Prenica（プレニカ）

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

With no annotations, the description carries the burden; it discloses that the tool returns the body from beginning to end (no truncation) and frames it as a read-only detailed-reading operation. It does not discuss error cases or output formatting, but for a single-URL read tool this is reasonable disclosure.

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?

Two compact sentences: the first states the core behavior and scope, the second states the usage context. There is no filler or repetition of the title/schema.

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 one-parameter, no-output-schema read tool, the description is complete: it defines the input source via the schema, says what is returned, and states when to invoke it. No important selection or invocation information is missing.

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 100%, and the description itself adds no parameter detail beyond the schema's existing explanation that the URL may be a Japanese-language URL or path. Baseline 3 applies because the schema already carries the semantic weight.

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 states a specific action ('本文を...返します') on a specific resource (the body of a Prenica page) and adds the full-range scope '最初から最後まで'. It clearly differentiates from search_pages, which is for finding pages, by positioning get_page as the detailed-reading step.

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?

It explicitly says to use this tool when reading details of press releases found with search_pages, naming the prerequisite sibling and the exact use case. This gives the agent a concrete routing rule rather than leaving the choice to inference.

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

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

With no annotations, the description carries the full burden, and it does a good job: it discloses the output shape (titles and URLs), states the snapshot/staleness caveat, and explains how URL paths correspond to page categories. Pagination behavior and error conditions are not discussed, but the core read-only, data-freshness traits are clearly conveyed.

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 compact and front-loaded: the first sentence states what is returned, the second explains URL semantics, and the third adds an important freshness caveat. Every sentence contributes value, though the URL taxonomy detail could arguably be trimmed without losing core meaning.

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 simple list tool with no output schema, the description covers the return content and an important data-freshness limitation. It is less complete about pagination semantics and when to choose a sibling tool like search_pages, but the tool name and schema partially cover those 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%, and the description never mentions limit or offset. The parameter names are conventional and somewhat self-explanatory, but the description does not clarify how they affect the returned list, how pagination works, or what a reasonable limit choice would be.

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 clearly states that the tool returns a list of pages loaded in Prenica with titles and URLs. It also gives a concrete sense of the page taxonomy through URL examples, making the purpose specific and understandable. It doesn't explicitly name sibling tools, but list_pages is inherently distinct from get_page and search_pages.

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?

Usage is implied by the title 'see what pages exist' and the description's focus on returning the page list. However, there is no explicit guidance about when to use this tool versus search_pages or get_page, and no mention of when not to use it.

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

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.

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

With no annotations, the description carries the full burden. It discloses that the tool returns an overview and gives useful content details, but it does not explicitly state that the operation is read-only, has no side effects, or describe the output format. This is adequate but not rich.

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 concise and front-loaded: the first sentence states the core behavior, the second adds relevant service facts, and the third gives the intended use case. No unnecessary repetition or filler.

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 zero-parameter, informational tool, the description provides enough context for an agent to select and invoke it correctly. It explains what the overview contains and when to use it. It does not detail the return structure, but the absence of an output schema lowers that burden.

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 tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and it correctly focuses on what the tool returns rather than inputs.

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 clearly states the tool returns an overview of the Prenica service, using a specific verb ('返します') and a named resource. It is readily distinguishable from the sibling page-related tools because it addresses the service itself, not pages.

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 explicitly says to use this tool when first wanting to know what the service is. It does not name alternatives or exclusions, but the siblings are clearly page-focused, so the intended context is clear enough.

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