get_price

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

Beyond the annotations (readOnlyHint, openWorldHint, destructiveHint), the description adds valuable behavioral details: a maximum of 200 symbols per query, that the response includes the stock name, and that include_change triggers an additional daily candle lookup making the request slower. This provides practical context but does not cover error handling or edge cases.

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 concise and well-structured: it begins with the purpose, then a note about response content, followed by a clear Args section. Every sentence adds value, and the length is appropriate for the information conveyed.

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?

Given the tool's low complexity (2 params, 1 required), the presence of an output schema, and annotations that cover safety, the description provides sufficient context for an agent to select and invoke the tool correctly. It covers constraints (200 max), parameter behavior, and performance considerations, making it complete for practical use.

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 description coverage is 0%, so the description fully compensates. It explains the symbols parameter with format (comma-separated) and examples ('005930,000660' or 'AAPL'), and details include_change's meaning, its calculation, and performance impact. This goes well beyond the bare schema names.

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 states the tool retrieves the current price of a stock, with a specific verb ('조회한다' = retrieves) and resource ('현재가' = current price). It also distinguishes from siblings by noting batch support ('최대 200종목') and implying a focus on current price rather than historical data, which sets it apart from tools like get_candles.

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 description gives explicit guidance for the include_change parameter, instructing to enable it only when the user asks about price changes/fluctuations, and warns about performance when many symbols are queried. It also advises verifying the returned stock name when the user mentioned a name. However, it does not explicitly mention alternatives or when not to use the tool, though the context makes this fairly obvious.

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