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

Annotations only declare readOnlyHint, yet the description adds real behavioral context: deterministic ordering by code, one row per company, the default of scope=published, the meaning of the hasBenefits=false/null rows, and an explicit cost signal ('Costs 10 tokens'). It does not cover pagination behavior or an upper-bound note on result volume.

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 resource and field list, then filters, then the scope caveat and cost — a sensible order with no filler. The single dense sentence chain and the duplicated Japanese phrasing are slightly heavy but serve a bilingual audience.

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 and 8 optional parameters, the description compensates by enumerating the return fields and their meaning, so an agent knows what to expect. The remaining gap is pagination/result-size behavior (limit default 100, max 2000; offset 0), which is undocumented in prose.

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 75%, so most parameters are already documented, setting the baseline at 3. The description adds some mapping (month 1-12, benefit type, minimum shares/investment as filters) but glosses 'minimum shares or investment' as a filter without conveying that minSharesLowerThan/minInvestmentLowerThan are upper bounds, and never mentions limit/offset or asOf.

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 the resource precisely ('Japanese companies with shareholder benefits'), the row granularity ('one row per company, ordered by code'), and enumerates the returned fields, which separates it from the single-company sibling get_shareholder_benefits. It stops short of naming that sibling explicitly, so the agent must infer the list-vs-detail split.

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 explains what each filter does and clarifies the non-obvious scope semantics ('scope=all also includes companies confirmed to have none ... and unconfirmed ones (null)'), which is genuine when-to-use guidance. However, there is no guidance on when to prefer this over get_shareholder_benefits or screen_stocks, and no stated exclusions.

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