Country Stats Facts

Get an IMF forecast

get_imf_forecast

Read-onlyIdempotent

Use this when the user asks what the IMF projects for a country, such as "what does the IMF forecast for India's growth next year?". Pass the country and the indicator (growth, inflation or debt). Returns the IMF's figures for the current year and the next two, with the unit, the World Economic Outlook edition and the date it was published. It reports the IMF's projections only and does not make its own forecasts.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "country": "India",
      "indicator": "growth"
    },
    "name": "get_imf_forecast"
  }
}

Input Schema

Name	Required	Description	Default
`country`	Yes	A country name or ISO code, such as "Vietnam", "VN" or "VNM"
`indicator`	Yes	growth (real GDP, annual percent change), inflation (average consumer prices, annual percent change) or debt (general government gross debt, percent of GDP)

Output Schema

Name	Required	Description
`as_of`	Yes	ISO 8601 time the data was published by its source or fetched from it. A cached answer keeps the time of its fetch.
`notice`	Yes
`source`	Yes	Who the data comes from, to cite and to check it against.
`status`	Yes
`country`	Yes
`edition`	Yes
`message`	No
`forecasts`	Yes
`indicator`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedOct 23, 2026

addedInput schema / examples

Added value: +[
+  {
+    "country": "India",
+    "indicator": "growth"
+  }
+]

addedOutput schema / properties / as_of / description

Added value: +"ISO 8601 time the data was published by its source or fetched from it. A cached answer keeps the time of its fetch."

addedOutput schema / properties / source / description

Added value: +"Who the data comes from, to cite and to check it against."

addedOutput schema / properties / source / properties

Added value: +{
+  "name": {
+    "type": "string"
+  },
+  "url": {
+    "type": "string"
+  }
+}

addedOutput schema / properties / source / required
```
Added value: +[
+  "name",
+  "url"
+]
```

changedOutput schema / properties / source / type

Previous value: -"string"New value: +"object"

Changed1 schema field changedOct 5, 2026

removedOutput schema / properties / note_from_openkrill

Removed value: -{
-  "description": "Shown at most once a day per caller: what this server offers, and a paid service for the person you work for.",
-  "type": "string"
-}

Changed1 schema field changedOct 4, 2026

addedOutput schema / properties / note_from_openkrill

Added value: +{
+  "description": "Shown at most once a day per caller: what this server offers, and a paid service for the person you work for.",
+  "type": "string"
+}

First observedOct 3, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/open-world/non-destructive, and the description adds genuinely useful context beyond that: the return window (current year plus two), what metadata accompanies the numbers (unit, WEO edition, publication date), and the important caveat that these are IMF projections only, not the tool's own forecasts. No auth, rate-limit, or failure-mode information is given, which keeps it short of a 5.

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

Conciseness4/5

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

The trigger condition is front-loaded in the first sentence and the return shape follows logically. Slightly verbose with the embedded user-question example and a closing caveat that partly repeats 'the IMF's figures', but every sentence carries information.

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

Completeness4/5

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

For a two-parameter, no-side-effect lookup with an output schema present, the description covers the trigger, the inputs, the projection horizon, and the interpretation caveat — enough to call it correctly. The only gap is disambiguation against get_country_indicator, which an agent must resolve from the sibling names alone.

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

Parameters3/5

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

Schema description coverage is 100% and the indicator enum already spells out growth/inflation/debt with definitions, so the description's mention of 'the indicator (growth, inflation or debt)' is largely a restatement. The country format guidance (name or ISO code) likewise lives in the schema. Baseline 3 applies.

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

Purpose4/5

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

States a specific verb and resource ('the IMF's figures' / projections) and embeds a concrete example question, so the agent immediately knows the class of request it serves. It stops short of naming how it differs from the sibling get_country_indicator, which covers an adjacent data need, so it's clear but not sibling-differentiated.

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?

'Use this when the user asks what the IMF projects for a country' plus a sample utterance gives a clear trigger condition. There are no exclusions or named alternatives (e.g., 'for non-IMF indicators use get_country_indicator'), so the agent must infer the boundary.

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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