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BACH-AI-Tools

Google News13 MCP Server

entertainment

Retrieve entertainment news articles from Google News for a specified language region using the Google News API.

Instructions

This endpoint is used to get entertainment news from Google News.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lrYeslanguage region, ex: en-US
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'gets' news, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or details the response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, with every word earning its place. There's no wasted verbiage, making it highly concise and well-structured for quick understanding.

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?

Given the tool's low complexity (1 parameter, no nested objects) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks details on behavioral traits (e.g., response format, error handling) and doesn't guide usage relative to siblings. It meets the bare minimum but has clear gaps in context.

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 input schema has 100% description coverage, with the 'lr' parameter fully documented as 'language region, ex: en-US.' The description adds no additional parameter information beyond what the schema provides. According to the rules, when schema coverage is high (>80%), the baseline score is 3, as the schema does the heavy lifting and the description doesn't compensate with extra semantics.

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 clearly states the tool's purpose: 'get entertainment news from Google News.' It specifies both the verb ('get') and the resource ('entertainment news'), and distinguishes it from siblings like 'business' or 'sport' by focusing on entertainment content. However, it doesn't explicitly differentiate from 'latest' or 'search,' which might also retrieve news, so it's not a perfect 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'entertainment' over siblings like 'latest' (which might include entertainment news) or 'search' (which could filter for entertainment topics). There's no context on exclusions or prerequisites, leaving the agent to infer usage based on the name alone.

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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