macroMacroeconomic series. view=indicators lists indicators. view=countries lists countries. view=series is one country in Alpha-3; pass country, and indicator when you want a single indicator.
| Name | Required | Description | Default |
|---|---|---|---|
| view | Yes | indicators, countries, or one country series. | |
| country | No | Select Country in Alpha-3 ISO format. | |
| indicator | No | Select desired indicator. Default: gdp_current_usd |
Changes observed during successful MCP inspections.
Input schema / additionalPropertiesAdded value: +falseInput schema / properties / viewAdded value: +{
+ "description": "indicators, countries, or one country series.",
+ "enum": [
+ "indicators",
+ "countries",
+ "series"
+ ],
+ "type": "string"
+}Input schema / requiredPrevious value: -[
- "country"
-]New value: +[
+ "view"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds only the semantic mapping of view values to behavior, with no data range, freshness, rate limit, or return-shape context beyond what the schema enum already conveys.
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?
Three short, declarative sentences with zero filler; the resource statement is front-loaded and each subsequent clause maps one view mode to its parameters. Every sentence earns its place.
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?
Covers all three parameters and the view routing, which is the core need. With no output schema and no description of what a series result actually contains (single value, time series, units), an agent cannot anticipate the response shape.
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 coverage is 100% so the baseline is 3, but the description goes further by explaining parameter interaction: country is only meaningful with view=series, and indicator is optional for a single-indicator pull. That clarifies the combinatorial semantics rather than repeating field text.
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?
States a specific resource (macroeconomic series) and enumerates the three view modes, so the agent knows exactly what data domain this covers. However, it never differentiates itself from siblings like 'government' or 'bond', which also deal with macro-flavored economic data, so selection still relies on name inference.
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 gives clear internal routing guidance: view=indicators lists indicators, view=countries lists countries, and view=series needs country/indicator. But it offers no when-to-use-this-vs-another-tool guidance against the 22 siblings, and no exclusions, so cross-tool selection is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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