query_etf

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals data sources (Sina, Tencent), price adjustment (no adjustment, raw prices), date coverage (daily from ~2012, min ~8 trading days), and explicit error handling for minute over-coverage. This goes beyond basic operation and gives the agent clear expectations about output and limitations.

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 with the core purpose and output format. It mixes English and Chinese but remains efficient, covering key behavioral details in two sentences. No wasted words, though the Chinese phrases could be seen as less accessible to non-Chinese readers.

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 data-query tool with a complete schema and no output schema (since output goes to file), the description covers the essential operational details: output path, data sources, coverage, and error behavior. It does not explain return values (not needed as output is written to file) and the schema already documents parameter formats. The description is sufficient for correct invocation.

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%, so the baseline is 3. The description adds value by clarifying the data source and coverage behavior tied to period and freq (e.g., min uses Tencent source with ~8 days coverage), which enriches the schema's enum descriptions. This extra context helps the agent select appropriate parameter values.

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 onshore-listed ETFs and outputs CSV to a file path. It distinguishes itself from siblings like query_stock and query_index by explicitly targeting ETFs, though it does not name alternatives.

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 implies usage when ETF data is needed but provides no explicit guidance on when to prefer this over sibling tools. It does mention data source differences (Sina for daily, Tencent for min) and coverage limitations, which helps decide when to use it, but no exclusions or alternative recommendations are given.

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