macro_germany_gdp

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds the source URL and return type but does not disclose potential data limitations, update frequency, or network behavior. It provides minimal additional context beyond what annotations already state.

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 only the source title, URL, return type, and return format. Every line serves a purpose, and there is no redundant or filler content, making it well-structured for a zero-parameter tool.

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 provides the basic essentials: source, URL, and return format. However, it lacks details about the DataFrame's columns, data frequency (e.g., quarterly), units, or time coverage, which could be important for an agent deciding if this tool meets a user's need.

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?

With zero parameters, there is nothing for the description to explain. The schema coverage is 100% vacuously, and the baseline for a zero-parameter tool is 4 per guidelines.

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 a source for German GDP data from the East Money data center, with a specific URL and return type. The name and description together distinguish it from other macro indicators, though it lacks an explicit verb like 'get' or 'retrieve'.

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 on when to use this tool versus the many other macro_* tools for different countries or indicators. There are no explicit alternatives, exclusions, or usage context beyond the obvious 'German GDP' implication.

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