get_stock_total

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'analysis' but doesn't clarify if this is a read-only data fetch, a computational tool, or something else. It lacks details on permissions, rate limits, output format, or any side effects. For a tool with no annotations, this leaves critical behavioral traits unspecified.

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 a single, concise sentence in Korean that directly states the tool's focus. It's front-loaded with the core purpose and avoids unnecessary words. However, it could be more structured by separating the action from the outcome, but it's efficient and doesn't waste space.

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 no annotations, no output schema, and a vague purpose, the description is incomplete. It doesn't specify what the tool returns (e.g., raw data, analysis report) or how it behaves. For a tool with 3 required parameters and complex sibling context, more detail is needed to guide effective use, such as explaining the analysis output or usage scenarios.

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 100%, with clear descriptions for corp_code, bsns_year, and reprt_code. The description adds no parameter-specific information beyond what the schema provides. It doesn't explain how these inputs relate to the analysis or provide examples. Baseline 3 is appropriate since the schema does the heavy lifting, but the description doesn't compensate with additional context.

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 '주식 총수 내역을 통한 자본금 구성 및 유통물량 리스크 분석' translates to 'Capital composition and circulating volume risk analysis through total stock details.' It indicates the tool analyzes stock-related data but is vague about the specific action (e.g., retrieve, calculate, generate). It mentions 'analysis' but doesn't specify if it fetches data or performs computations, and it doesn't clearly distinguish from siblings like get_stock_increase_decrease or get_stock_exchange.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., for financial reporting, risk assessment), or exclusions. With many sibling tools related to stocks and corporate data, there's no indication of how this differs or when it's appropriate, leaving the agent to guess based on the name alone.

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