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AIsa SERP — Other Engines

List of Bing Locations for SERP

get_dataforseo_serp_bing_locations
Read-onlyIdempotent

You will receive the list of locations by this API call. You can filter the list of locations by country when setting a task.

Usage-based billing; Default request estimate: $0.02 USD (not a fixed price). Account-specific pricing and final settlement may differ.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / x-fastmcp-wrap-result
      Added value: +true
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered. The description's only added behavioral content is the usage-based billing estimate ($0.02 default request), which is useful cost context, but it says nothing about pagination, list size, or coverage limits.

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 core message is front-loaded in the first sentence and the filtering hint follows immediately. The opening 'You will receive ... by this API call' is slightly padded and the injected pricing block is boilerplate, but nothing is misleading or bloated.

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?

With no parameters and an output schema present, the description does not need to document return values. It adequately covers what the call yields and how the result is used, leaving only minor gaps around list scope/size.

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 tool takes zero parameters, so per the baseline there is nothing for the description to disambiguate. It still notes that filtering happens downstream ('when setting a task') rather than via this call's arguments, which prevents an agent from hunting for a non-existent country parameter.

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

Purpose4/5

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

The description states a specific resource ('the list of locations') for the Bing SERP context, so the agent can tell it returns location data rather than organic results. However, it never distinguishes itself from the near-identical siblings get_dataforseo_serp_baidu_locations or get_dataforseo_serp_seznam_locations beyond the implicit Bing scope in the name/title.

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?

'You can filter the list of locations by country when setting a task' hints at the intended workflow (look up locations before creating a task), but it never states when to call this versus the languages sibling or the organic_fetch tools. Usage is implied rather than explicitly framed.

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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