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TypeScript
Remote

get_cloud_resource_facet_value

Retrieve specific facet values from cloud providers like AWS, GCP, Azure, or Linode to support security analysis and resource management in cloud environments.

Instructions

Get values for a specific facet from a cloud provider

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "provider": "<provider>",
      "facet_id": "<facet_id>"
    },
    "name": "get_cloud_resource_facet_value"
  }
}

Input Schema

NameRequiredDescriptionDefault
providerYesCloud provider (aws, gcp, azure, linode)
facet_idYesID of the facet

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden but lacks behavioral details. It doesn't disclose if this is a read-only operation, what permissions are needed, how results are formatted, or any rate limits. The description is too minimal to inform the agent adequately about how the tool behaves beyond its basic purpose.

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 a single, efficient sentence with no wasted words, making it easy to parse. However, it could be more front-loaded with critical context (e.g., clarifying 'facet' or usage), but as-is, it's appropriately concise for its limited content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete for a tool that likely returns data values. It doesn't explain what 'values' are returned (e.g., strings, lists, structured data), error conditions, or how to interpret results. For a tool with two parameters and potential complexity, this leaves significant gaps for the agent.

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%, with clear descriptions for both parameters (provider and facet_id), including an enum for provider. The description adds no extra meaning beyond the schema, such as explaining what a facet_id represents or examples of facet types. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the action ('Get values') and resource ('for a specific facet from a cloud provider'), which is clear but vague. It doesn't specify what a 'facet' is or how it differs from sibling tools like 'get_cloud_resource_facets' or 'get_cloud_resource_details', leaving room for confusion about its exact scope.

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?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'get_cloud_resource_facets' (likely listing facets) and 'get_cloud_resource_details' (likely broader details), the description offers no context for selection, leaving the agent to guess based on tool names alone.

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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