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AIsa SERP — Google

Live Google Dataset Search Advanced

post_dataforseo_serp_google_dataset_search_live
Destructive

Live Google Dataset Search provides real-time data on the top 20 Google Dataset search engine results. These results are specific to the indicated keyword. You can specify other parameters optionally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changed
    • changedInput schema / properties / body / items / properties / file_formats / description
      Previous value: -"Dataset file formats"New value: +"file formats of the dataset optional field possible values: other, archive, text, image, document, tabular"
    • changedInput schema / properties / body / items / properties / keyword / description
      Previous value: -"Keyword to search datasets for"New value: +"keyword required field you can specify up to 700 characters in the keyword field all %## will be decoded (plus character ‘+’ will be decoded to a space character) if you need to use the “%” character for your keyword, please specify it as “%25”; if you need to use the “+” character for your keyword, please specify it as “%2B”; learn more about rules and limitations of keyword and keywords fields in DataForSEO APIs in this Help Center article"
    • changedInput schema / properties / body / items / properties / language_code / description
      Previous value: -"Search engine language code"New value: +"search engine language code optional field if you don't specify language_name if you use this field, you don't need to specify language_name possible value: en"
    • changedInput schema / properties / body / items / properties / language_name / description
      Previous value: -"Full name of search engine language"New value: +"full name of search engine language optional field if you use this field, you don't need to specify language_code possible value: English"
    • changedInput schema / properties / body / items / properties / last_updated / description
      Previous value: -"Last updated filter"New value: +"last time the dataset was updated optional field possible values: 1m, 1y, 3y"
    • changedInput schema / properties / body / items / properties / os / description
      Previous value: -"Device operating system"New value: +"device operating system optional field choose from the following values: windows, macos default value: windows"
    • changedInput schema / properties / body / items / properties / usage_rights / description
      Previous value: -"Usage rights filter"New value: +"usage rights of the dataset optional field possible values: commercial, noncommercial"
  2. First observed

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already declare openWorldHint=true and the striking destructiveHint=true, which the description never addresses or explains; it only says the tool 'provides real-time data,' which is silent on the tension with a destructive hint. Nothing is said about cost, rate limits, or what the live request actually mutates.

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?

Two sentences, front-loaded with the resource and result cap, with no padding beyond a mildly redundant closing sentence about optional parameters. Efficient overall.

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?

An output schema exists so return values need no explanation, but for a live open-world POST whose annotations flag it destructive, the description is too thin: it omits the array-wrapped request shape, any of the available filter semantics, and any operational caveats an agent would need before invoking.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is reported at 0% for the top-level body parameter, and the description contributes only 'other parameters optionally.' It never mentions that the input is an array of request objects, nor any of the meaningful nested filters (file_formats, usage_rights, last_updated, language_code/name) that the schema itself does document.

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?

States a specific verb+resource: live Google Dataset Search results, capped at the top 20, scoped to the supplied keyword. It is distinguishable from most siblings, though it never differentiates itself from the adjacent post_dataforseo_serp_google_dataset_info_live, which an agent might reasonably confuse it with.

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?

There is no when-to-use or when-not-to-use guidance, no mention of alternatives like dataset_info_live, and no cost/prerequisite notes. The only guidance offered is the vague 'You can specify other parameters optionally,' which tells the agent nothing about selection.

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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