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localgov-jp

@localgov-jp/mcp-server

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by localgov-jp

get_auction_detail

Fetch a single Japanese auction property's structured data by case ID, including court, property type, base price, bid floor, deposit, bid period, opening date, address, and photos.

Instructions

一件の競売物件の構造化データを取得. Fetch one auction by case_id (e.g. "bit_00000078922"). Returns case_number, court, property_type, sale_base_price_jpy, bid_floor_jpy (= base × 80%), deposit_jpy, bid_period, opening_date, address, photos, source_url (BIT), and _canonical (cite this). Free. Brand-isolated from the subsidies module.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
case_idYesAuction case id, e.g. "bit_00000078922"
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool is free, returns a specific set of fields, includes a computed field (bid_floor_jpy = base × 80%), and provides _canonical for citation. It does not cover error behavior or rate limits, but gives solid behavioral context for a simple fetch operation.

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

Conciseness5/5

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

The description is compact and information-dense, with a list of return fields and important notes (free, brand isolation). The bilingual content is slight redundancy, but every sentence and clause carries value; there is no filler.

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

Completeness5/5

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

Given a single parameter and no output schema, the description fully explains what will be returned, including field names, a computed field, a citation instruction, and the tool's scope. It is sufficient for an agent to invoke the tool and interpret the result, with no major missing details.

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 description coverage is 100% (the schema already describes case_id with an example). The description adds the same example and clarifies the usage context, but does not add meaningful new semantics beyond what the schema provides, so the baseline of 3 is appropriate.

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 the tool fetches one auction by case_id, with a concrete example ('bit_00000078922') and a list of returned fields. It distinguishes itself from siblings like search_auctions and get_subsidy_detail by specifying 'one auction' and 'Brand-isolated from the subsidies module'.

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?

It implies usage for retrieving details of a single known auction by case_id, and notes it is free and independent of the subsidies module. However, it does not explicitly mention that search_auctions should be used to find case_ids or state when not to use this tool, leaving a small gap.

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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