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AWS Notebook Runner MCP

get_sagemaker_notebook_job_spec

Retrieve a SageMaker NotebookJobStep specification to plan and preview a notebook run without execution.

Instructions

Return the SageMaker NotebookJobStep spec for a dry-run plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
local_pathYes
job_nameYes
image_uriYes
kernel_nameNopython3
instance_typeNo
max_runtime_secondsNo
parametersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description must convey behavior. It says 'Return the spec' implying a read-only operation, but it does not disclose whether the tool has side effects, requires authentication, or triggers any AWS actions. Behavioral traits like idempotency or error states are absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is concise but severely underspecified. It lacks any structure such as bullet points or sections that would improve readability. The brevity comes at the expense of necessary detail.

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

Completeness1/5

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

Given 7 parameters, no schema descriptions, and no annotations, the description is far from complete. It does not explain how to use the parameters, what the output spec includes (despite an output schema existing), or any contextual information about dependencies or limitations. The agent would lack critical details to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 7 parameters with 0% description coverage, and the tool description does not explain any parameters. The description adds no meaning beyond the schema property names, failing to clarify what local_path, job_name, image_uri, or other parameters represent or how they are used.

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 tool returns a SageMaker NotebookJobStep spec for a dry-run plan. The verb 'Return' is specific and the resource is named, distinguishing it from sibling tools like plan_notebook_job or start_sagemaker_notebook_job. However, it could be more precise about what 'dry-run plan' means in this context.

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 such as plan_notebook_job or estimate_notebook_job_cost. There is no mention of prerequisites, exclusions, or context for usage.

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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