answer_why

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

With no annotations provided, the description carries the behavioral disclosure burden. It adds meaningful context about output semantics: relevance=low or no_path_reason means the den does not contain that path and should not be cited. It does not elaborate on other behavioral aspects, but the output schema partially fills that gap.

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?

Three compact sentences deliver the core purpose, example usage, a complementary-tool pointer, and an important result-interpretation caveat. Every sentence earns its place, and the main action is front-loaded.

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 moderate complexity (5 parameters, output schema present), the description covers the essential intent, example usage, and a key limitation. Slightly more explicit differentiation from other siblings would make it fully complete, but nothing critical is missing for invoking the tool correctly.

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 the baseline is 3. The description adds value beyond the schema by giving realistic example questions that clarify the expected form of the 'question' parameter, going beyond the schema's one-line 'Natural-language why question'.

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's function: explaining architectural 'why', principles, and pros/cons as causal paths. Concrete examples ('왜 콘크리트에 양생이 필요한가') anchor the purpose, and the mention of k_snippets for numeric/legal content helps distinguish it from at least one sibling.

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 says to use this tool for reason-seeking questions and advises calling k_snippets when numeric/legal content is needed. It also warns not to use low-relevance/no-path results as evidence. However, it does not explicitly contrast with other closely related siblings like evidence_for or path_between.

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