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anpekesen

namegender-mcp

Countries a name appears in

name_countries

Find the countries where a first name is recorded, with counts from seven published national datasets. Use it to compare name prevalence across those countries or check if a name appears in attested records.

Instructions

Returns the countries where a name is recorded. WARNING: this is NOT a claim about origin or ethnicity. Counted birth registrations are published for only seven countries (US, UK, France, Canada, Spain, Ireland, Norway), so the ranking compares those countries only; countries that publish no counts, such as Turkey or Japan, appear in the attested list, not in the ranking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesFirst name.
limitNoHow many counted countries to return. Default 25.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses a critical behavioral trait: the ranking only compares seven countries, and countries without published counts appear in the attested list but not the ranking. This is valuable context beyond the schema. It does not mention pagination or exact return structure, but the core behavioral caveat is clearly disclosed.

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 two sentences with no wasted words. The core purpose is front-loaded, and the critical warning is placed immediately after. Every sentence earns its place, and the structure is easy to parse.

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 simple two-parameter tool with no output schema, the description covers the essential context: what the tool returns, the data source limitation, and the interpretation warning. It doesn't describe the exact return format, but given the tool's simplicity and the schema's completeness, the description is sufficiently complete for an agent to call it correctly.

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 schema already documents both parameters ('name' and 'limit'). The description adds context about what 'limit' controls ('How many counted countries to return') implicitly through the ranking explanation, but it doesn't add new parameter-level detail beyond the schema. Baseline 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 ('Returns') and resource ('countries where a name is recorded'), and immediately distinguishes itself from origin/ethnicity claims. The title 'Countries a name appears in' is reinforced by the description's explicit scope, making the tool's purpose unambiguous.

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?

The description clearly explains the data source limitation (only seven countries publish counts) and warns against misinterpreting the ranking as origin/ethnicity. It does not explicitly name sibling tools as alternatives, but the warning effectively tells the agent when NOT to use this tool for origin/ethnicity questions, which is strong usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.