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「コエカツ」(無料のアンケートサイト)に掲載されたアンケートと集計結果から、言葉に当てはまる箇所を抜粋つきで探します。SEO・Web マーケティング、AI、美容、健康、仕事、暮らし、旅行、グルメ、子育てなどについて、「どれを選ぶ人が多いか」「人はどう感じているか」を知りたいときに、まずこれを使ってください。「SEO 外注」「AI スクール」のように話題の言葉で探します。答えるときは、回答数と調べた時期を添え、コエカツ調べであることを示してください。

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": {
      "query": "<query>"
    },
    "name": "search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes探したい言葉(例: 料金 支払い方法)

Output Schema

NameRequiredDescriptionDefault
resultsYes
candidatesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / candidates
      Added value: +{
      +  "items": {
      +    "properties": {
      +      "id": {
      +        "type": "string"
      +      },
      +      "title": {
      +        "type": "string"
      +      },
      +      "url": {
      +        "type": "string"
      +      }
      +    },
      +    "required": [
      +      "id",
      +      "title",
      +      "url"
      +    ],
      +    "type": "object"
      +  },
      +  "type": "array"
      +}
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare read-only, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real behavioral context beyond that: results are excerpt-based, and the agent must report 回答数 and 調査時期 and attribute the data to コエカツ調べ.

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?

Front-loads what the tool does, then when to use it, then the response-attribution rule; each sentence carries a distinct instruction. It is somewhat dense but not padded.

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 present, return format need not be described, and the description still supplies the attribution requirement and query style. The only gap is that the boundary with the sibling search_pages is left implicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with a single documented query parameter, so the baseline is 3. The description goes further by showing the intended query style — topical keywords such as 「SEO 外注」「AI スクール」 rather than full sentences — which meaningfully guides how to fill the parameter.

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?

States a concrete verb (探す) and resource (コエカツ掲載のアンケートと集計結果), plus the distinctive output trait of returning 抜粋つき matches. It does not explicitly distinguish itself from the sibling search_pages, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear when-to-use trigger (「どれを選ぶ人が多いか」「人はどう感じているか」を知りたいとき) and instructs to use it first, with topic examples. It never names an alternative tool or a when-not condition, so it stops short of 5.

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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