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BACH-AI-Tools

News Api14 MCP Server

trending_topics

Find the most popular news articles for a specific topic, language, and country. Enter your parameters to get trending news tailored to your audience.

Instructions

This endpoint lets you find the most popular news article for a specific country, language, and topic (like sports or entertainment).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoExample value:
topicYesThe topic of interest, example: General, Politics, Sports, or a subtopic Soccer. Check out the Supported Topics endpoint to see a list of all the topics you can search for.
languageYesexample: en, fr, de, zh-Hant. Check out the Supported Languages endpoint to see a list of all the languages you can search for.
countryNoexample: us, in, fr, de, id . Check out the Supported Countries endpoint to see a list of all the countries you can search for.
limitNoThis parameter controls the maximum number of articles returned on a single page.0
pageNoThis parameter specifies the page number you want to access. For example, page=2 will return the second page of results.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions 'most popular' but does not define popularity criteria (e.g., recency, views). Pagination behavior is only hinted at via parameters; no mention of default limits, total results, or ordering. The description lacks important behavioral details beyond the schema.

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?

The description is a single sentence that is direct and front-loaded. It earns its place by stating the core functionality. However, it could be slightly more informative without being verbose, such as clarifying what 'most popular' means.

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?

Given no output schema and no annotations, the description is insufficient. It does not explain the return format, pagination mechanics, or how 'popular' is determined. For a tool with 6 parameters, the description should provide more context to help the agent use it effectively.

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?

Input schema coverage is 100% with descriptions for all 6 parameters. However, the main description adds no additional semantic value beyond restating the parameters in a general way. The schema already provides examples and references to other endpoints, so the description does not enhance understanding significantly.

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?

The description clearly states the tool finds the most popular news article based on country, language, and topic. The verb 'find' and resource 'most popular news article' are specific. It distinguishes from sibling tools like search_articles which are for general searching, not trending.

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 description implies usage for trending content but does not explicitly state when to use this tool over alternatives like search_articles or get_random_article. No guidance on exclusions or prerequisites, but the context of 'most popular' provides some implicit direction.

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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