SEO対策研究室

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

With no annotations, the description carries the burden and does disclose that the tool returns the page body from start to finish, implying a read-only retrieval. However, it does not mention the output format, error behavior, or potential size of the returned content, so transparency is adequate but incomplete.

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 two sentences with the core operation front-loaded, followed by concrete use cases and a parameter instruction. There is no filler or redundant detail beyond a minor restatement of the parameter, which is unlikely to confuse an agent.

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 one-parameter read tool without an output schema, the description is nearly complete: it explains what is returned, when to use it relative to search_pages, and how to specify the target page. It lacks explicit output-format or error-handling details, but those are not critical for basic invocation.

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 only parameter, url, has 100% schema description coverage explaining it accepts a URL or path and that Japanese is allowed. The description's final sentence restates this instruction without adding new semantics, so the baseline of 3 applies.

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 verb and resource: it returns the full body text of a page in 「SEO対策研究室」. It also distinguishes itself from siblings by explaining it is used to read details of articles found via search_pages and to verify survey percentages.

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 gives clear when-to-use guidance: reading article procedures/evidence found via search_pages and checking survey option percentages. It does not explicitly say when not to use it compared to list_pages or site_overview, but the use cases are concrete enough to guide an agent.

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?

No annotations are provided, so the description carries the full behavioral burden. It describes the return content (titles/URLs) and URL-path categories, but discloses no behavior such as pagination via limit/offset, default page size, ordering, or whether the full list is returned at once. For a listing tool this is a notable 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 main purpose is front-loaded in the first sentence. The subsequent URL-path breakdown (/blog/, /datasets/, /seo-case-studies/, etc.) is genuinely useful for the stated use case, but it is somewhat verbose for a list tool and could be trimmed. Moderate efficiency overall.

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?

The description explains the return format (titles and URLs) and the semantic meaning of URL categories, which supports the intended use. However, with no annotations and no output schema, pagination behavior, parameter semantics, and ordering are left unexplained, making it incomplete for an agent that needs to page through results correctly.

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 adds nothing about the two parameters (limit, offset). It doesn't explain pagination semantics, defaults, or the maximum of 200. The description's URL-path taxonomy is useful but unrelated to parameter meaning, leaving both params semantically unexplained.

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 and resource: 'returns a list (titles and URLs) of pages loaded into SEO対策研究室'. The return format is explicit. It implicitly differentiates from search_pages (listing vs searching) and get_page (single page), though it doesn't name them.

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?

Offers one usage context: 'use it when you want to introduce articles organized by field'. This gives a concrete trigger but never contrasts with the sibling tools (search_pages, get_page, site_overview) or states when NOT to use it. No exclusions are provided.

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 search is scoped to one site, returns matching passages with excerpts, and instructs that answers should include page URLs. It also lists additional content types that are searchable. Missing details like result ordering or match semantics prevent a 5.

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, front-loaded with the core function, and each sentence adds useful information: source, role, query style, additional searchable content, and output expectation. It is not overly verbose, though the topic list is somewhat long.

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?

Given no output schema and no annotations, the description supplies the source, query behavior, result type (excerpts), and URL expectation. It is mostly sufficient for an agent to select and call the tool, but it does not clarify return layout or how it relates to sibling tools beyond the implied usage trigger.

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 coverage is only 50%: query has an example but limit has no description. The description adds meaningful guidance for query semantics (short words, examples like 'サイテーション'), but it does nothing for the limit parameter beyond what the schema already shows. The compensation is only partial.

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 is specific about the action ('記事から...抜粋つきで探します'), the exact resource ('SEO対策研究室'), and the scope (site-internal search). It also enumerates topics, making the tool's purpose unmistakable. It clearly distinguishes itself from siblings like get_page, list_pages, and site_overview by focusing on content search with excerpts.

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 gives an explicit trigger: 'SEO...について質問されたら、まずこれを使ってください' and even advises the query style ('短い言葉で探します'). However, it does not name specific alternatives or state when not to use the tool, so it stops short of full exclusions.

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?

No annotations are provided, so the description carries the full burden of disclosure. It explains what content the tool returns (the site overview, the author, the topics covered) but does not describe the output format, length, or any other behavioral traits. For a zero-parameter read-style tool the burden is low, and the description 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 two sentences, front-loaded with the verb and resource, and efficiently covers what the tool returns, the site's subject matter, and when to use it. It is appropriately sized for a zero-parameter overview tool, though the middle content sentence is somewhat descriptive rather than purely functional.

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?

With no parameters, no output schema, and no annotation requirements, the description is essentially complete for an agent to call this tool correctly. It explains what is returned and when to invoke it. Nothing essential is missing for correct invocation.

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 description has no parameter burden to carry. The baseline of 4 applies for a parameterless tool; no parameter documentation is needed and none is missing.

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 verb (返します - returns) and the resource (the SEO対策研究室 site overview), and distinguishes this site-level tool from the page-level siblings (get_page, list_pages, search_pages). It describes the site's content and the author, giving a clear sense of what the tool provides. Sibling differentiation is implicit rather than explicit, preventing a 5.

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 gives an explicit use case: 'だれが書いているか、何が調べられるかを最初に知りたいときに使います' (use when first wanting to know who writes it and what can be researched). This is clear context. However, it does not mention alternatives or exclusions relative to the page-level sibling tools, so it stops 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.