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kuraneko1
by kuraneko1

google_search

Executes a Google query in a JavaScript-rendered Chrome browser and returns structured search results. Pair with URL fetching to extract full text from promising pages.

Instructions

Search Google in a JavaScript-rendering Chrome browser running non-headless inside Xvfb. Returns structured search results. Workflow: first google_search, then fetch_url on interesting result URLs for full text. Pace calls: bursts of 15+ searches per minute raise a pace_warning and risk a Google CAPTCHA.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNoGoogle region, e.g. jp or usjp
hlNoGoogle UI language, e.g. ja or enja
limitNoMaximum results (1-20)
queryYesSearch query

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden of transparency. It discloses the non-headless browser environment, rate-limiting risk, and CAPTCHA possibility, though it does not mention side effects or authentication requirements.

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?

The description is compact and information-dense, covering purpose, workflow, and usage caution in three sentences. No redundant or filler content is present.

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?

Given no output schema, the description provides enough context for an agent to understand the tool's role and sequencing with fetch_url. It could be slightly more specific about the result structure, but overall it is sufficiently complete for the tool's complexity.

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 descriptions cover all four parameters (query, gl, hl, limit) with types, defaults, and constraints. The tool description adds no extra parameter-level detail beyond the schema, so a baseline score is appropriate.

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?

Description clearly states the tool searches Google and returns structured results, distinguishing it from fetch_url and health_check. It specifies the execution context (JavaScript-rendering Chrome under Xvfb), making the purpose unambiguous.

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

Usage Guidelines5/5

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

Explicitly describes the intended workflow: use google_search first, then fetch_url for full text. It also provides pacing guidance by warning about pace_warning and CAPTCHA risk with bursts of 15+ searches per minute.

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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