会社名の一覧に法人番号をまとめて付ける（名寄せ）

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

Annotations already declare read-only, idempotent, non-destructive, so the description is free to add the operationally important details the annotations cannot express: asynchronous job completion within seconds, the poll-don't-resubmit rule, and quota consumption (batch-row quota, 50 rows/month on Free). It even explains the three confidence outcomes, which governs how the agent should act on results.

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?

Front-loaded with the purpose and immediately followed by the confidence vocabulary and the polling rule; every sentence carries information. It is a dense single paragraph that could be broken into bullets, but there is no filler to cut.

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 no output schema, the description still covers the result shape (per-row confidence levels and their meaning) and the retrieval flow. Combined with annotations and a fully documented schema, nothing an agent needs to call this correctly is 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 coverage is 100%, so baseline is 3, but the description adds real semantics beyond it: the 50-item cap, why prefecture is worth supplying, and critically that job_id is used with no companies to fetch an existing result — a mutual-exclusion rule the schema does not state.

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 and resource (match company names to corporate numbers in bulk, 名寄せ) and scopes the input source (customer/sales list, vendor master). It also distinguishes itself from bango_find_company by naming the single-company case, so an agent can pick the right tool without opening either 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?

Gives explicit operating rules: up to 50 names per call, per-row prefecture improves accuracy, use bango_find_company for a single company, and when the job is still running call again with job_id only and do not resubmit. Alternatives and the when-not condition are both named.

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