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callremind

CallRemind MCP Server

Official
by callremind

updateAgent

Update an existing AI agent's settings, such as name, goal, voice, and start message, to keep call agent details accurate and current.

Instructions

Update fields on an existing AI agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesAgent id
goalNo
nameNo
voiceNo
owner_emailNoIgnored for user API keys; required only with system API key
agent_start_messageNo

Schema Changelog

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

  1. First observedv1.0.6

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It only says 'Update fields' and does not disclose partial-update semantics, required fields, permission requirements, return values, or 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.

Conciseness4/5

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

The description is a single, direct sentence with no wasted words. It is front-loaded with the action and resource, though it may be too terse to fully support correct invocation.

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

Completeness2/5

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

For a 6-parameter mutation tool with no annotations and no output schema, this description is far too minimal. It omits critical information about update behavior, parameter roles, and expected outcomes, leaving the agent to infer too much.

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

Parameters2/5

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

Schema description coverage is only 33% (2 of 6 parameters have descriptions), and the description does not compensate by explaining what fields can be updated. The word 'fields' adds little meaning beyond the schema property names, leaving most parameters semantically underdocumented.

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 clearly states the verb 'Update' and the resource 'existing AI agent', making the tool's purpose understandable. It distinguishes itself from createAgent by specifying 'existing', but it does not explicitly name or contrast sibling tools.

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?

Usage context is implied by the word 'existing'—use this when modifying an agent rather than creating a new one. However, there is no explicit guidance on when to choose this tool over createAgent or other sibling tools, and no alternative tools are named.

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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