macro_rmb_loan

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 the source URL and return type (pandas.DataFrame), but it does not disclose whether the data is scraped, how fresh it is, or the DataFrame's columns/units. It provides some context but does not substantially go beyond the annotations.

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, with a clear label, source URL, and return annotation. It is front-loaded with the indicator name and contains no filler. The structure is a bit docstring-like rather than a full sentence, but it is efficient and every line adds value.

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 simple no-parameter read-only tool, the description provides the essential source and return type, but it omits specifics like data periodicity (monthly?), the exact columns in the DataFrame, and whether it returns historical series or only the latest value. Since there is no output schema, more detail would improve completeness.

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 schema coverage is trivially complete. The description does not need to explain parameter meaning, and the baseline of 4 is appropriate since there is nothing to document.

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 tool as providing new RMB loan (新增人民币贷款) macro data from THS Data Center, with a source URL and return type. It distinguishes itself from sibling tools like macro_rmb_deposit and macro_china_new_financial_credit by naming the specific indicator, though it lacks an explicit action verb like 'fetch' or 'query'.

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 given on when to use this tool versus alternatives such as macro_china_money_supply or macro_china_new_financial_credit. The description does not mention data frequency (e.g., monthly), date ranges, or any constraints, leaving the agent with no criteria for choosing it over similar macro tools.

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