Retrieve AWS Cost and Usage Report configurations from Datadog to monitor and analyze cloud spending data.
List the AWS CUR configs.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "get_cost_aws_cur_configs"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List' implies a read-only operation, but the description doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what format the output takes. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.
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 with the core action and resource, making it immediately clear what the tool does. Every word earns its place, and there's no unnecessary elaboration.
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?
For a simple list operation with no parameters and no output schema, the description is minimally adequate. However, without annotations or output schema, it should ideally mention something about the return format or behavior (e.g., 'returns an array of CUR configuration objects'). The description meets basic requirements but leaves the agent guessing about the response structure.
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 no parameter documentation is needed. The description appropriately doesn't discuss parameters, which is correct for a parameterless tool. It focuses on the action and resource, which is sufficient given the empty input schema.
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 the AWS CUR configs' clearly states the verb ('List') and resource ('AWS CUR configs'), making the tool's purpose immediately understandable. It distinguishes from sibling tools by specifying the AWS CUR configs resource, though it doesn't explicitly differentiate from similar list operations like 'get_cost_azure_uc_configs' or 'get_cost_gcp_uc_configs' beyond the resource name.
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. There are no explicit when/when-not instructions, no mention of prerequisites, and no comparison to sibling tools like 'create_cost_aws_cur_configs' or 'update_cost_aws_cur_configs'. The agent must 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.