Market capitalization
get_market_capitalizationLatest market capitalization (JPY) of a listed company. 直近の時価総額(円)。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | 4-digit Japanese ticker code / 4桁の証券コード (e.g. "7203" = Toyota) |
get_market_capitalizationLatest market capitalization (JPY) of a listed company. 直近の時価総額(円)。
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | 4-digit Japanese ticker code / 4桁の証券コード (e.g. "7203" = Toyota) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description contributes the currency (JPY) and the point-in-time nature of the value, which are genuinely useful, but says nothing about data freshness/lag, whether the figure is a raw or free-float-adjusted cap, or how a missing symbol is handled.
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?
One tightly-scoped sentence with the key attributes (latest, JPY, listed company) front-loaded — nothing is padded. The Japanese restatement duplicates the same content verbatim, which costs a little space but is reasonable for a bilingual audience.
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?
For a one-parameter read-only lookup with no output schema, the essentials (unit and recency) are present. It still leaves the agent guessing about the relationship to the many adjacent financial-metric tools, which is the main completeness gap for a catalog this dense.
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?
Schema description coverage is 100%: the single 'symbol' parameter already documents itself as a 4-digit Japanese ticker with a Toyota example. The description adds no further meaning about the identifier beyond what the schema states, so the baseline 3 applies.
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?
States a specific resource (market capitalization) with a clear scope qualifier ('Latest') and unit (JPY), so an agent knows exactly what comes back. It does not, however, distinguish itself from near-siblings such as get_market_cap_history, get_key_metrics_latest, or get_quote.
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?
There is no explicit when-to-use or when-not-to-use guidance. The word 'Latest' hints that this is a point-in-time snapshot rather than a time series, implicitly routing agents away from get_market_cap_history, but that inference is left entirely to the reader with no named alternative.
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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