get_institution_news

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

No annotations are provided, so the description carries the full burden. It fully discloses key behavioral traits: OR search with aliases, post-fetch date filtering due to API limitations (Naver API lacks date parameter), sorting options, and pagination behavior for max_fetch. Limitations are transparently stated.

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 front-loaded with the main purpose in the first sentence, followed by parameter details in a structured, bullet-like format. Each sentence adds value, though some minor redundancy (e.g., repeating '네이버 API는 기간 파라미터가 없어' could be slightly more concise). Overall well-organized.

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 6 parameters, no annotations, and no output schema, the description provides sufficient context for behavior and limitations. It covers parameter interactions and API dependencies. However, it does not describe the structure of the returned data (e.g., fields like title, url, date), which would be helpful for an agent. Missing this detail reduces completeness slightly.

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 description must compensate. It explains 5 of 6 parameters (org_code, query, days, sort, max_fetch) in detail, describing their roles and special behaviors (e.g., alias substitution, date filter mechanism). The 'limit' parameter is not mentioned, but its purpose is standard. Overall, adds significant meaning beyond the schema.

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 action ('검색합니다' - searches) and the resource ('공공기관 관련 최근 뉴스' - recent news about public institutions). It distinguishes itself from sibling tools like 'digest_institution_news' by focusing on raw news retrieval, with specific details on how it handles org_code and query for institution-specific searches.

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 provides parameter-level guidance (e.g., when to use org_code vs query alone) but does not address when to choose this tool over alternatives like 'digest_institution_news' or 'cross_check_news_with_metrics'. No explicit 'when not to use' or comparison to siblings is given.

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