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Browse onomatopoeia by category

jp_browse_onomatopoeia
Read-onlyIdempotent

Browse Japanese onomatopoeia by category or linguistic type. Filter by texture, emotion, taste, or gitaigo to explore paginated entries.

Instructions

カテゴリや分類(擬音語・擬態語など)で絞り込んで一覧を取得する。

Browse onomatopoeia filtered by category and/or linguistic type, with pagination.

Args:

  • category (string, optional): カテゴリID。jp_list_onomatopoeia_categories で確認できる

  • type (string, optional): 'giongo'(擬音語) | 'giseigo'(擬声語) | 'gitaigo'(擬態語) | 'gijougo'(擬情語)

  • limit (number): 返す件数 1-50 (default: 20)

  • offset (number): 読み飛ばす件数 (default: 0)

Returns: { "total": number, "count": number, "offset": number, "has_more": boolean, "results": [ { ...entry } ], "message": string }

Examples:

  • 「食感のオノマトペを一覧で見せて」 -> category="taste"

  • 「擬情語だけ見たい」 -> type="gijougo"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo言語学的な分類で絞り込む
limitNo返す件数
offsetNo読み飛ばす件数
categoryNoカテゴリIDで絞り込む

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
totalYes
offsetYes
messageYes
resultsYes
has_moreYes
Behavior4/5

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

Annotations already declare read-only and non-destructive. The description adds meaningful context: pagination behavior (limit/offset/has_more), the return structure, and guidance to consult jp_list_onomatopoeia_categories for valid category IDs.

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?

Well-structured with summary, args, returns, and examples. Bilingual repetition adds some length but each section serves a distinct purpose, keeping it focused and skimmable.

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?

Covers filtering, pagination, return fields, parameter constraints, and category lookup. With an explicit output schema snippet and examples, no critical gaps remain for an agent to invoke correctly.

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

Parameters4/5

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

Schema has 100% coverage with enums and descriptions. The description adds value by explaining how to obtain category IDs via a sibling tool and providing concrete natural-language to parameter examples, which goes beyond the 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?

Description uses specific verbs ('Browse', '取得する') and clearly defines scope: filtering by category and/or linguistic type with pagination. It distinguishes from sibling tools like jp_search_onomatopoeia by focusing on list browsing rather than keyword search.

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?

Provides examples mapping natural language requests to parameters ('擬情語だけ見たい' -> type='gijougo'), establishing clear usage context. Does not explicitly exclude alternatives or mention when not to use, but the browsing vs. searching distinction is implicit.

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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