Skip to main content
Glama

Docflow Update Category Field

docflow_update_category_field

Update a document category field's name, description, or extraction prompt to refine data extraction and improve accuracy for specific field types.

Instructions

Update a field's name, description, or extraction prompt (POST /category/fields/update).

Updating the prompt can improve extraction accuracy for specific field types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
promptNo
field_idYes
category_idYes
descriptionNo
workspace_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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 states that the tool updates fields and adds a beneficial consequence of updating the prompt, but it does not mention whether updates are partial or full replacements, whether null values clear fields, what permissions are required, or any side effects. This is a significant transparency gap for a mutation tool.

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 only two sentences and wastes no words. The core action and endpoint are front-loaded, followed by a single useful usage note. Every sentence contributes meaningful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has six parameters, no annotations, and an output schema, so the description does not need to explain return values. However, it omits important operational details such as update semantics, constraints on null values, and whether all three optional fields can be omitted. These gaps make it only minimally adequate for correct invocation.

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 schema has 0% description coverage, so the description must compensate. It names three of the mutable parameters (name, description, prompt) and clarifies their purpose, but it leaves the three required identifier parameters (workspace_id, category_id, field_id) to be inferred from names. It also does not explain the nullable defaults or whether at least one optional field must be provided.

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 uses a specific verb ('Update') and resource ('a field's name, description, or extraction prompt'), and includes the exact POST endpoint. This clearly distinguishes it from sibling update tools like docflow_update_category and docflow_update_category_table, which target different resources.

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 clearly implies when to use this tool: when you need to modify a category field's name, description, or extraction prompt. The second sentence adds a concrete motivating scenario ('improve extraction accuracy for specific field types'), providing useful context, though it does not explicitly discuss alternatives or exclusions.

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