query_options

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

With no annotations provided, the description carries the full responsibility for revealing behavior. It clearly states that output is written to a file_path as CSV, and the use of 'Query' implies a read-only operation. However, it does not mention whether the file is overwritten, whether any network requests are made, or any potential side effects beyond file creation.

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 information-dense, with no fluff. It uses a structured format with bullet-like separations for the kind values, and the key operational note about finding contract codes is succinctly embedded. Every sentence contributes to understanding the tool, and the mixed Chinese/English is efficient for the intended domain.

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?

The description provides enough context for an agent to use the tool correctly: it covers the data scope, output format, the three query kinds, and a workflow tip. Since there is no output schema, it does not need to describe return values. However, it could be more complete by explicitly stating that the 'hist' kind requires start_date and end_date, or by noting default behaviors, but overall it is sufficient for basic usage.

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?

The schema descriptions cover all parameters, and the tool description adds meaningful context: it explains that 'kind' controls the query mode, that 'underlying' applies to months/contracts, that 'trade_date' is for contracts/CFFEX, and that start_date/end_date are for hist. This goes beyond the schema by clarifying which parameters are relevant for each kind, making the semantics clearer.

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 queries China options, specifically SSE ETF options and CFFEX index options (IO/HO/MO), which distinguishes it from sibling tools like query_etf, query_index, and query_futures. It also indicates the output is written to a CSV file, giving a complete picture of the tool's primary function.

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 explains the three 'kind' values (months, contracts, hist) and provides a practical hint: '本轮仅日线' (only daily data for now) and '找合约代码先用 months/contracts' (find contract codes via months/contracts first). This guidance helps the agent choose the correct workflow, though it does not explicitly compare to alternative sibling tools.

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