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

With no annotations provided, the description carries the behavioral disclosure burden. It goes beyond a simple 'gets a quote' by warning that prices are not durable and should not be treated as lasting values. This is relevant, though it does not mention potential rate limits or data latency beyond 'real-time.'

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 description is compact and front-loaded: it states what the tool returns first, then adds the non-durability caveat. Every sentence carries value, with no redundant wording.

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?

For a simple single-parameter tool with no output schema, the description covers the key return fields and warns about data freshness. An agent can reasonably infer the expected behavior, though exact output structure and formatting are not specified.

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 the identifier parameter is well explained with examples of company names, KRX tickers, and index slugs. The description adds no additional parameter meaning, so the baseline of 3 applies.

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 clearly identifies the resource ('stock quote for one indexed company') and enumerates the returned fields (price in KRW, daily change, market cap, PER, PBR, 52-week range). This differentiates it from sibling tools like get_company or search_approvals, which serve different purposes.

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 provides useful usage context by stating the data is real-time and advising to call again for current values. However, it does not explicitly state when to prefer this tool over siblings or when not to use it, leaving some inference to the agent.

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