moveAgentsToFolder or movePulseDashboard.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear operational context: moving an agent to a different team affects the connected workspace. It also provides a direct usage hint for dry_run=true. It does not explicitly enumerate alternatives or when-not-to-use, but the core use case is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation2/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness4/5

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.

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