aris-mcp

Aris Get Model Attributes

aris_get_model_attributes

Read-onlyIdempotent

Retrieve a model's attributes, such as AT_NAME and kg_intelligence, by supplying its GUID or AML Model.ID to inspect model metadata.

Instructions

Get a model's attributes (for example AT_NAME and kg_intelligence).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model_id": "<model_id>"
    },
    "name": "aris_get_model_attributes"
  }
}

Input Schema

Name	Required	Description	Default
`model_id`	Yes	Model GUID (or AML Model.ID).

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv2.0.0Nov 7, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds only the hint that attributes have names like AT_NAME and kg_intelligence; it says nothing about whether attributes are a fixed list, how they are keyed, or behavior on an unknown model_id.

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?

One short sentence, front-loaded with the verb and resource, with no padding. It is arguably too terse for the guidance it omits, but nothing written is wasted.

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 is simple (one required param), annotations cover its safety profile, and an output schema exists so return values need not be described. However, in a family of fourteen aris_* siblings including aris_get_model and aris_set_model_attributes, the definition gives no routing guidance, leaving a real gap for a retrieval tool.

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 100% and the single parameter model_id already documents 'Model GUID (or AML Model.ID)'. The description adds no additional syntax, format or validation meaning beyond that, so the baseline 3 applies.

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 names a specific verb and resource (get a model's attributes) and lists two example attribute keys (AT_NAME, kg_intelligence), which tells an agent this returns attribute-level metadata rather than the model itself. It does not explicitly distinguish itself from aris_get_model or aris_set_model_attributes, but the get/set pair is inferable.

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 statement of when to use this versus aris_get_model, which presumably returns broader model data, or versus the sibling setters. The agent must infer that this is the read counterpart of aris_set_model_attributes from the name alone.

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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