Crawlora MCP

yahoo_search_suggest

Read-only

Fetch Yahoo web-search autocomplete suggestions for a partial query, including optional knowledge-panel entity details. Use yahoo_news_suggest for news-specific completions, or yahoo_search once the query is ready and you need result links.

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": {
      "q": "<q>"
    },
    "name": "yahoo_search_suggest"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes	Partial search query to autocomplete
`count`	No	Number of suggestions to return, default 10, clamped to 1..20

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.

Changed2 schema fields changedOct 7, 2026
- addedInput schema / properties / count / description
```
Added value: +"Number of suggestions to return, default 10, clamped to 1..20"
```
- addedInput schema / properties / q / description
```
Added value: +"Partial search query to autocomplete"
```
First observedOct 7, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so safety profile is covered. The description adds valuable behavioral context beyond that: results include optional knowledge-panel entity details, which tells the agent the payload may contain richer entity data, not just strings. No rate limits or failure modes mentioned, hence not a 5.

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?

Two sentences, zero filler. The capability statement comes first and the routing guidance second, which is the correct front-loading.

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

Completeness5/5

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

An output schema exists, so return values need not be described. For a simple 2-parameter suggestion tool with annotations covering the safety profile, nothing an agent needs in order to call it correctly 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 q and count are already documented in the schema (count even has its default and 1..20 clamp). The description adds no format or syntax detail beyond 'partial query', so the 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?

Names a specific verb+resource ('Fetch Yahoo web-search autocomplete suggestions') plus scope ('for a partial query'). It explicitly separates itself from yahoo_news_suggest and yahoo_search, so an agent can route without opening a schema.

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?

States the selecting condition for two distinct alternatives: yahoo_news_suggest for news-specific completions, and yahoo_search once the query is ready and result links are needed. Explicit when-to-use and when-not-to-use guidance.

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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