macro_econ

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it lists data types, it doesn't describe critical behaviors: whether this is a read-only operation, what data sources are used, historical coverage limits, rate limits, authentication requirements, or error conditions. For a data retrieval tool with 3 parameters, this leaves significant behavioral gaps.

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 a single, efficient sentence that lists all available indicators. While dense, every element earns its place by specifying the data scope. It could be improved with front-loaded categorization (e.g., 'Retrieves macroeconomic indicators including...'), but it avoids redundancy and stays focused.

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 3-parameter data retrieval tool with no annotations and no output schema, the description is minimally adequate. It covers what data is available but lacks critical context: output format, data freshness, source reliability, error handling, and usage constraints. The 100% schema coverage helps, but behavioral and output information gaps remain significant.

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?

Schema description coverage is 100%, with clear parameter descriptions in the schema. The description adds value by listing all possible indicator values (shibor, lpr, gdp, etc.), which provides semantic context beyond the schema's '指标类型' description. However, it doesn't explain parameter interactions or constraints beyond what's already documented in the 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 the tool's purpose as '获取宏观经济数据' (get macroeconomic data) and provides a comprehensive list of specific indicators including Shibor, LPR, GDP, CPI, etc. This is a clear verb+resource combination, though it doesn't explicitly differentiate from sibling tools like 'index_data' or 'stock_data' which might also provide economic indicators.

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. There's no mention of prerequisites, limitations, or comparison with sibling tools like 'index_data' or 'company_performance' that might overlap in economic data coverage. The user must infer usage from the indicator list alone.

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