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Web search

search
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Search the web through Google and return ranked organic results (title, link, snippet) as JSON. Fast mode: no Knowledge Graph, ads or AI modules; use google_search for the full results page. Free without an API key (shares the google_search allowance).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesWhat to search for
glNoTwo-letter country for localization, e.g. "us"
hlNoLanguage code such as "en" or "en-GB"; default en
numNoRequested result count, 1-10; Google may return fewer
startNoResult offset for pagination
locationNoNamed search origin such as "Austin, Texas"; conflicts with uule and lat/lon
result_groupsNoReturn only these top-level result groups, e.g. ["organic_results", "knowledge_graph"]; omit for the complete response. search_metadata is always kept

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / num / description
      Previous value: -"Requested result count, 1-100; Google may return fewer"New value: +"Requested result count, 1-10; Google may return fewer"
    • changedInput schema / properties / num / maximum
      Previous value: -100New value: +10
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Adds behavioral context beyond annotations: fast mode, no Knowledge Graph/ads/AI modules, and sharing the google_search allowance. Doesn't contradict annotations (readOnlyHint, openWorldHint).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with the main purpose front-loaded, followed by the mode distinction and cost note. No filler.

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?

No output schema, but the description specifies the return format (title, link, snippet) as JSON. Covers the core use case, differentiation, and cost. Lacks explicit pagination details, but schema covers start/num.

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 covers all 7 parameters with descriptions (100% coverage). The description adds minimal extra param meaning, mostly reinforcing the fast-mode focus and result_groups behavior.

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

Purpose5/5

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

Clearly states it searches the web via Google and returns ranked organic results as JSON. Distinguishes itself from google_search by noting fast mode and pointing to the sibling for the full page.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to use google_search for the full results page, and implies this tool is for fast organic results. Doesn't mention other search siblings, but the primary alternative is addressed.

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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