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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'time series.' It does not disclose ordering, date coverage, pagination, the effect of limit, or whether values are raw or adjusted, leaving the response semantics largely unknown.

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 single sentence is free of filler and front-loads the core result type. It is appropriately short, though it is so minimal that it leaves no room for the behavioral or routing details the tool needs.

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 two-parameter tool with no annotations and no output schema, the return shape and the limit parameter are essential but unexplained. An agent would need to guess what the time-series response looks like and how to discover a valid indicator_id, possibly through get_macro_indicators.

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 0%, so the description must compensate by explaining the parameters. It clarifies that indicator_id identifies a single indicator, but it does not explain limit or its default of 200, leaving the optional parameter effectively undocumented.

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 states that the tool returns time-series data for a single macro indicator selected by id, which differentiates it from list-style siblings like get_macro_indicators. It lacks an explicit verb like 'returns' and the phrase 'data center' is somewhat ambiguous, but the resource and scope are generally clear.

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 when-to-use guidance is provided. The description never mentions get_macro_indicators as the way to obtain an indicator_id or states when this tool should be selected over other macro or stock-data siblings. The only implicit signal is 'by id,' which is too weak to route an agent confidently.

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