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gray-wilbee

fub-mcp

by gray-wilbee

update_appointment_type

Keep appointment types up to date by modifying their name, sort order, or custom fields in Follow Up Boss.

Instructions

Update an appointment type. (PUT /appointmentTypes/{id})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
nameNoThe name of the appointment type.
extraBodyNoExtra raw JSON body fields not explicitly listed above — e.g. custom.* fields when creating/updating people or deals. Keys and values are sent as-is.
extraQueryNoExtra raw query parameters not explicitly listed above — e.g. FUB custom field filters like custom.ClosingDate on /people or /deals. Keys and values are sent as-is.
orderWeightNoSet this value to enforce a specific sort order.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Update', implying a mutation, but reveals nothing about side effects, required permissions, idempotency, or what happens on partial updates. The HTTP method 'PUT' is mentioned but adds no meaningful behavioral context beyond what the verb already implies.

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

Conciseness3/5

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

The description is extremely short (one sentence) and easy to parse, but it is under-specified rather than efficiently concise. It front-loads the endpoint but omits any substantive guidance. It is not verbose, but the brevity comes at the cost of usefulness.

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?

The tool has 5 parameters including nested objects (extraBody, extraQuery) and no output schema. The description offers no explanation of how these parameters interact, what the update semantics are, or what the response might look like. Given the moderate complexity, the description is inadequate for an agent to confidently invoke the tool correctly.

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?

The input schema already provides descriptions for 4 of 5 parameters (80% coverage), including details for extraBody and extraQuery. The tool description adds no additional parameter information, but the schema is sufficiently self-documenting. Baseline 3 is appropriate since the description does not need to compensate for a coverage gap.

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 'appointment type', making the core purpose understandable. However, it does not differentiate this from sibling tools like update_appointment or update_appointment_outcome, which have similar update semantics. The HTTP endpoint mention adds minor specificity but does not distinguish the tool's unique role.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, typical scenarios, or exclusions. An agent must infer from the name alone, which is insufficient given the large sibling set.

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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