list_countriesList the ISO 3166-1 alpha-2 country codes supported for geo-targeting. Pass a model to get the codes available for that specific engine (some engines block certain countries).
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Optionally filter to countries supported by a specific engine. |
| Name | Required | Description | Default |
|---|---|---|---|
| countries | Yes | ISO 3166-1 alpha-2 country codes. |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "countries": {
+ "description": "ISO 3166-1 alpha-2 country codes.",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "countries"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds the useful behavioral detail that engines can block certain countries, which explains why results vary by model — value beyond annotations but modest in scope.
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?
Two sentences, front-loaded with what the tool returns and followed by the conditional-parameter guidance. No redundancy or filler.
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 simple read-only lookup with full schema coverage and an output schema handling return values, the description is essentially complete. The engine-blocking caveat is the one piece of non-obvious context an agent needs, and it is present.
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% and the sole parameter has an enum, so the schema fully documents the model input. The description adds the semantic rationale (engine-specific country blocking) but no format or syntax detail beyond what the schema provides. Baseline 3 is appropriate.
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 verb (List) and resource (ISO 3166-1 alpha-2 country codes for geo-targeting), which is concrete and distinguishable from siblings like list_states and the scrape_* tools. An agent immediately knows this is a reference/lookup tool returning country codes, not a scraping tool.
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?
Explicitly describes the conditional use of the optional model parameter ('Pass a model to get the codes available for that specific engine'), which is the key usage decision here. It doesn't name explicit alternatives or when-not-to-use, but the single-parameter design leaves little ambiguity.
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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