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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that results include matching excerpts and that responses should include the publishing company name and page URL, which are useful behavioral clues. It does not describe matching semantics, ranking, result limits, or whether the search is full-text, but for a read-only search tool this is a moderate rather than severe gap.

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?

The description is four sentences, with the core purpose front-loaded in the first sentence and examples in the second. The final sentence about distribution, pricing, and publication criteria is slightly tangential to the core search operation, but it adds useful routing context for common user questions. Overall it is dense and mostly free of redundancy.

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?

There is no output schema, so the description should hint at what the tool returns. It does so by saying results come with excerpts and by instructing the agent to include the company name and page URL in answers. While it does not specify a precise result structure, this is adequate for a straightforward search tool, especially with the included query examples.

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?

The schema documents only the query parameter, leaving limit undocumented, so schema coverage is 50%. The description compensates by explaining query semantics in detail: it gives examples, lists entity and industry types, and shows multi-word queries. The limit parameter is not discussed in prose, but its default, minimum, and maximum are already self-explanatory in the schema.

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?

The description opens with a specific action and resource: searching Prenica press releases for passages that match a query, with excerpts. It also gives concrete example queries and clearly distinguishes this search tool from sibling tools like get_page or list_pages by focusing on keyword-based content search rather than retrieval or listing.

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 provides strong usage context: what kinds of terms to search (company names, product names, event names, industries such as IT/AI, food, beauty, entertainment, finance) and example query formats like 「セミナー 10月」「コスメ」「イベント 開催」. It also mentions it can answer questions about distribution, pricing, and publication criteria. However, it never explicitly contrasts this tool with siblings or says when not to use it, so it falls just short of a 5.

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