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Search Japanese onomatopoeia

jp_search_onomatopoeia
Read-onlyIdempotent

Find the right Japanese onomatopoeia by describing a scene or meaning in Japanese or English. Get matching words with meanings, examples, and nuance.

Instructions

場面や意味から日本語のオノマトペ(擬音語・擬態語)を検索する。日本語でも英語でも検索できる。

Search Japanese onomatopoeia by scene, meaning, or keyword. Queries may be in Japanese or English.

Args:

  • query (string): 探したい場面や意味。例: "雨が静かに降る", "snow falling silently", "tired"

  • category (string, optional): カテゴリで絞り込む。jp_list_onomatopoeia_categories で一覧を取得できる

  • limit (number): 返す件数の上限 1-20 (default: 5)

Returns: { "query": string, "count": number, "results": [ { "word", "romaji", "type", "categories", "meaning_ja", "meaning_en", "example_ja", "example_en", "nuance" } ], "message": string // 該当なしの場合の案内 }

Examples:

  • "雨が静かに降る様子は?" -> query="雨 静か 降る"

  • "How do I say the sound of heavy rain?" -> query="heavy rain"

  • Don't use when: 特定の語の意味だけを知りたい場合は jp_explain_onomatopoeia を使う

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo返す件数の上限
queryYes探したい場面・意味・キーワード(日本語または英語)
categoryNoカテゴリで絞り込む場合に指定する

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
queryYes
messageYes
resultsYes
Behavior4/5

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

Annotations already cover read-only/idempotent/non-destructive behavior. The description adds valuable behavioral context beyond that: query language flexibility, a defined return structure with a message field for empty results, and an example showing query normalization ('雨が静かに降る' -> '雨 静か 降る'). This is more than baseline but not exhaustive.

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?

The description is well-structured with sections for Args, Returns, Examples, and exclusions. It repeats the main purpose in Japanese and English, which is somewhat redundant but serves bilingual users and is not bloated. Every section earns its place.

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?

The tool has a clear search use case, an output schema that covers the return structure, annotations for safety, a sibling-tool cross-reference for edge cases, and concrete examples. The description is complete for an agent to select and invoke the tool 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 coverage is 100%, so the baseline is 3. The description adds meaningful examples for the query parameter, a cross-reference for obtaining valid category values via jp_list_onomatopoeia_categories, and reiterates the limit range. This goes beyond the schema's own descriptions.

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's purpose: 'Search Japanese onomatopoeia by scene, meaning, or keyword' and explicitly notes bilingual query support. It also differentiates from the sibling tool jp_explain_onomatopoeia via the 'Don't use when' note, making the scope unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when NOT to use the tool and points to the correct alternative: 'Don't use when: 特定の語の意味だけを知りたい場合は jp_explain_onomatopoeia を使う'. It also includes concrete examples of valid query phrasings, making usage clear.

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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