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dgallitelli

SageMaker AI MCP Server

by dgallitelli

list_processing_jobs_sagemaker

Lists Amazon SageMaker processing jobs to view status, configuration, and outputs for monitoring and management.

Instructions

List SageMaker Processing 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the tool's name without adding details about pagination, filtering, read-only semantics, or any other behavioral traits. This is insufficient for a tool with zero annotation coverage.

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 unnecessary words. It is front-loaded and appropriately sized for a simple list operation, earning the maximum score for conciseness.

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 has no parameters and an output schema, so the description need not explain return values. However, it lacks usage guidance and behavioral transparency, making it only minimally complete for an agent tasked with selecting among many similar sibling tools.

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 does not add parameter-specific meaning, which is appropriate since there are no parameters to document. No additional semantics are needed beyond the schema.

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 identifies the action ('List') and resource ('SageMaker Processing Jobs'), stating exactly what the tool does. However, it does not explicitly distinguish this from sibling list tools such as list_training_jobs_sagemaker or list_transform_jobs_sagemaker, so it falls short of a 5.

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?

The description provides no guidance on when to use this tool versus alternatives like describe_processing_job_sagemaker for a single job or other list_*_jobs tools. There are no mentions of use cases, exclusions, or preferred scenarios.

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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