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key-arg

Statable Analytics

top_countries

Identify which countries send the most visitors to your site, with ISO alpha-2 codes and display names for direct use in country filters.

Instructions

Top countries by visitors for a site. Returns {"results":[{"dimensions":{"visit:country":"US"},"labels":{"visit:country":"United States"},"metrics":{"visitors":N}}]} — the dimension value is the ISO alpha-2 code (drops straight into a country filter); the display name is in labels.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteNoNumeric site_id (preferred, from list_sites) or a domain, e.g. example.com — scheme, www. and path are ignored when matching. If several sites share the domain the call fails and lists their site_ids. Omit for a single-site key.
limitNoDefault 100, max 1000.
periodNo"7d"/"30d", or any "Nd" = last N full days (N = 1..90); "month" = current calendar month to date. Default 30d.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does a good job: it exposes the exact response shape and clarifies that the dimension value is an ISO alpha-2 code while the display name lives in labels. It does not discuss sorting or error behavior, but 'top' implies the ordering and this is not a destructive or complex operation.

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 description is one information-dense sentence that leads with the core purpose, then provides the return format and key field semantics. Every clause adds value, though the embedded JSON example makes it slightly longer than strictly necessary.

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?

There is no output schema, so the description's return-shape disclosure is essential and is handled well. Parameter defaults and site-matching nuances are covered by the input schema. Minor gaps like explicit sort order and timeout/error behavior exist, but the tool is simple enough that these are not critical.

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%, so the input schema already documents all three parameters (site, limit, period) with meaningful details. The description adds no parameter-specific semantics, so the baseline score of 3 is appropriate.

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?

The description states a specific verb and resource: 'Top countries by visitors for a site.' This clearly distinguishes it from sibling tools like top_sources and top_pages, and the country filter reference confirms it is a country-level report.

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

Usage Guidelines3/5

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

The description gives the scope ('for a site') and hints at a downstream use ('drops straight into a country filter'), so an agent can infer when to call it. However, it never explicitly contrasts it with sibling tools or states when-not-to-use it, leaving some selection burden on the agent.

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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