fx_swap_quote

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds context by providing the source URL and specifying the return type as a pandas.DataFrame. However, it does not disclose any additional behavioral traits such as data freshness, network dependencies, or error handling, which would be valuable. Thus it earns a 3.

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 relatively compact, consisting of a data-path string, a URL, and a return annotation. It is front-loaded with the essential product name '人民币外汇远掉报价'. However, the title-like first line duplicates the annotation's title, and the return type could be integrated into a single sentence. Still, no wasted sentences, so a 4.

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 zero-parameter tool with no output schema, the description provides the core essentials: the data source, the type of data, and the return format. It could be more complete by mentioning the data's scope (e.g., real-time vs. historical) or typical columns, but given the simplicity, a 4 is reasonable.

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 takes no parameters, and the schema has 100% coverage (empty properties). The description does not need to explain parameters, and it adds meaning by stating the return type and data source. With zero parameters, a baseline of 4 is appropriate, and the return-type note is a useful addition.

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 returns '人民币外汇远掉报价' (RMB FX forward swap quotes) from the China Foreign Exchange Trade System, which is a specific data product. However, it lacks an explicit verb like 'get' or 'fetch', and the naming is somewhat implicit. It does distinguish from related siblings like fx_spot_quote by specifying '远掉' (forward/swap), so it earns a 4.

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 no guidance on when to use this tool versus alternatives such as fx_spot_quote, fx_pair_quote, or fx_c_swap_cm. It simply states the data source and return type, with no indication of use cases or exclusions. This is a clear gap.

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