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Visa Requirements

by io.github.pipeworx-io
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Visa Requirement

visa_requirement
Read-onlyIdempotent

Do I need a visa? Visa requirement for one passport (nationality) traveling to one destination country — returns visa-free (with allowed stay days when known), visa on arrival, e-visa, eTA, visa required, or no admission. Covers 199×199 country pairs. Data: community-maintained Passport Index snapshot (last updated 2026-02-18) — verify with official sources before travel. Example: visa_requirement({ passport: "United States", destination: "Brazil" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
passportYesPassport / nationality — ISO2, ISO3, or country name, e.g. "US", "DEU", "South Korea", "UK"
destinationYesDestination country — ISO2, ISO3, or country name, e.g. "BR", "Japan", "Türkiye"

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "destination": "Brazil",
+    "passport": "US"
+  },
+  {
+    "destination": "Japan",
+    "passport": "Germany"
+  }
+]
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds valuable context: data is community-maintained, last updated 2026-02-18, covering 199×199 country pairs, and advises verifying with official sources. It also illustrates the output format via an example. No contradictions with annotations.

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 concise and front-loaded with a natural language question ('Do I need a visa?'). It efficiently conveys purpose, input, output, coverage, data source, and an example in a few sentences without redundancy.

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?

Despite lacking an output schema, the description compensates by listing possible return values, providing an example, stating coverage (199×199 country pairs), and noting data freshness and source. This is complete for a lookup tool with such rich annotations.

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

Parameters5/5

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

Schema coverage is 100% with detailed descriptions for both parameters (passport and destination). The description goes beyond the schema by providing accepted formats (ISO2, ISO3, country name) and an example usage that explicitly shows how to call the function. This adds significant meaning.

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 clearly states the tool's function: it returns visa requirements for a single passport-destination pair. It lists possible return values (visa-free, visa on arrival, e-visa, eTA, visa required, no admission) and distinguishes itself from sibling tools like visa_free_destinations and visa_passport_compare by focusing on a single country pair.

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 implicitly guides usage by specifying input as one passport and one destination. However, it does not explicitly compare with sibling tools or state when to use this tool versus alternatives. An example and coverage note are provided, but clearer exclusion criteria would improve this dimension.

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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