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SageMaker AI MCP Server

by dgallitelli

describe_training_job_sagemaker

Get full details of an Amazon SageMaker Training Job, including status, configuration, and logs, by providing the training job name.

Instructions

Describe a SageMaker Training Job

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
training_job_nameYesThe name of the SageMaker Training Job to describe

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. 'Describe' clearly implies a read-only operation, but the description does not add details about what information is returned, permission requirements, or failure behavior. It is minimal but not misleading, so a score of 3 is appropriate.

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, front-loaded sentence that states the essential purpose without any filler. Every word contributes to clarity, making it highly concise and well-structured for the tool's simplicity.

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

Completeness4/5

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

For a simple describe operation with a single parameter and an output schema present, the description is nearly complete. It does not explain return values, but the output schema serves that purpose. The only minor gap is the lack of explicit context about when to use this tool, but that is already covered under usage guidelines.

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 input schema covers 100% of the parameters, including a clear description for the required training_job_name. The tool description itself adds no additional parameter-level meaning, so the baseline of 3 applies.

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 'Describe a SageMaker Training Job' clearly identifies the action (describe) and the resource (SageMaker Training Job). It distinguishes from sibling tools that target other resources like pipelines, endpoints, or models.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through the verb 'describe' and the resource name, but it does not explicitly state when to use this tool versus alternatives such as list_training_jobs_sagemaker. No exclusions or alternative recommendations are provided, so the usage context is inferred rather than explicit.

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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