digest_institution_news

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

Despite no annotations, the description reveals key behaviors: automatic classification into 8 themes, output includes counts, representative headlines, and a date timeline. It also implies a limitation (works best for institutions with high coverage via '보도량 많은 기관'). No destructive actions are mentioned, fitting a read-only 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 well-structured: first sentence states the main action, second details the output, and third provides a use case. It is front-loaded with the core purpose. While slightly verbose with the listed themes, every part earns its place. Could be slightly more concise but overall effective.

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 no output schema, the description explains return structure (theme counts, headlines, timeline) sufficiently. It also provides a use case. However, it lacks any explanation of the 5 input parameters, leaving a gap in completeness. The tool has moderate complexity, and the description misses parameter documentation.

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 input schema has 5 parameters with 0% description coverage—no parameter descriptions are provided in the schema or the main description. The description only indirectly references 'days' via an example ('한 달'), but it does not explain org_code, query, max_fetch, or per_theme. With this low coverage, the description fails to add meaning to 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 tool's function: it automatically classifies and aggregates institution news by theme, returning counts and timelines instead of a flat list. The verb 'digest' and resource 'institution news' are specific, and the description distinguishes it from a flat article list, implying differentiation from sibling tool get_institution_news.

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 contrasts with 'flat article list' and gives an example query ('summarize KAMCO's issues for the past month'), indicating when to use the tool for distribution insights. However, it does not explicitly name alternatives or when not to use it, though the contrast with a sibling tool provides implicit guidance.

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