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ProTech001
by ProTech001

mmar_update_attribute

Update an existing meta-attribute by providing its UUID and JSON data with the new name, default value, sequence, UI component, and attribute type.

Instructions

Update an existing meta-attribute. Send the updated attribute data including name, default_value, sequence, ui_component, and attribute_type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uuidYesThe UUID of the Attribute to update
attribute_dataYesJSON string of the updated Attribute data
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It does not specify whether the update is partial or full replacement, what happens if the attribute does not exist, side effects, or any permissions needed. This is a significant 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is front-loaded with the main action. It is concise and free of unnecessary words, though it could be improved with structured formatting for the list of fields. Still, it is efficient and readable.

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?

For a simple two-parameter update tool with full schema coverage, the description is minimally adequate: it states purpose and payload fields. However, it lacks essential behavioral context such as partial vs. full replacement, error handling, or return value expectations, leaving an agent uncertain about the update semantics.

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 already describes both parameters, giving a baseline of 3. The description adds value by listing the expected fields inside the 'attribute_data' JSON (name, default_value, sequence, ui_component, attribute_type), which clarifies what the JSON string should contain beyond the schema's generic wording.

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 clearly states the action ('Update an existing meta-attribute') with a specific verb and resource. It distinguishes from creation tools by emphasizing 'existing' and lists the key fields to update. This leaves no ambiguity about what the tool does.

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?

No explicit when-to-use or alternatives are provided. The description implies use for updating an existing attribute but does not contrast with create_attribute_for_class or other related tools, nor does it mention prerequisites or contexts where this tool is preferable.

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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