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gambot-ai

gambot-mcp

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Get contact fields

gambot_get_contact_fields

Retrieve contact field definitions including base and custom fields. Use these definitions to pass custom values via 'customFields' when creating or updating contacts.

Instructions

Get contact field definitions (base + custom/dynamic). Contacts store custom values as top-level keys — pass them via 'customFields' on create/update.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It reveals the return subject (base and custom/dynamic definitions), the storage convention for custom values, and the relevant create/update field. For a no-parameter read operation, this is adequate, though it does not detail auth or response shape.

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, front-loaded sentences. The first states the purpose clearly; the second adds meaningful operational context about how field definitions relate to create/update calls. No filler or redundancy.

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 zero-parameter, no-annotation getter, the description is nearly complete: it explains what is returned and how the output connects to customFields usage. The only minor gap is the lack of an exact shape for a field definition object, but the tool remains fully callable and understandable.

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

Parameters4/5

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

The input schema is an empty object with zero parameters, so there are no parameter semantics for the description to add. It still contributes useful context about the 'customFields' key, but no parameter documentation is needed.

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 states a specific verb and resource: 'Get contact field definitions (base + custom/dynamic)'. It distinguishes itself from sibling tools like get_lead_fields and get_case_fields by naming the contact resource, and from get_contact by clarifying it returns definitions, not values.

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 downstream context: custom contact values are stored as top-level keys and should be passed via 'customFields' on create/update. This implies when the output matters, but it does not explicitly name alternative field-definition tools or state when not to use this one.

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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