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dgallitelli

SageMaker AI MCP Server

by dgallitelli

describe_model_sagemaker

Retrieve detailed information about an Amazon SageMaker model by its name, including configuration, status, and other metadata.

Instructions

Describe a SageMaker Model

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_nameYesThe name of the SageMaker Model to describe

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 only says 'Describe' without explicitly stating that the operation is read-only, requires any specific permissions, or returns a representation of the model. The description adds no context beyond what the name alone implies.

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 a single, concise sentence with no redundant phrasing. It is appropriately sized for a tool with one parameter and an output schema, with every word earning its place.

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?

Given the simplicity of the tool (one parameter, output schema present), the description provides a minimally viable purpose. However, it lacks usage guidance and any behavioral notes, creating noticeable gaps. It is adequate but not comprehensive for a reader who needs to decide when and how to invoke this 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?

The schema fully documents the only parameter (model_name) with a clear description, achieving 100% coverage. The tool description adds no additional parameter semantics, so the baseline of 3 applies. There is no need for the description to re-explain what the schema already covers.

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 uses a clear verb+resource pattern ('Describe a SageMaker Model') and names the resource type, distinguishing it from sibling tools like describe_pipeline_sagemaker and describe_endpoint_sagemaker. However, it does not elaborate on what specific aspects of the model are described (e.g., configuration, status), leaving some ambiguity about the exact scope.

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 such as list_models_sagemaker or other describe_* tools. The description simply states what it does without indicating prerequisites, exclusions, or preferred contexts.

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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