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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description still adds real value beyond them: data provenance (FSC quotes for price, DART for financials) and the methodologically important note that the band uses the earnings that were actually published at each point in time. It does not discuss failure modes, missing-data behavior, or result size.

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 core question is front-loaded, which is good, but the body is a single dense run-on sentence that stacks every metric in parenthetical lists. The metric enumeration does earn its place for tool selection, yet the structure could be split into scope / outputs / sources for faster scanning.

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 return-value burden and does so reasonably: it states the band statistics, the peer comparison fields, the median, and the two data sources. Remaining gaps—response shape for a stock with no peer data, or what happens when DART financials are missing—are minor for a read-only analytics 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 baseline is 3, but the description adds meaning the schema lacks: it explains that the PER/PBR band is bounded to roughly two years of FSC quote history, which effectively qualifies the 'years' parameter (schema advertises 2–11, default 5) and warns the agent not to expect an 11-year band. The peer comparison phrasing also contextualizes the 'peers' parameter as a same-industry market-cap leader set.

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 analytical resource and enumerates its outputs precisely: current PER/PBR/PSR/POR/FCF yield/dividend yield, a ~2-year month-end PER/PBR band (min/median/max/current position), and same-industry peer comparison with a median. That scope is clearly separable from siblings like financials, price, compare and rank, though no sibling is named explicitly.

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?

The framing '싼가 비싼가' implies a valuation use case, but there is no explicit when-to-use guidance, no prerequisites, and no routing to or away from alternatives such as compare or financials. An agent must infer selection from the metric list alone.

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