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dgallitelli

SageMaker AI MCP Server

by dgallitelli

list_transform_jobs_sagemaker

Lists Amazon SageMaker transform jobs to monitor batch inference progress and manage job lifecycle.

Instructions

List SageMaker Transform Jobs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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. It only says 'List SageMaker Transform Jobs' which is essentially the operation name itself. It does not mention pagination, ordering, region scope, output shape, or any other behavioral traits, leaving the agent with no insight beyond the name.

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, compact sentence that immediately conveys the operation. No filler or unnecessary details, making it highly efficient and front-loaded.

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 zero-parameter listing tool, the description is adequate to convey its primary purpose, and the existence of an output schema likely covers return values. However, it lacks guidance on when to use it (e.g., in workflows) and any constraints like available filters or result limits, making it only minimally complete.

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 input schema has zero parameters, so the baseline is 4. The description appropriately says nothing about parameters, and there is nothing more to explain about them.

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 clearly states the action ('List') and the resource ('SageMaker Transform Jobs'), distinguishing it from sibling list tools that target other SageMaker resources (e.g., training jobs, processing jobs). It is specific, though it does not elaborate on scope or any special behavior.

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 guidance is provided on when to use this tool versus alternatives. It does not mention that this is for enumerating transform jobs, nor does it direct users to describe_transform_job for details on a specific job. The lack of any contextual hints makes it harder for an agent to decide if this is the right list tool.

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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