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bestpractical

mcp-server-rt

Official

create_custom_field

Destructive

Create custom fields for Request Tracker tickets, queues, users, assets, or articles. Set type, validation pattern, entry hint, and allowed values, then apply the field to queues or globally.

Instructions

Create a new custom field. After creating, use apply_custom_field to apply it to specific queues or globally. Use add_custom_field_value to add values to Select-type fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
NameYesCustom field name
TypeYesField type
PatternNoRegex validation pattern (e.g. "(?#Mandatory)." for required)
EntryHintNoHint text shown to users when entering values
MaxValuesNo0 for unlimited, 1 for single-value (default depends on Type)
LookupTypeYesWhat object type this CF applies to
DescriptionNoField description

Schema Changelog

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

  1. Addedv0.3.0

TDQS

A4.2/5.0
Behavior4/5

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

The annotations include destructiveHint=true, so the agent already knows this is a state-changing operation. The description adds useful behavioral context beyond the annotation: a newly created custom field is not automatically applied, and Select-type fields require additional value population. There is no contradiction with the annotations.

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 sentences with no wasted words. The primary action is front-loaded, and the follow-up guidance is directly actionable. Every sentence adds value.

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 tool with 7 parameters, the schema covers all parameter details, and the description covers the essential post-create workflow. There is no output schema, so the description could have mentioned expected return behavior, but the critical creation and follow-up context is present. Minor gap only.

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%, so the parameters are already fully documented in the schema. The description adds a small workflow note relevant to the Type parameter (Select-type fields need values), but it does not substantially explain the parameters themselves. The baseline of 3 is appropriate given full schema coverage.

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 action ('Create a new custom field') with a clear resource. It also distinguishes itself from related tools by referencing apply_custom_field and add_custom_field_value as follow-up actions, making its role in the workflow unmistakable.

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 provides explicit workflow context: after creating a custom field, apply it with apply_custom_field, and add values to Select-type fields with add_custom_field_value. It does not explicitly list when not to use this tool, but the guidance is clear enough for an agent to select it appropriately among the sibling tools.

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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