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cygkichi
by cygkichi

get_e_stat_data_catalog

Search and retrieve statistical data catalogs from Japan's e-Stat API by keyword and survey year, with pagination control.

Instructions

Retrieves the data catalog from the E-Stat API.
機能名:データカタログ情報取得
政府統計の総合窓口(e-Stat)で提供している統計表ファイルおよび統計データベースの情報を取得できます。
統計表情報取得機能同様に、リクエストパラメータの指定により条件を絞った情報の取得も可能です。


Args:
    search_word (str): Search keyword for statistics tables.
        Use "AND", "OR", or "NOT" to specify multiple words for search.
        Examples:
            - "東京 AND 人口"
            - "東京 OR 大阪"
    surveyYears (str): The survey years for the statistics tables.
        Must be in one of the following formats:
            - yyyy: Unified year.
            - yyyymm: Unified month.
            - yyyymm-yyyymm: Unified month range.
        Example: "2023" or "202301-202312" or "202301"
    startPosition (int, optional): Start position for the search results.
        Defaults to 1. For example:
            - To get the first 100 results, set startPosition to 1.
            - To get the next 100 results, set startPosition to 101.
    limit (int, optional): Maximum number of results to retrieve. Defaults to 100.
Example:
    search_word = "東京 AND 人口"
    surveyYears = "2023"
    startPosition = 1
    limit = 100

Returns:
    str: The response text from the E-Stat API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
search_wordYes
surveyYearsYes
startPositionNo
Behavior2/5

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

With no annotations provided, the description carries the full burden. It discloses that it returns the API response text and explains parameter behavior, but it does not disclose the response structure, potential errors, rate limits, or whether it is a read-only operation. This is a significant gap for a tool with no annotation coverage.

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?

The description is structured with headings (Args, Example, Returns) and is mostly concise. However, it includes redundant Japanese text that repeats the English purpose, slightly increasing length without adding new information.

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

Completeness3/5

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

The description explains the parameters well and includes pagination behavior, but it provides minimal return value details ('response text from the E-Stat API') without describing the format or content of the catalog. It also omits any constraints or error handling. For a moderate-complexity tool with no output schema, this is only partially complete.

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

Parameters5/5

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

The input schema has no descriptions (0% coverage), and the description fully compensates by explaining each parameter: search_word with AND/OR/NOT examples, surveyYears with format constraints, startPosition with pagination examples, and limit with default value. It also provides a combined usage example, adding substantial meaning beyond the schema.

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?

The description states it 'Retrieves the data catalog from the E-Stat API' with a specific verb and resource. It also explains it can retrieve information about statistical table files and databases, which is clear. However, it does not explicitly differentiate from sibling tools like search_e_stat_tables, so it misses full differentiation.

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

Usage Guidelines2/5

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

The description says 'Similar to the statistical table information acquisition function, it is also possible to obtain information narrowed down by request parameters,' but it does not state when to use this tool versus alternatives. There is no explicit guidance on when to choose this catalog tool over sibling tools.

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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