get_survey調査1件の設問・選択肢・得票数・割合を取得します。引用用の固定URL（citation.stable_url。固定できる時点が無い調査では null）とライセンスも一緒に返します。
| Name | Required | Description | Default |
|---|---|---|---|
| as_of | No | YYYY-MM 形式。その月末時点までの累計に固定する（引用向け）。省略すると最新の累計 | |
| survey_id | Yes | search_surveys が返した survey_id | |
| trusted_only | No | true にすると、メール確認済みアカウントの票だけに絞った集計を返す |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It indicates this is a read operation ('取得') and notes the nullable citation.stable_url condition. However, it does not disclose potential side effects, authentication requirements, or other behavioral nuances beyond the basic retrieval.
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 compact, consisting of two sentences. It front-loads the core purpose and adds essential return-value details without unnecessary fluff.
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?
The description adequately explains the tool's primary function and return fields, including edge cases (null citation URL). While no output schema exists, the description lists all key return components, making it sufficiently complete for a simple retrieval tool.
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 schema already covers 100% of parameters with descriptions, so the baseline is 3. The description adds no parameter-specific details, but given the high schema coverage, it doesn't need to compensate.
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 specifies the action ('取得します' - retrieves) and the exact resource (one survey's questions, choices, vote counts, percentages, plus citation URL and license). This differentiates it from sibling tools like search_surveys (which searches) and list_categories (which lists categories).
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?
No guidance is provided in the description about when to use this tool versus search_surveys or list_categories. The need for a survey_id is implied but not explicitly connected to search_surveys, and no exclusions or alternative workflows are mentioned.
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.