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

Annotations already declare readOnlyHint and idempotentHint, so the description is not obliged to restate safety, and it doesn't. Instead it discloses genuinely non-obvious behavior: pre-match normalization (trim, lowercase, folding common Latin variants), the ranking tiers pinyin_exact / romanization_exact / phonetic_close, and the 百家姓-order fallback when nothing matches. It also states that max_candidates is a hard cap rather than a hint, which changes how an agent should interpret short result lists.

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 dense clauses front-load the matching semantics, then the ranking order, then the fallback, then the sibling routing — no sentence is redundant with another. The closing 仅处理姓氏 clause doubles as both a scope limit and a hand-off, so nothing is wasted.

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?

An output schema exists, so return values need no explanation, and the description instead covers exactly the parts structured fields cannot: normalization, ranking, fallback, cap semantics, and sibling routing. For a two-parameter read-only lookup this leaves nothing an agent needs 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 description coverage is 100%, so the baseline is 3 and the schema already documents both parameters. The description still adds meaning beyond it: source_surname must be Latin pinyin/English spelling and will be normalized before matching, and max_candidates is characterized as a hard upper bound rather than a soft preference. It does not add format examples beyond what the schema gives, so it stops short of a 5.

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 precise verb+resource: matching candidate surnames by pronunciation (按发音匹配候选姓氏), and immediately bounds the input domain to Latin pinyin/English spellings. It explicitly contrasts itself with naming_pick (character pool) and naming_check (full-name evaluation), so an agent can distinguish it from siblings without opening 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?

It states both when to use it (surname-only phonetic matching from a Latin source) and when not to, naming the exact alternatives for the other two jobs (取字池用 naming_pick，整名评估用 naming_check). The input precondition that the source surname must be Latin pinyin/English spelling is also spelled out, which is the main way an agent could misuse this tool.

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