Amazon SageMaker Well-Architected MCP Server

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get_pillar_details

Retrieve a pillar's description and validation checks, enabling you to assess SageMaker workloads against the AWS Well-Architected Framework.

Instructions

Get detailed information about a specific Well-Architected pillar and its checks.

    Returns the pillar description and all validation checks that are performed
    for the specified pillar.

    Args:
        ctx: MCP context
        pillar: Pillar name

    Returns:
        PillarInfoResponse with pillar details and checks

Input Schema

TableJSON Schema

Name	Required	Description	Default
`pillar`	Yes	Pillar name: security, reliability, performance, cost, operational_excellence, or sustainability.

Output Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Pillar name
`checks`	Yes	List of checks for this pillar
`content`	Yes	Response content
`isError`	No	Whether this is an error response
`description`	Yes	Pillar description

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 6, 2026

TDQS

B3.4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the behavioral-disclosure burden. It clearly implies a read operation and states the return contents, which is useful, but it does not mention permissions, invalid-pillar behavior, or any other side effects. Core behavior is adequately described, but with gaps.

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

Conciseness3/5

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

The opening sentence is clear and front-loaded, but the Returns line largely repeats the first sentence, and the Args/Returns blocks duplicate what the schema and output schema already provide. The description is compact but contains redundant docstring sections.

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 single-parameter read operation with an output schema available, the description is largely complete: it names the target pillar, the returned data, and the checks included. It lacks usage guidance around siblings and edge-case behavior, but these are minor for this simple 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?

Schema description coverage is 100%, and the pillar parameter already has a descriptive enum-like list of valid values. The description only repeats 'pillar: Pillar name' and adds no meaning beyond the schema, so the baseline score of 3 is appropriate.

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?

States a specific operation (get) and resource (a Well-Architected pillar), and explicitly describes what is returned: the pillar description and all validation checks. This helps an agent distinguish it from sibling tools, which focus on validating SageMaker resources rather than fetching pillar details.

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 explains what the tool does but gives no guidance on when to use it versus the sibling validation tools or list_sagemaker_resources. No alternatives, exclusions, or contextual triggers are mentioned.

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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