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

The description discloses behaviors not inferable from the annotations: the meaning of abstained=true and exact=false output flags, and instructs the agent not to fabricate similar terms and to verify exact-name matches. It also restates read-only and no external calls, complementing the annotations.

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 long but every sentence earns its place: purpose, sibling routing, parameter constraints, and special output semantics. The use of arrows, stars, and line breaks front-loads the most important information and makes the dense content scannable.

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 tool with 12 siblings and two output flags, the description covers the full decision space: when to use, what to expect, how to set parameters, and how to interpret abstained/exact. An output schema exists, so the lack of return-format detail is acceptable. Nothing necessary for correct invocation is missing.

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 each parameter already has a description, so baseline is 3. The description adds value by clarifying that term must be a single term not a question sentence, that limit is truncated to 1-5 with default 3, and that as_of uses YYYY-MM-DD format—practical constraints beyond 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 opens with a specific verb+resource: '건축·건설 용어 하나의 뜻을 돌려준다' and provides concrete example queries. It also states what the tool does not return ('기준값은 주지 않는다') and names sibling tools that handle other question types, making its purpose unmistakable.

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?

It explicitly instructs when to call this tool ('X가 무엇인가' 질문) and lists alternatives for other intents: k_snippets for numeric/rank texts, enumerate for type/enumerations, answer_why for reasons, compare for differences, and path_between for connections. This is an explicit when/when-not/alternatives mapping.

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