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

Annotations already establish readOnly/idempotent/non-destructive/closed-world, so the description only needs to add substance — which it does: results are organised per source table, prefixed by a list of the dimensions and values available for that company, include prior-year values, deltas and share of total, include company-disclosed plan/forecast figures and row-level tables, and each table carries its basis (consolidated/separate), entity and footnotes. That is real context about output shape and scoping that the annotations cannot convey.

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?

The purpose is front-loaded and every clause carries content, but it is delivered as one very dense run-on paragraph with long enumerations of dimensions and table types, which is harder to scan than a short structured list would be. It is not padded, but it is not well-structured either.

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 burden of describing returns, and it does so adequately: dimension/value registry at the top, per-table breakdowns with amounts, prior-year comparison and share, basis/entity/footnote metadata, plus row-level tables. What remains unspecified — pagination, volume of output, or how missing dimensions are signalled — is minor for a read-only lookup tool.

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 the schema already documents all five parameters, including the topic list and period formats. The description adds only the default topic value and an illustration of how 'where' narrows, which mostly restates schema content — baseline 3 is appropriate.

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 a specific verb and resource (breaking a single company/report's business composition into per-table breakdowns of revenue, customers, volume, price, backlog, production, raw materials and capex, across named dimensions), which is far more specific than the name 'breakdown' alone. It does not, however, contrast itself against the many adjacent siblings (business_trend, business_rank, business_search, financials, earnings), so the agent must infer the boundary.

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 gives operational guidance on narrowing results ('where 로 좁혀 더 깊이', e.g. '판매지역=수출') and states the default topic (sales), which implies how to use it. But there is no explicit when-to-use-this-instead-of guidance versus business_trend/business_rank/financials, and no stated preconditions or exclusions.

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