macro_usa_lmci

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 covered. The description adds useful context beyond that: the data range starts 20141006, the return is the '今值(%)' series, and the source URL is given. This is modest added value, not rich behavioral disclosure.

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 resource is stated first, followed by coverage range, source URL and return type. It is compact with little filler, though the bare URL and raw Sphinx-style ':return:'/'rtype:' markup are slightly noisy rather than purpose-written prose.

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 present, the description carries the return burden itself and does state the return shape (Fed LMCI current value in percent, returned as a pandas.Series). For a zero-parameter data-fetch tool this is close to complete; only the absence of usage guidance and update frequency keeps it from a 5.

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, so the schema has nothing to document and the baseline is 4. The description correctly implies no inputs are required (data is fixed to a default full range), consistent with the empty input 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 names a specific resource ('美联储劳动力市场状况指数报告' – the Fed Labor Market Conditions Index report) and its data coverage, so an agent knows it retrieves that series. However, it does not explicitly differentiate itself from close siblings such as macro_usa_unemployment_rate or macro_usa_non_farm, which also report US labor-market data, so the agent must infer the distinction from the name.

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 statement of when to use this tool or which alternative to prefer for US labor-market data. Among the many macro_usa_* siblings, the description gives no routing guidance, leaving selection entirely to inference from the tool name.

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