list_regions
Retrieve all available geographic regions for Amazon Advertising API operations to configure campaign targeting and management.
Instructions
List all available regions
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve all available geographic regions for Amazon Advertising API operations to configure campaign targeting and management.
List all available regions
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'List all available regions' implies a read-only operation, it doesn't specify whether this requires authentication, how results are returned (e.g., pagination, format), or any rate limits. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded and appropriately sized for a simple list operation, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is minimally adequate. However, without annotations or output schema, it lacks details on return values (e.g., format, structure) and behavioral context, leaving gaps that could hinder an agent's ability to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't add parameter details beyond this, but with no parameters, a baseline score of 4 is appropriate as there's nothing to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all available regions' clearly states the verb ('List') and resource ('regions'), making the tool's purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'get_region' (which presumably retrieves a specific region), so it doesn't fully distinguish from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'get_region' or other sibling tools. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/KuudoAI/amazon_ads_mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server