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aws_resource_get

Read-onlyIdempotent

Read a single AWS resource via Cloud Control API using its CloudFormation type name and primary identifier, returning parsed properties.

Instructions

Read a single AWS resource via Cloud Control API. Covers hundreds of resource types with a CloudFormation schema. typeName is '::::' (e.g. 'AWS::Lambda::Function'); identifier is the primary key for that type (function name, bucket name, IAM role name, ARN, or composite id). Returns parsed Properties. For resources not covered by CCAPI or for data-plane operations, use aws_call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionNoOverride session region for this call.
profileNoOverride session profile for this call.
typeNameYesCloudFormation type name, e.g. 'AWS::Lambda::Function', 'AWS::S3::Bucket', 'AWS::IAM::Role'.
timeoutMsNoTimeout in milliseconds. Default 60000.
identifierYesPrimary identifier for the resource (function name, bucket name, ARN, or composite id).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds that it returns parsed Properties and clarifies identifier formats, adding value beyond annotations.

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?

Three sentences, front-loaded with purpose, then format and usage guidance. No wasted words.

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?

Covers all parameters and return type, with proper use cases. Lacks mention of error handling or permissions, but given simplicity of a read operation, it is largely complete.

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

Parameters5/5

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

Schema coverage is 100%, but description adds meaningful context: typeName format with example, identifier examples (function name, bucket name, etc.), and timeout default. This exceeds the baseline.

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?

Description clearly states 'Read a single AWS resource via Cloud Control API' and specifies it covers hundreds of resource types. It distinguishes from sibling aws_call by noting when to use that alternative.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly contrasts with aws_call for non-CCAPI or data-plane operations. Could mention other siblings like aws_resource_list, but the guidance is clear for its primary use case.

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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