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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds genuine behavior beyond that: it discloses compound-surname handling, an ambiguity flagging mechanism with a worked example (선우진), and a distinct rule for Latin-script input. It stops short of describing the result structure or how the flag is surfaced, which matters since there is no output schema.

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 sentences, each carrying distinct information: core behavior first, then edge-case recognition, then ambiguity handling, then Latin-script fallback. The parenthetical examples earn their place by making the compound-surname and ambiguity rules concrete rather than abstract.

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 simple, single-parameter, read-only transformation, the description covers input domain, edge cases, and ambiguity handling. The one gap is the return shape: with no output schema, an agent cannot know whether results are objects with family/given fields plus a flag, or parallel arrays. That is a modest omission for a tool this simple.

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?

There is a single parameter with 100% schema description coverage ('Up to 1000 names'), so the schema already carries the meaning. The description adds only the implication that input is a batch of names and that Latin-script entries are accepted, without syntax or per-item detail. Baseline 3 is appropriate when the schema does the heavy lifting.

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 names a specific verb and resource ('Split Korean full names into family name and given name') and scopes the operation with concrete rules: compound surnames like 남궁/황보, ambiguity flagging, and a separate Latin-script rule. An agent can immediately tell this apart from siblings such as kr_address_split or kr_mask_pii without consulting any schema.

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?

Usage is implied rather than stated: the description makes clear it handles Korean personal names and even Latin-script names, which is a useful scope signal, but it gives no explicit when-to-use/when-not guidance or named alternatives. There is no statement about what to do with the flagged ambiguous results beyond the fact that they are flagged.

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