Skip to main content
Glama
dgallitelli

SageMaker AI MCP Server

by dgallitelli

describe_pipeline_execution_sagemaker

Retrieve detailed information about a SageMaker Pipeline Execution by providing its ARN, including status, steps, and results.

Instructions

Describe a SageMaker Pipeline Execution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipeline_execution_arnYesThe ARN of the SageMaker Pipeline Execution to describe

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

No annotations are present, and the description gives no behavioral details such as permissions, error handling, read-only guarantees, or potential side effects. The word 'describe' implies a read operation, but nothing is disclosed beyond that.

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 short (one sentence) but under-specified. It does not earn its place because it simply restates the tool name without adding useful information. Concise is not the same as minimal to the point of uselessness.

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

Completeness2/5

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

Given the simplicity (one required parameter) and the presence of an output schema, the description need not explain return values. However, it lacks any contextual framing about what a SageMaker Pipeline Execution is, what information is returned, or when to use this tool. The bare description is inadequate for an agent to confidently select and invoke the 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 covers the single parameter fully (100% coverage), so the baseline is 3. The description adds no parameter semantics beyond what the schema already states, but the schema adequately documents the pipeline_execution_arn parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Describe a SageMaker Pipeline Execution' is a tautology that merely restates the tool name. It does not provide any specifics about what the 'describe' operation returns or how it differs from sibling tools like describe_pipeline_sagemaker or describe_training_job_sagemaker.

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

Usage Guidelines1/5

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 the many sibling describe_* tools. No context, prerequisites, or alternative suggestions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dgallitelli/sagemaker-ai-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server