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

Annotations already cover safety (readOnly, idempotent, openWorld=false), and the description adds real value beyond them: the exact return shape (title/summary/date/url, body deferred to url), the data provenance (NHIS-published, yearly refresh), and an anti-hallucination rule for missing values.

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 purpose and return-shape statements are front-loaded and useful, but the middle section about NHIS evaluation values and yearly updates reads like boilerplate borrowed from a different data-lookup tool and does not obviously belong to an article search.

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?

No output schema exists, so the description correctly takes on the burden of describing the returned fields and the url-deferral behavior, which makes it largely callable. However, it omits the undocumented limit/category parameters and mixes in provenance text that poorly fits an article-search tool.

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 33% (just 'q'), and the description does not compensate: it never mentions the 'limit' cap of 10 or the 'blog'/'news' category filter. Only the keyword scope ('제목·요약에서 찾는 말') indirectly maps to q.

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?

Names a specific verb and resource ('안내 글·뉴스 찾기 / Search articles') and explicitly states what is returned (title, summary, publish date, url) versus what is deferred to the url. It is clearly distinguishable from get_institution/compare_institutions, though it never explicitly contrasts itself with the closest sibling search_institutions.

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?

There is no guidance on when to choose this tool over search_institutions or search_institutions-style lookups; the only usage-like instruction is about handling missing values ('point to the url or the contact page'), which is a fallback rule, not a selection rule.

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