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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description adds that results are candidates (plural, categorized) with ids, which tells the agent to expect a ranked/listed set rather than a single exact hit, but it does not cover result volume, ranking, or empty-result behavior.

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?

Two short sentences, front-loaded with what is returned and followed by the workflow cue. No filler and nothing repeated from 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?

One parameter, full schema coverage, an output schema, and safety annotations mean the description need not do heavy lifting. What is minimal but sufficient; only the plural-candidate behavior could use a word on result limits or ranking.

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 the schema already gives examples and a maxLength, so the baseline would be 3. The phrase "業種名の言葉から" adds that matching is driven by ordinary words rather than exact canonical names or ids, which is meaning 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?

Specific verb and resource: returns ListHub industry candidates (major category, middle category, keyword) plus id, given an industry word. The stated return shape and the mention of get_quote make it clearly distinguishable from the sibling tools 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?

"get_quote の前に使います" gives explicit workflow ordering relative to a named sibling, which is real selection guidance. It stops short of saying when not to use it or how it relates to search_areas.

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