macro_china_new_financial_credit

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety behavior is covered. The description adds the data source URL and return type (pandas.DataFrame), but does not explain data frequency, granularity, or any other behavioral nuances. It does not contradict 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 extremely concise, containing a title, source URL, and return type in a docstring-like structure. Every line serves a purpose (identifies resource, gives provenance, and output type), but it is under-specified rather than optimally concise. No unnecessary words.

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, the description is incomplete. It does not describe what the data actually means (e.g., monthly new loans, sector breakdown), the data frequency, or how it differs from similar macro indicators. The return description '新增信贷数据' just repeats the title, adding little value. Given the absence of an output schema, the description should provide more context about the returned data.

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 (100%). The description does not need to explain parameters since there are none. Baseline of 4 for zero parameters is appropriate; no additional parameter semantics are required.

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 China's new credit data (中国-新增信贷数据) and includes the data source URL. The resource is specific and the return type is stated, but it lacks an explicit verb and does not differentiate from other macro_china_* credit-related tools beyond 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?

No guidance is provided about when to use this tool versus alternatives. With many sibling macro_china_* tools, the description does not mention exclusions, prerequisites, or comparison to similar tools like macro_china_money_supply or macro_rmb_loan.

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