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awslabs

amazon-datazone-mcp-server

Official
by awslabs

list_project_profiles

List project profiles in an Amazon DataZone domain; supports pagination.

Instructions

Lists all project profiles available in an Amazon DataZone domain.

Args: domain_identifier (str): The ID of the domain max_results (int, optional): Maximum number of profiles to return (1-50, default: 50) next_token (str, optional): Token for pagination

Returns: Any: The API response containing the list of project profiles

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
next_tokenNo
max_resultsNo
domain_identifierYes
Behavior2/5

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

With no annotations, the description must fully disclose behavioral traits. It mentions pagination parameters but does not state ordering, filtering capabilities, rate limits, or that it is a read-only operation. The return type is vaguely described as 'API response' without detail.

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

Conciseness4/5

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

The description is structured with clear Args and Returns sections, which is helpful for an AI agent. It is relatively concise, but the Returns section is minimal and could be more informative without significant added length.

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?

Given the absence of an output schema, the description should elaborate on the return structure. It only states 'the API response containing the list of project profiles', which is insufficient. No error conditions or edge cases are mentioned. The tool has only three parameters, so basic completeness is adequate but not thorough.

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 schema has 0% description coverage, so the description must compensate. It provides meaningful descriptions for all three parameters: domain_identifier, max_results (with range and default), and next_token (pagination). This adds value beyond the schema, though domain_identifier format is not explained.

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?

The description clearly states the action (lists), resource (project profiles), and scope (in an Amazon DataZone domain). It effectively distinguishes from sibling tools like list_projects (lists projects) and get_project_profile (retrieves a single profile).

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives such as list_projects or search. Usage is implied for listing all project profiles in a domain, but no guidance on prerequisites or when to use is provided.

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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