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UN-Habitat — SDG 11.2.1 Public Transport Access

unhabitat.urban.transport_access
Read-onlyIdempotent

Retrieve city-level data on the proportion of urban population with convenient access to public transport (SDG indicator 11.2.1). Covers 1,555 cities across all world regions from the UN-Habitat Urban Indicators Database. Filter by country, city name, or UN region. Returns access percentage and estimate source per city. Useful for urban mobility analysis, SDG 11 reporting, and comparing public transit equity across cities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoFilter by city name (partial match, e.g. "Nairobi", "Lagos", "Mumbai"). Case-insensitive.
limitNoMaximum number of cities to return (1–100, default 50).
regionNoFilter by UN-Habitat region (partial match). Regions include "Sub-Saharan Africa", "Northern America and Europe", "Eastern and South-Eastern Asia", "Central and Southern Asia", "Latin America and the Caribbean", "Northern Africa and Western Asia", "Oceania".
countryNoFilter by country name (partial match, e.g. "Kenya", "United States", "Brazil"). Case-insensitive.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context: the tool covers 1,555 cities across all world regions, returns access percentage and estimate source per city, and supports partial matching on filters. This goes beyond what annotations provide.

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 three sentences with no redundancy. It front-loads the core purpose, then adds scope, filters, and use cases. Every sentence earns its place.

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?

The description covers purpose, scope, filters, and use cases. With an output schema present and annotations covering safety, the agent has enough to call the tool correctly. Minor gap: no mention of pagination or default behavior beyond the limit parameter, but the schema covers that.

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 four parameters (city, limit, region, country) with examples and constraints. The description adds the filter dimensions at a high level but doesn't add meaning 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 clearly states the tool retrieves city-level data on public transport access (SDG 11.2.1), specifies the data source (UN-Habitat Urban Indicators Database), and lists filter dimensions (country, city, region). It distinguishes itself from sibling tools like unhabitat.urban.city_budget and unhabitat.urban.land_consumption by focusing on the specific SDG indicator.

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 provides clear context for when to use this tool (urban mobility analysis, SDG 11 reporting, comparing transit equity) and lists the available filters. It doesn't explicitly state when not to use it or name alternative tools, but the use cases are specific enough that an agent can determine applicability.

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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