futures_spot_price_daily

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

The annotations already confirm read-only, idempotent, non-destructive behavior. The description adds context by specifying the data source URL, accepted date formats, and the return type (pandas.DataFrame). However, it does not disclose potential limitations, rate limits, or error behavior. The label '展期收益率数据' seems slightly inconsistent with the basis-oriented fields, but it does not contradict annotations.

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 appropriately structured with a purpose summary, source URL, parameter documentation, and a clear field dictionary. It is longer than necessary but each section adds information; the field definitions are particularly valuable given no output schema.

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?

With no output schema, the description's field dictionary covers return values comprehensively. Parameters are well-documented. However, it lacks explicit information about data frequency (daily vs intraday) and fails to differentiate from sibling tools like futures_spot_price_previous, leaving some contextual gaps.

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 provides only defaults and no descriptions for start_day, end_day, and vars_list. The description compensates fully by explaining the expected formats (YYYY-MM-DD, YYYYMMDD, datetime.date), the meaning of vars_list (contract symbols like [RB, AL]), and the default behavior (all commodities). This is a strong value-add beyond the 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 identifies the resource as '大宗商品现货价格及相应基差' (commodity spot prices and corresponding basis) for a specified time period. It distinguishes from likely sibling futures_spot_price_previous by focusing on a date range, though it does not explicitly compare 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 provides parameter defaults (e.g., start_day/end_day default to today, vars_list defaults to all commodities) but gives no guidance on when to prefer this tool over similar options like futures_spot_price_previous or spot_price_qh. No exclusions or alternatives are mentioned.

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