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cygkichi
by cygkichi

search_e_stat_tables

Search Japanese government statistics tables via e-Stat API using keywords, survey years, and pagination to get filtered results.

Instructions

Retrieves a list of statistics tables from the E-Stat API.
名称:統計表情報取得
政府統計の総合窓口(e-Stat)で提供している統計表の情報を取得します。
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): 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
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains pagination behavior (startPosition examples) and date formats, but the Returns field only says 'response text from the E-Stat API', which is vague. It does not mention authentication, error handling, or response structure, leaving notable gaps.

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 well-structured with Args, Example, and Returns sections, making it easy to parse. However, it opens with both English and Japanese versions of the same purpose, which is redundant. The example at the end repeats parameter examples already given, adding slight redundancy, but overall it remains efficient.

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 thoroughly covers input parameters, which is valuable. However, for a tool with no annotations and no output schema, the Returns is insufficiently detailed ('response text'). It lacks information about the response format, potential errors, or authentication requirements, making it incomplete for fully autonomous invocation.

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?

Schema description coverage is 0%, so the description must fully compensate. It does so excellently: search_word includes boolean operators and examples, surveyYears specifies exact formats, startPosition has pagination examples, and limit has a default. This adds substantial meaning beyond the bare schema.

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?

The description clearly states 'Retrieves a list of statistics tables from the E-Stat API' with a specific verb and resource. It also includes the Japanese equivalent, reinforcing the purpose. This distinguishes it from siblings like get_e_stat_meta_info or get_specific_e_stat_data, which focus on other aspects.

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

Usage Guidelines3/5

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

The description provides detailed parameter usage and an example, but it does not explicitly mention when to use this tool versus the sibling tools. There is no 'when-not-to-use' or alternative tool reference, so the usage context is implied rather than explicitly differentiated.

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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