stock_us_spot

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

The description adds key behavioral context beyond annotations, including the 15-minute data delay, which is critical for time-sensitive decisions. It also specifies the source URL and return type (pandas DataFrame). Annotations already cover read-only and idempotency, so the extra details are valuable.

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 concise and front-loaded with the core purpose, followed by the source URL and return type. Every line adds value (source, delay, return type) with no redundant filler.

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 parameterless tool returning a snapshot, the essential details are covered: data source, universe (all US stocks), delay, and return type. The empty schema and simple behavior make the description complete, though it could mention columns or data volume without harming the overall adequacy.

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 tool has zero parameters and an empty schema, so there is nothing to describe. The baseline for 0 params is 4, and the description doesn't need to add parameter information.

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 it provides '所有美股的数据' (all US stock data) from Sina Finance, with a return of real-time quotes. It distinguishes itself from siblings like `stock_us_spot_em` by specifying the source (Sina) and universe (all US stocks), though it lacks an explicit action verb.

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. The 15-minute delay is a caution but not a usage recommendation, and there is no mention of when to prefer other spot tools or what to use for lower latency or different data.

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