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Agent Data Tools: Everyday data

by io.github.Nutshell2000
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Country info, country facts: facts about a country: capital, region, income level and population

country
Read-only

Facts about a country by ISO code (SE, SWE, US…): official World Bank name, ISO-2 and ISO-3 codes, region, income level, capital city and its coordinates, and the latest population figure with its year (World Bank open data). Use to enrich records with country data. Example: country=SE. Price $0.01/call via x402 USDC or a card key (/credits), first 25 free; failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "country": "<country>"
    },
    "name": "country"
  }
}

Input Schema

NameRequiredDescriptionDefault
countryYesISO 3166 alpha-2 or alpha-3 code

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial behavior beyond annotations: pricing ($0.01/call), access methods (x402 USDC or card key /credits), the first 25 calls free, and failed calls free. It also reinforces that the call reads/computes only and that repeated calls are billed, which is useful operational context not captured by the annotations.

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?

Front-loads the resource and returned fields, then adds useful pricing context. It is somewhat dense, and the phrase 'Reads or computes only and changes nothing' partly repeats the readOnly/destructive annotations, but overall there is little waste.

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?

For a simple one-parameter lookup with no output schema, the description fully covers the returned data fields, data source (World Bank open data), and billing behavior. An agent has everything needed to call it correctly.

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

Parameters4/5

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

Schema coverage is 100% and the parameter is already documented as ISO 3166 alpha-2 or alpha-3. The description nonetheless adds examples (SE, SWE, US, country=SE) that make the accepted format immediately clear, providing modest value beyond the schema.

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?

States a specific verb and resource: returns facts about a country by ISO code, then enumerates the exact fields returned (name, ISO-2/ISO-3, region, income level, capital coordinates, population). It is clearly distinguishable from sibling geocoding and economic-indicator tools.

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?

Gives a clear usage context ('Use to enrich records with country data') and a concrete example ('country=SE'). It does not explicitly compare against alternatives such as geocode or econ_population, so it stops short of full when/when-not guidance.

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

All Agent Data Tools: Everyday data toolsInspect
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