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Glama

mdan_consult_agent

Read-only

Consult a specialized agent persona to get in-character answers with layered customization and memory. Choose the right expert to address your question directly.

Instructions

Load an MDAN agent persona (with layered customization and its memories) to answer in character

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesAgent name (see mdan_list_agents)
questionNoQuestion or topic to discuss with this agent

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.1.1

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already mark the tool readOnlyHint=true, which covers the safety profile. The description adds that the loaded persona carries 'layered customization and its memories,' which is useful behavioral context, but it does not disclose response behavior, side effects, or any preconditions beyond what the schema already states.

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?

The description is a single efficient sentence that front-loads the action ('Load an MDAN agent persona') and compresses the behavioral intent. No filler or redundant phrases are present.

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 read-only consult tool with a 31-value enum and an optional question, the description gives enough to understand the core interaction: load a persona and get an in-character answer. It does not describe an output schema (there is none) and does not clarify why the question is optional given the described purpose, but these are minor gaps.

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%, and the schema already explains both parameters ('Agent name (see mdan_list_agents)' and 'Question or topic to discuss'). The description adds no parameter-specific meaning beyond the schema, so the baseline 3 applies.

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

Purpose4/5

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

The description uses a specific verb ('Load') and identifies the resource ('MDAN agent persona') and the intent ('to answer in character'), so an agent can tell this is a consult/persona-loading tool. It does not explicitly differentiate from nearby siblings like mdan_customize_agent or mdan_list_agents, so it stops short of full sibling discrimination.

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

Usage Guidelines3/5

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

The phrase 'to answer in character' implies the natural use case: ask a persona a question. However, there is no explicit guidance on when not to use it or how it relates to alternatives such as mdan_customize_agent or mdan_memory_recall, leaving the agent to infer the boundary.

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