search_surveysキーワードでアンケート調査を検索します。言い換え（AI／人工知能、リモートワーク／在宅勤務など）でも見つかります。返ってくる survey_id を get_survey に渡すと集計結果を取得できます。
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 取得件数（既定10、最大30） | |
| query | Yes | 探したい話題。日本語の自然な言い回しでよい（例: 老後の不安、AI活用、在宅勤務のつらいところ） | |
| category_id | No | list_categories が返した category_id。指定するとその配下（全階層）の調査だけを検索する | |
| min_respondents | No | 回答者数の下限。引用に耐える標本だけが欲しい場合に指定する |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden and does disclose a useful behavioral trait: paraphrase matching (e.g., AI/artificial intelligence). It also indicates the output's role, but does not detail the return structure, pagination, or search scoping, leaving some transparency gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: the first states the core action, and the second adds valuable behavioral and workflow context. It is front-loaded, free of filler, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description adequately explains the key workflow: search returns survey_id which is passed to get_survey. It also covers paraphrase matching, but omits return format details such as whether a list is returned or how results are ordered, leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptive text for all four parameters. The description's mention of keyword search and natural phrasing closely mirrors the schema's query description, adding no new parameter-level meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'search surveys by keyword' with a specific verb and resource. It distinguishes itself from siblings by explicitly noting returned survey_id feeds into get_survey, and the paraphrase-matching detail adds further scope clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when you need to find surveys to obtain survey_id) and explicitly outlines the workflow to get_survey. It lacks explicit 'when not to use' guidance or naming of alternative tools, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: get_survey retrieves a specific survey's details, list_categories explores the category hierarchy, and search_surveys finds surveys by keyword. There is no overlap or ambiguity between them.
All tool names follow the same verb_noun snake_case pattern: get_survey, list_categories, search_surveys. The naming is consistent and predictable.
With 3 tools, the server is well-scoped for its purpose of accessing survey data. Each tool fulfills a necessary role in the discovery and retrieval workflow without unnecessary redundancy.
The tool set covers the full lifecycle from discovering surveys (via search or categories) to retrieving detailed results. As a read-only data source, there are no obvious gaps or missing operations.