get_news

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

The description discloses data quality nuances beyond annotations: two sources with different timestamp accuracy, approximate times for name search, potential mixing of same-name articles, and late tagging for today's articles. It also notes that company press releases are not disclosures. This adds substantial behavioral context that annotations (readOnlyHint, openWorldHint) do not cover.

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 organized with clear sections: purpose, usage, source distinctions, and args. It uses bullets for the source details, making it scannable. Every sentence adds value—no filler. It is appropriately sized for the complexity of the tool.

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 the tool's complexity (two sources, timing caveats, three parameters with no schema descriptions) and the presence of an output schema, the description is complete. It covers what the tool does, when to use it, parameter semantics, and behavioral quirks, leaving nothing an agent needs to call 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?

Schema coverage is 0%, so the description fully compensates. The Args section defines each parameter: code (6-digit example), limit (default 10, max 30), and today_only (Korean date filter). This is essential and clearly stated, giving the agent everything needed to fill the parameters correctly.

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 clear statement: '종목뉴스 — 한국 주식 종목의 최근 기사' (stock news — recent articles for Korean stock), and explicitly names the two sources (Naver stock news and name search). It also distinguishes itself from get_move_context and get_disclosure, making the purpose unambiguous and differentiated from siblings.

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 provides explicit usage triggers ('무슨 뉴스 있어', '기사 찾아줘', '재료가 뭐야') and an explicit when-not-to-use ('오늘 왜 오르나' → get_move_context). It also clarifies that get_disclosure returning zero does not imply no articles, which is a valuable routing rule.

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