macro_usa_phs

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 agent knows this is a safe read operation. The description adds the data source URL and return type, but discloses nothing about data coverage, update frequency, or DataFrame contents. No contradiction with annotations exists.

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 compact—three lines (title, URL, return type) with no filler. The first line is redundant with the provided title, but the remaining lines earn their place by adding source and return-format context.

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, read-only tool, the description is minimally adequate: it names the data, gives the source URL, and states the return type. However, with no output schema, it leaves unspecified what columns or historical coverage the DataFrame contains and how this tool differs from the similarly named sibling macro_usa_pending_home_sales.

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, so the baseline of 4 applies; there is nothing for the description to explain. The empty input schema already provides complete coverage.

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: US pending home sales monthly rate (未决房屋销售月率) from East Money, with the source URL and a pandas DataFrame return type. However, it is essentially a restatement of the title and does not differentiate this tool from closely related siblings like macro_usa_pending_home_sales.

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 the many sibling macro_usa_* economic data tools (e.g., macro_usa_exist_home_sales, macro_usa_new_home_sales, macro_usa_pending_home_sales). There is no mention of context, prerequisites, or exclusions.

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