rv_from_futures_zh_minute_sina

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

Annotations already declare readOnly=true and destructive=false, so the safety profile is covered. The description adds context about data cleaning/formatting and the returned DataFrame structure (Date, Open, High, Low, Close), which is useful but does not disclose rate limits, error behaviors, or data coverage nuances.

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 structured with a leading sentence followed by a URL and docstring-style param/return sections. The URL is extraneous, but the core content is front-loaded and each section serves a purpose. It is slightly verbose but remains readable and efficiently organized.

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 covers the essential semantics: data source, processing, parameters, and return format. However, it lacks differentiation from sibling tools like futures_zh_minute_sina, does not mention data range or pagination, and provides no output schema, leaving some ambiguity for an agent deciding between this and related tools.

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 has no parameter descriptions (0% coverage), so the description carries the full burden. It explains the symbol format with an example (IF2008 for 沪深300 futures August 2020) and lists allowed period values {'1','5','15','30','60'} minutes, adding meaningful semantics beyond the raw schema.

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 fetches minute-level historical futures data from Sina Finance and performs data cleaning/formatting. It specifies the source, data type, and processing step, which distinguishes it from raw retrieval tools like futures_zh_minute_sina, though it does not explicitly 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?

There is no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as which futures contracts are supported or when the minute-level data would be preferred over daily or real-time data, leaving the agent without explicit usage context.

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