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Get IMF Government Fiscal Balance

imf.macro.fiscal_balance
Read-onlyIdempotent

Get general government net lending/borrowing (fiscal balance, percent of GDP) from the IMF World Economic Outlook (WEO) for one or more countries, including IMF forward projections. Filter by ISO 3166-1 alpha-3 country code(s) and/or a year range; omit filters to get all 190+ countries plus regional/income-group aggregates. Data: IMF DataMapper (www.imf.org), CC BY 4.0, no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoISO 3166-1 alpha-3 country code to filter (e.g. "USA", "DEU", "JPN", "CHN"). Omit to return all 190+ countries plus IMF regional/income-group aggregates.
end_yearNoLatest year to include, including IMF WEO forward projections (e.g. 2029). Omit for full history.
countriesNoList of ISO 3166-1 alpha-3 country codes to filter (e.g. ["USA","DEU","JPN"]), max 20. Use instead of "country" to fetch multiple countries in one call.
start_yearNoEarliest year to include in the returned time series (e.g. 2015). Omit for full history.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable context: it includes IMF forward projections, that omitting filters returns all countries plus regional/income-group aggregates, the data source and license, and that no auth is required. This goes beyond the annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, information-dense sentence that front-loads the core purpose. Every element—data source, metric, filter options, default behavior, licensing, and auth—earns its place. No redundancy or fluff; it is efficiently structured for quick parsing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the existence of an output schema (which handles return-value details), the description covers all essential aspects: what the tool does, how to filter, default behavior, data provenance, licensing, and authentication. For a read-only data retrieval tool, nothing an agent needs to correctly invoke it is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are fully documented in the schema. The description adds a key behavioral nuance not in the schema: omitting filters yields all 190+ countries plus aggregates. This clarifies the default behavior and the distinction between 'country' and 'countries' parameters, adding value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Get) and resource (fiscal balance, percent of GDP) from the IMF WEO. Differentiates from sibling tools like imf.macro.current_account, imf.macro.gdp_growth, imf.macro.inflation by naming the exact indicator. The description makes the tool's function unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clearly explains how to use the tool: filter by ISO country codes and year range, or omit to get all countries plus aggregates. While it doesn't explicitly contrast with sibling tools, the specific indicator name makes alternatives obvious. It provides clear context on the filtering options and default behavior, but lacks an explicit 'when not to use' statement.

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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