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marleyhereicome-cpu

Merchgraph (Kingdom Hearts)

Resolve listing

resolve_listing

Converts Japanese secondhand listing titles and descriptions into canonical SKU candidates, condition terms, counterfeit flags, and MSRP-based price guidance.

Instructions

日本語の中古出品タイトル・説明文から、正規SKU候補・状態語・海賊版注意フラグ・定価比の目安を返す。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
srcNo計測用の流入元タグ(任意)。Web版チェッカーのURLパラメータ?src=から渡される。src自体と日時のみ利用ログに残す
urlNo出品URL(任意・サーバー側では保存しない)
titleYes出品タイトル(必須)
platformNo出品プラットフォーム(任意)
price_jpyNo出品価格(円、任意)
descriptionNo説明文の抜粋(任意)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the returned output categories, which is useful, but it does not state whether the tool is read-only, whether it writes or logs data, what happens with `url` or `src`, or whether there are rate limits or error behaviors.

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 a single tightly packed sentence that front-loads the input source and enumerates the outputs. There is no filler, and every element contributes to understanding what the tool returns.

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

Completeness2/5

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

With six parameters, no annotations, and no output schema, the description should do more to explain return-value format, usage context, and behavioral constraints. It lists output categories but does not describe their structure or reliability, and it omits when to choose this tool over siblings.

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%, so the schema itself documents all six parameters, including `src`, `url`, `platform`, `price_jpy`, and `description`. The description adds only broad meaning by implying title and description are used; it does not clarify how `platform` or `price_jpy` influence resolution, so baseline 3 is appropriate.

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 a specific transformation: from Japanese used-listing title/description it returns candidate official SKU, condition terms, counterfeit warning, and list-price ratio. This is more than a tautology and names concrete outputs, but it does not distinguish the tool from the sibling `resolve_listings_batch` or explain when single resolution is preferred over batch.

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 gives no explicit when-to-use guidance, no exclusions, and no alternatives. It also does not state whether this is for single listings only, when to use it instead of `resolve_listings_batch` or `explain_product`, or what prerequisites exist.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.