신용융자·대주 잔고 추이 조회

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

No annotations are provided, so the description carries the burden. It clearly identifies the operation as a read-only inquiry ('조회합니다') and provides domain context about the data's significance. However, it does not disclose potential response structure, pagination, or any side effects. The interpretation guidance adds value beyond a basic read-only declaration, but the lack of explicit safety/behavioral details keeps it from a 5.

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, using three sentences to cover purpose, interpretation, and alternatives. Every sentence adds value: the first states the core function, the second provides market interpretation, and the third distinguishes it from sibling tools. No fluff or repetition.

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 4 parameters with full schema coverage and no output schema, the description sufficiently explains what the tool does and when to use it. It also includes interpretation guidance that aids the agent in reasoning about results. However, it does not mention output format or pagination (though count parameter mentions 'latest first'), but this is not critical for a data-retrieval tool. The absence of annotations is compensated by the description's clarity.

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%, so the baseline is 3. The description does not add much beyond the schema for parameters; it mentions credit_type (loan/short) by defining the terms, but the schema already describes each parameter clearly. The interpretation context indirectly helps understand what parameters mean, but no new parameter-specific details are added.

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's function: retrieving new, repayment, and balance trends for credit loans (borrowed money to buy) or short borrowing (borrowed to sell) for a specific stock. It uses a specific verb (조회합니다/retrieves) and distinct resource (신용융자·대주 잔고 추이). It also differentiates from sibling tools by explicitly naming get_stock_lending and get_short_selling as alternatives for other data.

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 clear usage guidance: it states that this tool is for individual credit transactions, while get_stock_lending covers institutional/foreign securities lending and get_short_selling covers short selling volume. It also explains interpretation context (credit balance signals forced-selling pressure, short balance signals bearish bets), helping the agent decide when to use it.

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