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ZENITH Code

Economic indicators catalog

get_economic_indicators
Read-only

List the available macroeconomic series (US and Japan: CPI, unemployment, payrolls, Fed funds, Treasury yields, GDP, USD/JPY, Japan CPI/unemployment/rates) with Japanese/English names, unit and frequency. Call this first to find a series id for get_economic_series. The data source is given once, in a note after the result. 配信可能な経済指標系列の一覧(ja/en メタ)。出典は結果の後ろの注記に 1 つ。 Date-times are ISO 8601 UTC (YYYY-MM-DDTHH:MM:SSZ; add 9 hours for Japan time). Date-only fields are YYYY-MM-DD. 時刻(日時)は ISO 8601 の UTC(YYYY-MM-DDTHH:MM:SSZ。日本時間は 9 時間を足す)。日付だけの項目は YYYY-MM-DD。

Input Schema

NameRequiredDescriptionDefault
countryNoFilter by country / 国で絞り込み

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

readOnlyHint is already supplied by annotations, so the safety profile is covered; the description adds genuinely new behavior — the source attribution appears once in a note after the result, and the result carries bilingual labels plus unit and frequency. The ISO 8601/UTC and +9h Japan-time conventions are disclosed but look like boilerplate that is not clearly relevant to a static catalog.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The lead sentence and the "call this first" instruction are well front-loaded, but the entire content is then duplicated in Japanese and followed by date-format boilerplate that a metadata-listing tool arguably does not need. Roughly half the text is redundant, diluting the actionable guidance.

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 no output schema, the description carries the burden of describing the return value, and it does — series names in two languages, unit, frequency, and a post-result source note. What is missing is any hint of result size or pagination, which matters for a catalog spanning two economies.

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

Parameters3/5

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

Schema coverage is 100% and the single enum parameter is already documented as "Filter by country / 国で絞り込み". The description implies the US/JP split via its enumeration, but adds no filter semantics (e.g. what happens when country is omitted and whether all series are returned) beyond what the schema provides, so the baseline 3 applies.

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 opens with a specific verb plus resource ("List the available macroeconomic series") and enumerates exactly what is covered — CPI, unemployment, payrolls, Fed funds, Treasury yields, GDP, USD/JPY, and the Japan equivalents — along with the returned metadata (ja/en name, unit, frequency). That is enough for an agent to distinguish it from get_economic_series, which fetches values rather than the catalog.

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?

"Call this first to find a series id for get_economic_series" gives an explicit ordering and names the tool it feeds, which is exactly the routing an agent needs. It stops short of a when-not condition (e.g. that this returns no actual data points), so it falls just short of a full 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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