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create_document_type

Create a document type in Paperless-NGX with an optional matching pattern and algorithm to automate document classification.

Instructions

Create a new document type with optional matching pattern and algorithm for automatic document classification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
matchNo
matching_algorithmNoMatching algorithm: 0=None, 1=Any word, 2=All words, 3=Exact match, 4=Regular expression, 5=Fuzzy word, 6=Automatic

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv2.2.1
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / matching_algorithm / description
      Added value: +"Matching algorithm: 0=None, 1=Any word, 2=All words, 3=Exact match, 4=Regular expression, 5=Fuzzy word, 6=Automatic"
    • removedInput schema / properties / matching_algorithm / enum
      Removed value: -[
      -  "any",
      -  "all",
      -  "exact",
      -  "regular expression",
      -  "fuzzy"
      -]
    • addedInput schema / properties / matching_algorithm / maximum
      Added value: +6
    • addedInput schema / properties / matching_algorithm / minimum
      Added value: +0
    • changedInput schema / properties / matching_algorithm / type
      Previous value: -"string"New value: +"integer"
  2. First observedv1.0.0

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 burden. It implies a write/mutation but says nothing about uniqueness of name, behavior on duplicate, permissions required, or what the created type looks like. Only the classification purpose hints at downstream behavior.

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?

A single front-loaded sentence with no filler; the optional parameters are noted up front. It is efficient, though it could be slightly richer given the missing behavioral detail.

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 mutation tool with no annotations and no output schema, the description leaves important gaps: side effects, name uniqueness/conflict handling, and return shape are unaddressed, and one of three parameters is undocumented in both schema and description.

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 coverage is only 33%: 'matching_algorithm' is fully documented in-schema (enum 0–6), while 'name' and 'match' are undocumented. The description partially compensates by framing 'match' as a matching pattern and both extras as optional, but gives no format or example for the pattern.

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 states a specific verb+resource ('Create a new document type') and adds the purpose ('for automatic document classification'), which distinguishes it from sibling read tools like get_document_type. It does not explicitly disambiguate from create_tag or create_correspondent, but the create+resource framing is clear.

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 explicit when-to-use guidance, no mention of alternatives like list_document_types or update_document_type, and no prerequisites. The phrase 'for automatic document classification' implies intent but leaves the agent to infer when to reach for this tool.

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