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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: multi-word queries are AND-matched, results carry ids for fetch, and there are copyright/citation obligations on the output.

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?

Front-loaded with the core purpose and the id→fetch workflow; every sentence carries weight (search scope, AND semantics, copyright/citation). Slightly dense but no filler.

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?

With no output schema, the description compensates by telling the agent that results contain ids usable with fetch, and adds the citation requirement. It stops short of describing result shape (fields, ranking) or pagination, but is sufficient for correct invocation.

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 the baseline is 3. The description adds one semantic not present in the schema — that multiple whitespace-separated terms are combined with AND — which directly affects how the query parameter behaves.

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?

States a specific verb (키워드 검색) and enumerates the corpus it searches (기준서 문단·질의회신·감리지적사례·실무해설). It also explicitly distinguishes itself from the sibling fetch by describing the two-step id→fetch workflow.

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?

Gives clear routing guidance: search here by keyword, then pass the returned id to fetch for full text. It does not name when to prefer siblings like get_paragraphs or get_qna over a keyword search, so it stops short of a full 5.

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