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datasets_numbeo_cities_facets

Returns city counts per country from the Numbeo dataset, narrowed by cost of living, safety, pollution, and other index thresholds.

Instructions

Facet the Numbeo cities dataset. Returns city counts per country for the Numbeo cities dataset; facet is required and accepts only country. Narrow the counts with q, country and index thresholds such as min_cost_of_living_index, min_safety_index or max_pollution_index. Items are value and count pairs.

Input Schema

NameRequiredDescriptionDefault
qNoFull-text query over the city name, max 256 characters
facetYesFacet enum: country
countryNoExact country filter, max 128 characters
max_crime_indexNoMaximum Crime Index
min_crime_indexNoMinimum Crime Index
min_safety_indexNoMinimum Safety Index
max_traffic_indexNoMaximum Traffic Index
max_pollution_indexNoMaximum Pollution Index
min_health_care_indexNoMinimum Health Care Index
max_cost_of_living_indexNoMaximum Cost of Living Index (New York = 100)
min_cost_of_living_indexNoMinimum Cost of Living Index (New York = 100)
min_quality_of_life_indexNoMinimum Quality of Life Index

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / facet / enum
      Added value: +[
      +  "country"
      +]
  2. Addedv1.5.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It usefully discloses the return shape ('Items are value and count pairs') and that the facet dimension is restricted to country, but it says nothing about auth requirements, rate limits, or pagination, and read-only behavior is only implied by the word 'facet'.

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?

Three compact sentences that are front-loaded with purpose and the required-parameter constraint. Each sentence carries distinct information, with only minor redundancy between 'facet the dataset' and 'returns city counts per country'.

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?

With no output schema, the description compensates by explaining the return format (value/count pairs) and the required facet dimension. For a 12-parameter aggregation tool this is reasonably complete, though it omits how multiple index thresholds interact and whether counts reflect the filtered subset.

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 all 12 parameters. The description echoes a few parameter names (q, country, min_cost_of_living_index, min_safety_index, max_pollution_index) as examples but adds no syntax, units, or combination rules beyond what the schema provides, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (facet) and resource (Numbeo cities dataset), and states what the operation returns: city counts per country. It clearly distinguishes itself from the search/item siblings by describing a facet/aggregation role, though it does not explicitly name those alternatives.

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?

It states that `facet` is required and only accepts `country`, and it explains that counts can be narrowed with `q`, `country`, and index thresholds. However, it never says when to choose this tool over datasets_numbeo_cities_search or the item tool, leaving the agent to infer usage from the word 'facet'.

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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