macro_uk_retail_monthly

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, which cover safety expectations. The description adds the source URL and return type (pandas.DataFrame), providing some context about return format, but does not disclose further behavioral details like data granularity or update frequency.

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 extremely concise: a title line, a source URL, a return value line, and a return type line. Every line earns its place with no redundancy or 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 zero-parameter tool with no output schema, the description includes the source, the exact indicator, the frequency, and the return type. It could be more explicit that it returns a time series of historical monthly values, but it is largely complete for a simple data retrieval tool.

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?

There are zero parameters, so the baseline score of 4 applies. The description adds no parameter-specific meaning, but none is needed. It does document the return value and type, which is useful context for the output.

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 '东方财富-经济数据-英国-零售销售月率' (Eastmoney - Economic Data - UK - Retail Sales Monthly Rate) and specifies the return value as '零售销售月率' (retail sales monthly rate). This distinguishes it from sibling macro_uk_retail_yearly by frequency.

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 clear context about the data returned but gives no explicit guidance on when to use this tool versus alternatives. Sibling tools like macro_uk_retail_yearly exist, but no exclusions or alternatives are mentioned. Usage is implied by the name and description.

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