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Google News data for agents

google_news_science

Paid ($0.005). Science — Google News. Live data as JSON. Pay with x402 or an Authorization: Bearer bby_live_... credits key.

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": {
      "languageCode": "<languageCode>"
    },
    "name": "google_news_science"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageCodeYesRequired.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly discloses a key behavioral trait: calling this tool costs $0.005 and requires payment via x402 or a Bearer bby_live_... credits key. It also states that data is live JSON. It does not cover rate limits, error behavior, or read-only status, but the most operationally important facts are present.

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 extremely compact, using short fragments to convey cost, category, data format, and payment method. The cost fact is front-loaded, and every phrase earns its place. There is no filler or repetition.

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

Completeness3/5

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

For a simple one-parameter category-fetch tool with no output schema, the description covers the essential cost and authentication details. However, it does not explain what languageCode should contain or what the returned JSON looks like beyond being 'live data as JSON.' An agent would need to infer language code formatting from other tools or conventions, so there is a noticeable but not severe gap.

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?

The only parameter, languageCode, has a schema description that only says 'Required.', which is minimal. Schema description coverage is 100%, so the baseline is 3, but the tool description itself adds no parameter information: it never mentions languageCode, valid formats, or example values. Thus it neither compensates for nor worsens the thin schema documentation.

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 identifies a specific resource: the Science category feed from Google News, and states its output as live JSON. The 'Science' label distinguishes it from sibling category feeds like google_news_business and google_news_health, though it lacks an explicit verb and does not contrast itself with google_news_latest or google_news_topic.

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?

The 'Science — Google News' label implicitly tells an agent when to use this tool: when it wants science-related Google News. However, there is no explicit when-to-use guidance, no mention of alternatives like google_news_search or google_news_topic, and no exclusions or prerequisites beyond payment.

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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