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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds one genuine behavioral fact beyond that: an empty query returns the entire list. It says nothing about result shape or whether answers or only questions are returned, so the addition is modest.

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?

Two compact sentences: scope and topics first, then the empty-query behavior. The topic list is informative rather than filler, though it is the bulkiest part of an otherwise tight definition.

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?

For a one-optional-parameter retrieval tool with no output schema, the description covers the knowledge domain and the no-query case adequately. The main remaining gap is what a hit looks like (question only, or question plus answer), which an agent may want to know before calling.

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% and the single optional 'query' parameter is already documented as '질문 키워드 (선택)'. The description adds only the empty-query fallback semantics, with no keyword matching rules or language/format expectations, so it sits at the baseline for a fully documented 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?

States a specific verb (검색합니다) and resource (자주 묻는 질문), and enumerates the covered topics (이력서 받는 법, 가격, 동글, 실측 SOH, 개인정보, 중고 전기차 배터리), which tells an agent this is the service/FAQ knowledge base rather than the data tools. It does not explicitly contrast itself with the generic 'search' sibling, so it is clear but not fully differentiated.

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 only guidance is 'query 를 비우면 전체 목록', which tells the agent how to do a full listing rather than a keyword lookup. There is no statement of when to prefer this over carvoltlab_stats, carvoltlab_report_items, or the generic 'search' tool, so usage context is implied by topic alone.

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