macro_china_industrial_production_yoy

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior. The description adds useful context: the data range, source URLs from Jin10, and the pandas.DataFrame return type. No behavioral contradictions with annotations exist.

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 relatively short and front-loaded with the core purpose. It includes supplementary source URLs and return type, though the first sentence largely duplicates the annotation title and the URLs are not strictly necessary for invocation.

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 zero-parameter data-retrieval tool, the description provides the data set, date range, source, and return type, while annotations cover safety semantics. It does not enumerate the DataFrame columns, but this is not a critical gap given the tool's simplicity.

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 and 100% schema description coverage, so the schema already fully defines the input. Description adds no parameter details, which is appropriate for this zero-parameter tool; baseline 4 applies.

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 returning China's industrial value-added year-over-year report (中国规模以上工业增加值年率报告) with a specific data range from 19900301 to present. It distinguishes itself from sibling macro indicators by naming the exact metric, though it lacks an explicit verb like 'retrieve' or 'fetch'.

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?

Usage is implied by the data description: an agent would use this when needing China's industrial production YoY report. However, there is no explicit guidance on when to choose this over sibling macro_china_* tools or any mention of alternatives/exclusions.

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