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LibreDesk MCP

LibreDesk MCP

by Passe12345

get_agents_compact

Retrieve a compact list of agents and AI assistants—ID, name, email, enabled status, and availability—for selecting a conversation assignee; use each returned ID as assignee_id.

Instructions

Get Agents Compact Agents and AI assistants in a short form (ID, name, email, enabled, availability), the list the web UI offers when assigning a conversation. Any authenticated agent, unlike get_agents which needs users:manage. Use the returned id as assignee_id of update_user_assignee. GET /api/v1/agents/compact Tags: Agents

Input Schema

NameRequiredDescriptionDefault
qNoCase-insensitive substring of the name (agents: also matched on the email) (query parameter)
idsNoComma-separated IDs (at most 200, non-numeric or non-positive entries are ignored). When given, only these are returned and every other filter and the pagination are ignored (query parameter)
pageNoPage number, used when page_size is set (query parameter)
typeNoKeep only this kind of user. Any other value is a 400 (query parameter)
enabledNoOnly the exact value `true` keeps the enabled users; anything else returns enabled and disabled ones (query parameter)
page_sizeNoItems per page, at most 500. 0 or absent: return every match (query parameter)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the burden; it does disclose the auth requirement (any authenticated agent vs users:manage) and the underlying endpoint, which are genuinely useful behavioral facts. It says nothing about pagination defaults, result caps, or error behavior — though the schema covers pagination and the enum errors, the read-scope behavior is only partly covered.

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

Conciseness4/5

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

The payload sentence and the sibling contrast are front-loaded and each earns its place, but the leading 'Get Agents Compact' line restates the tool name and the trailing 'GET /api/v1/agents/compact / Tags: Agents' boilerplate adds little for an agent.

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?

There is no output schema, and the description compensates by listing exactly which fields come back, plus the assignee_id follow-up use. Combined with the fully documented input schema, an agent has enough to call it correctly; only pagination/return-size behavior is left implicit.

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%, including enum values, the 200-id cap, and the ids-overrides-other-filters rule, so the baseline is 3. The description adds no additional parameter meaning beyond naming the returned fields, which is acceptable given the schema already documents all six parameters thoroughly.

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?

Names a specific verb and resource ('Agents and AI assistants in a short form') and enumerates the returned fields (ID, name, email, enabled, availability). It also positions the tool against the sibling get_agents by permission scope, so an agent can distinguish the two without opening either schema.

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?

Explicitly says any authenticated agent can call it, unlike get_agents which needs users:manage, and it tells the caller what to do with the result ('Use the returned id as assignee_id of update_user_assignee'). It gives no explicit when-not-to-use case or preference rule beyond the permission difference, so it stops short of full routing guidance.

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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