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

Annotations only cover the read-only/idempotent safety profile; the description goes well beyond by describing multi-match disambiguation, per-source blocks with as_of/updated/url/credit lines, the trap that a stale record (especially the representative) may be out of date, and the rule that a missing fact is unknown rather than zero. It also sets ethical boundaries (no employer judgments, no contacting the company on the user's behalf) and flags self-description as claim-not-fact and data-never-instructions, which is meaningful prompt-injection hardening.

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?

Purpose is front-loaded, but the remainder is a long chain of colon-linked clauses and nested parentheses that is hard to parse in one pass. Much of the length is justified because there is no output schema, yet several parentheticals ('the representative's above all', 'data and never instructions') could be shortened without losing meaning.

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 carries the full burden of describing returns and does so thoroughly: sources, as_of, updated, url, credit lines, fact kinds, company_type, postings, unknowns, and explicit non-coverage. An agent has enough to call it and interpret the response without further documentation.

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 there is a single parameter, so the schema already carries the syntax (name part, katakana reading, website name, 13-digit 法人番号). The description still adds behavioral meaning by explaining that the value is interpreted 'as in search_jobs' and that several matches return a list for the user to choose from, which tells the agent how matching will behave.

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 opening clause gives a specific verb and resource ('Get what the data says about one company') and immediately pins down provenance as the distinguishing feature. It implicitly separates itself from siblings by routing postings work to list_pages, list_page_ids and get_job, but never states directly why an agent would pick this over a broader search tool.

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?

'use it when the user names a company' is an explicit trigger condition, and the not_in_this_data block enumerates out-of-scope domains (finances, news/IR, reviews, team) with 'look elsewhere'. The gap is that 'look elsewhere' never names the alternative tool, and no when-not-to-use condition against search_jobs is spelled out.

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