Skip to main content
Glama

Set model attributes

aris_set_model_attributes
Idempotent

Write or update attributes on an ARIS model by supplying a model_id and attributes object, such as the kg_intelligence blob.

Instructions

Write/update attributes on a model (e.g. the kg_intelligence blob).

Input Schema

NameRequiredDescriptionDefault
model_idYes
attributesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.1

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the description need not restate the safety profile. The example ('kg_intelligence blob') adds a small amount of domain context about the attribute payload, but the description does not clarify merge-vs-replace semantics, permissions, or other behavioral details beyond what annotations provide.

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 front-loaded sentence with no wasted words. It is efficient, though its extreme brevity leaves important details unstated, which is a completeness issue rather than a conciseness one.

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 tool that writes an arbitrary nested attributes object with zero schema descriptions and no output schema, the description is inadequate. It provides only a lone example and omits parameter details, write behavior, and any operational guidance, though annotations cover the safety profile.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the burden of explaining parameters, yet it gives only a vague example attribute name. It does not describe the model_id format, the shape of the attributes object, or which fields are required, leaving both required parameters effectively undocumented.

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 (Write/update) and resource (attributes on a model), making the tool's purpose immediately clear. It does not explicitly differentiate from siblings like aris_set_object_attributes, but the model-vs-object scope is inferable from the name and description.

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 on when to use this tool versus alternatives, no prerequisites, and no exclusions. The description only says what it does, leaving the agent to infer when it is appropriate.

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