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

Annotations already cover readOnly/openWorld/non-destructive, and the description adds genuinely new behavioral context: only metadata (title, link, date, section) is returned, with no article body or AI summary, and full text lives only at item.url. It doesn't discuss result ordering or rate limits, but the return-shape disclosure is the important part.

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?

Three sentences, front-loaded with the use case before the return-shape caveat. Every sentence is relevant, though the final sentence about 확인할 수 있습니다 is somewhat redundant with the preceding 'no body text' clause.

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 two-parameter read-only search tool, the description covers what it does, when to use it, what it returns, what it deliberately does not return, and where to get the full content. Nothing needed to invoke or interpret it correctly 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?

With 100% schema description coverage, both query and limit are already documented with examples in the schema. The description reinforces that queries are interpreted by context and meaning, which clarifies the retrieval model, but adds no syntax, formatting, or constraint detail beyond what the schema states.

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 gives a specific verb+resource ('뉴스를 찾는다') and scopes it to semantic/topic retrieval with example questions. It implicitly separates itself from the list_* siblings by emphasizing meaning-based search, but it never names those alternatives, so differentiation is inferred rather than stated.

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 triggering contexts via quoted user phrasings ('요즘 왜 이슈야', '배경이 뭐야'), which is strong positive guidance. It stops short of saying when NOT to use it or pointing to list_latest_news for plain recency browsing.

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