toys__search_toys
[NEW玩具情報站]搜尋亞洲扭蛋、盒玩、公仔、模型(中文或日文,例如 寶可夢、ちいかわ、鋼彈),回傳官方發售時期、價格、狀態(謠傳/官方公布/確定發售/已發售/再販/售完)、限量限定與來源。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| brand | No | ||
| limit | No | ||
| query | Yes | ||
| status | No | ||
| category | No |
[NEW玩具情報站]搜尋亞洲扭蛋、盒玩、公仔、模型(中文或日文,例如 寶可夢、ちいかわ、鋼彈),回傳官方發售時期、價格、狀態(謠傳/官方公布/確定發售/已發售/再販/售完)、限量限定與來源。
| Name | Required | Description | Default |
|---|---|---|---|
| brand | No | ||
| limit | No | ||
| query | Yes | ||
| status | No | ||
| category | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does disclose the returned fields (release timing, price, status, limited-edition flag, sources) and the status vocabulary, which is useful since there is no output schema. However, it says nothing about result limits, pagination, data freshness, or rate limits.
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?
A single dense sentence that front-loads the verb and searchable product types before listing return values. No wasted framing, though cramming purpose, examples, and return fields into one sentence makes it slightly hard to scan.
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 5-parameter search tool with no output schema and no annotations, the definition covers the search scope and return fields but omits parameter semantics for brand/category/limit and any pagination or result-cap behavior. Adequate but with clear gaps.
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 0% across 5 parameters, so the description has to compensate. It adds real value for `query` (Chinese or Japanese, with examples) and effectively labels the `status` enum in Chinese. But `brand`, `category`, and `limit` receive no explanation beyond their self-descriptive names and enums.
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 verb (搜尋/search) plus the resource types it covers (亞洲扭蛋、盒玩、公仔、模型) and even gives example queries. An agent can tell this is a catalog search for Asian toy/gashapon products, distinct from single-item siblings like get_toy or timeline siblings like release_calendar.
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?
The description implies the tool's use (keyword search over a toy info database, accepting Chinese or Japanese) but never states when to prefer it over the many sibling toy tools (get_toy, release_calendar, latest_toy_news, toy_stats). Usage is inferable but no explicit when/when-not guidance is offered.
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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