index_option_50index_min_qvix

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds the data source URL and confirms the return type (pandas.DataFrame), which goes beyond annotations. However, it does not disclose any further behavioral details such as data granularity (e.g., 1-minute vs 5-minute intervals), trading session specifics, or potential network dependencies. It is not misleading but does not enrich the behavioral picture beyond the basics.

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 tool's identity. It includes a helpful source URL and a clear rtype declaration. The main redundancy is the repetition of the same Chinese phrase after ':return:', which could be omitted without loss of information. Overall, it is appropriately sized and not bloated.

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?

This is a simple zero-parameter retrieval tool, and the description states the resource and return type sufficiently for a basic invocation. However, since there is no output schema, the description should ideally clarify the expected DataFrame structure (e.g., column names, index, frequency), but it does not. The source URL helps, but the tool remains underspecified for an agent that needs to interpret the return value programmatically. It is adequate for calling the function but incomplete for data understanding.

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 input schema has zero parameters and 100% schema coverage, meaning there is nothing to describe. The baseline for 0-parameter tools is 4, and the description adds no parameter-related confusion. It avoids inventing unnecessary parameter semantics.

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 identifies the resource: '上证50股指 期权波动率指数 QVIX-分时' (SSE 50 Stock Index Options Volatility Index QVIX intraday). It also specifies the return type as pandas.DataFrame, and the appended URL provides the data source. However, it lacks an explicit verb (e.g., 'fetch', 'get'), and the distinction from sibling tools like index_option_50index_qvix (non-min) relies on the parenthetical '分时' rather than any clarifying wording.

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?

No guidance is provided on when to use this tool versus alternatives. Despite a large sibling list of QVIX tools for different underlyings and timeframes (e.g., index_option_50index_qvix for daily data, index_option_50etf_min_qvix for ETF-based QVIX), the description does not mention these alternatives or any exclusion criteria. The only hint is the name and '分时', which imply intraday use, but that is implicit and not stated as usage guidance.

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