What this knowledge is based on, and how fresh it is

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

With no annotations provided, the description carries the full burden, and it does well by disclosing that the tool reports limitations ('何を持っていないか'), provenance ('何に基づき'), and freshness ('いつ一次情報と突き合わせ'). This makes the tool's scope and boundaries clear, though it does not describe output structure or side effects, which are minimal for an informational tool.

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 clause states the core content, and the second adds the pointer to authoritative wording. Nothing is wasted, and the bilingual format is acceptable given the language-aware parameter.

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, read-only meta-information tool with one optional parameter and no output schema, the description covers all essential context: what the tool tells you, how fresh the knowledge is, what it lacks, and where to find authoritative text. No critical information is missing for an agent to invoke it 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?

The single optional parameter `lang` is fully documented in the schema with an enum and a description ('出力言語 / Output language'), so schema coverage is 100%. The tool description adds no additional meaning about the parameter, so the baseline score 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 names the resource ('this knowledge base') and the precise dimensions it covers: basis, freshness/date of last check, gaps, and pointer to authoritative wording. This clearly distinguishes it from siblings like whats_new_for_me and check_official_source even though no alternatives are named.

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 states a clear context for use: when an agent needs to know what the knowledge base is founded on, how fresh it is, what it lacks, or where to get the original wording. It gives one explicit conditional use-case, '原文が必要なとき' (when the original text is needed), but does not mention when not to use it or name alternative tools.

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