macro_china_non_man_pmi

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, establishing the safety profile. The description adds the data range (20160101 to present) and the return type (pandas.DataFrame), which are useful behavioral details. However, it does not disclose other behaviors such as update frequency, data source caveats, or column structure, so the added value is moderate.

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 concise and front-loaded with the key purpose. It includes a source URL and explicit return type annotations. There is minor redundancy (the phrase '中国官方非制造业 PMI' appears twice), but overall it is appropriately sized and structured with no wasted content.

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?

Given the tool is simple (no parameters, no output schema), the description covers the essentials: what data is returned, the date range, and the return type (pandas.DataFrame). It also provides a source URL for verification. It could mention more about the DataFrame's columns or update frequency, but for a zero-parameter data retrieval tool, this is largely complete.

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 0 parameters, so the baseline is 4. The description adds context by stating the data range is from 20160101 to present, implying no user-specified date filtering is available. This is a useful semantic detail beyond the empty 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 clearly states what the tool returns: China's official non-manufacturing PMI, with a specific date range (from 20160101 to present). The term '非制造业 PMI' differentiates it from manufacturing PMI siblings, though it lacks an explicit verb like 'get' or 'fetch' and does not name alternatives.

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 alternatives. It does not mention sibling tools like macro_china_pmi or give any context about suitable use cases, prerequisites, or exclusions. The only implied usage is for non-manufacturing PMI data, but this is not explicit.

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