get_term_articles

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

With no annotations provided, the description carries the full burden. It discloses that results are grouped by matching term groups, homonyms are separated, no pagination is available, and results are truncated by maxArticles. It also gives an example (개인정보 → ~700 articles). However, it does not explicitly state that the operation is read-only or mention authentication/permission requirements, which would be helpful.

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 concise and front-loaded with the core purpose. Every sentence adds value: purpose, grouping logic, homonym handling, pagination behavior, next steps. No redundant or unclear phrases.

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 absence of an output schema, the description explains the return type (list of articles grouped by term) and mentions the body preview behavior (200 chars if includeBody true). It provides sufficient context for the agent to understand the output format. Could be improved by explicitly listing the response fields (e.g., lawId, article number), but overall it is complete enough.

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 100%, so baseline is 3. The description adds context beyond the schema by explaining the purpose of maxArticles (truncation) and providing an example query (개인정보). The example illustrates how the tool behaves with a real term, adding semantic value.

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 tracks articles using specific legal terms, returns a list grouped by term, and distinguishes from sibling tools like 'get_legal_term' (definitions) and 'get_law_text' (full law text). It uses specific verbs and resources: '법령용어가 사용된 조문 추적' and '매칭 용어 그룹별로 ... 조문 목록 반환'.

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 explicitly tells when to use the tool (when you have a legal term keyword and need all articles containing it), what not to expect (no pagination, truncation by maxArticles), and provides follow-up tool recommendations ('다음: get_law_text ...' and 'get_legal_term').

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