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pvliesdonk
by pvliesdonk

Create Custom Field

create_custom_field

Create a custom field in Paperless to store metadata such as text, numbers, dates, or select options. Specify name and data type; include extra_data for select choices or default currency.

Instructions

Create a new custom field.

extra_data depends on data_type:

  • string, longtext, integer, boolean, float, date, url, documentlink — unused; omit or pass null.

  • monetary — optional {"default_currency": "USD"} (ISO-4217).

  • select — extra_data required: {"select_options": [{"label": "Low"}, {"label": "Medium"}]}. Paperless assigns each option a stable id on creation.

Unknown shapes are rejected by Paperless with a 400.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
nameYes
data_typeYes
extra_dataNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=false and destructiveHint=false, so no contradiction exists. The description adds valuable behavioral context beyond annotations: extra_data is conditionally required based on data_type, Paperless assigns stable option ids on creation, and invalid shapes result in a 400 error.

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 appropriately sized and front-loaded with the core action, then uses a compact bulleted list to cover the complex conditional parameter behavior. Every sentence and bullet contributes necessary information with no fluff or repetition.

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 create operation with a nested body and data-type-dependent behavior, the description covers the essential validation rules and the error response for invalid shapes. The output schema is available to explain return values, and annotations cover idempotency and read-only hints, so nothing critical is missing.

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 schema has 0% description coverage, so the description carries the burden for parameter meaning. It thoroughly explains the extra_data parameter across all data_type variants, including requiredness and exact shape for select and monetary. It does not explicitly describe name, but that parameter is self-evident and the schema marks it required.

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: "Create a new custom field." It clearly distinguishes this from sibling tools like update_custom_field and delete_custom_field through the "create" verb and "new" qualifier, and from other resource create tools through the resource name.

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?

There is no guidance about when to use this tool versus alternatives, such as update_custom_field or list_custom_fields. The only usage signal is the word "Create," which implies intent but does not provide context, prerequisites, or exclusions.

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