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

readOnlyHint/openWorldHint already establish the safety profile, and the description adds genuinely new cost information: an unindexed full scan of ~1M entries and the advice to probe scale with count_only. It also flags that with_definition inflates responses. Result ordering and truncation behavior are left unstated.

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 front-loaded sentences: capability, concrete conditions/use cases, then the performance caveat. Dense but each sentence carries distinct information; no filler or repetition of the title.

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 8 parameters all schema-documented, annotations present, and no output schema, the description covers what an agent needs to call it correctly and avoid expensive broad queries. It stops short of describing the shape of returned entries (beyond the with_definition hint), which would help given the missing 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% and the pattern grammar is thoroughly documented there, so the baseline applies. The description's mention of anchor=suffix with '-아지'/'둥이' largely restates what the anchor and pattern schema fields already say, adding little new parameter semantics.

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 (검색) and resource (우리말샘 사전) plus the distinguishing mechanism — jaso/phoneme slot patterns that composed-form search cannot express. The concrete examples ('받침이 ㅎ인 용언', anchor=suffix endings like '-아지') make it unmistakable versus tokenize or analyze_syntax.

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 concrete when-to-use scenarios — rhyme finding, 초성 quizzes, 끝말잇기, irregular-conjugation candidate collection — and a when-caution rule (broad patterns → check scale with count_only first). It does not explicitly say when to prefer a sibling such as tokenize for plain string splitting, so the routing is implied rather than complete.

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