Crawlora MCP

yahoo_news_related

Read-only

A page of articles Yahoo recommends alongside a given article -- the "you may also like" strip at the bottom of an article page -- with cursor-based pagination.

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": {
      "content_id": "<content_id>"
    },
    "name": "yahoo_news_related"
  }
}

Input Schema

Name	Required	Description
`count`	No	Number of related articles to return, default 10, clamped to 1..50
`cursor`	No	Pagination cursor from a previous response's next_cursor
`content_id`	Yes	Article id (the id field returned by home/category/article)

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 7, 2026

addedInput schema / properties / content_id / description

Added value: +"Article id (the id field returned by home/category/article)"

addedInput schema / properties / count / description

Added value: +"Number of related articles to return, default 10, clamped to 1..50"

addedInput schema / properties / cursor / description

Added value: +"Pagination cursor from a previous response's next_cursor"

First observedOct 5, 2026

TDQS

A3.7/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds 'cursor-based pagination', which is useful behavior context, but says nothing beyond that (ordering, freshness, why these articles).

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?

A single front-loaded sentence that earns its place; the analogy is slightly verbose but aids selection, and there is 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?

With an output schema and annotations covering safety, the description gives enough to call the tool correctly; only explicit usage routing to sibling endpoints is missing.

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 description coverage is 100%, so count, cursor and content_id are fully documented in the schema. The description reinforces pagination but adds no new parameter meaning, so baseline 3 applies.

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?

States a specific verb+resource (returns a page of Yahoo-recommended articles for a given article) and grounds it with a concrete analogy ('you may also like' strip), which cleanly separates it from yahoo_news_article and yahoo_news_home.

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?

Usage is implied: you call it with an article id to get recommendations. There is no explicit when-to-use/when-not guidance or named alternative (e.g. yahoo_news_suggest, yahoo_news_home), so an agent must infer the context.

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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