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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are largely covered structurally. The description adds that the search spans multiple legal source types (statutes, precedents, interpretations, tribunal decisions), which is genuinely useful behavioral context. It says nothing about result limits, ranking, or response shape, so with annotations carrying the safety profile a 3 is appropriate.

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 purpose is front-loaded and the examples are concrete, but the content is stated twice in Korean and English with the 'plain-language questions are fine' point repeated within the English sentence itself. Roughly half the text is redundant translation rather than new information.

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 should ideally hint at what comes back (article citations, case numbers, snippets) and how the limit parameter shapes results. It enumerates the source domains but says nothing about return format or result presentation, leaving a modest gap for a search tool with no output schema.

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 description coverage is 100%, so both parameters are already documented (limit 1~15 default 8, query as Korean question or keyword). The description's contribution is confirming that natural-language questions are valid input, which the schema already implies with '질문이나 낱말'. This is marginal added value over the schema, matching the baseline 3.

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 (찾는다/search) and enumerates the resources covered: Korean statutes, court precedents, MOLEG interpretations, and Constitutional Court/administrative appeal decisions. This scope is distinguishable from ID-based siblings like get_law and get_article, though those siblings are never named. The bilingual restatement adds nothing new to the purpose.

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 note that plain-language questions work, with examples like '회사에서 갑자기 잘렸어요' and '헬스장 환불', gives useful implied context for how to phrase a query. However, it never says when to use this tool versus get_law, get_article, or verify_citations, nor any exclusion conditions. Usage is left to inference.

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