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Glama

En qué departamento y localidad cae un punto

ubicar_punto
Read-onlyIdempotent

Find Uruguay's department and locality for any latitude/longitude using INE polygons, including 2023 population; for rural points, returns nearest locality and distance plus nearest IDE.uy address.

Instructions

Dado un punto (latitud y longitud en grados), en qué departamento y en qué localidad de Uruguay cae, según los polígonos oficiales del INE, con la población 2023 de la localidad. Si cae en el campo, la localidad más cercana y a qué distancia. Suma la dirección más cercana de IDE.uy con su distancia. Combinar con geocodificar_direccion para pasar de una dirección a su departamento.

Input Schema

NameRequiredDescriptionDefault
latYes
lonYes

Output Schema

NameRequiredDescriptionDefault
latYes
lonYes
notaYes
bajadoYes
fuenteYes
localidadYes
departamentoYes
direccion_mas_cercanaYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.13.2

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds real value beyond that: the data source (official INE polygons), the 2023 population enrichment, the fallback behavior when the point falls in open country (nearest locality plus distance), and the IDE.uy nearest-address augmentation.

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?

The core purpose is front-loaded in the first clause and every subsequent clause adds information (population, countryside fallback, address enrichment, sibling combination). It is a long run-on sentence that could be split for scannability, but nothing is truly wasted.

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 an output schema present and rich annotations, the description need not explain return values, and it still covers provenance, fallback logic, and workflow composition. The one meaningful gap is behavior for coordinates outside Uruguay, which an agent would want to know before calling.

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 coverage is 0% — both parameters are bare numbers with only titles. The description compensates partially by specifying that lat/lon are in degrees, which the schema does not say, but it omits the coordinate reference system and any valid range or out-of-country error behavior.

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: given a point (lat/lon), return the department and locality in Uruguay it falls in, per INE polygons. It also implicitly distinguishes itself from the sibling geocodificar_direccion by framing that tool as the address→coordinates direction.

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?

Explicitly tells the agent to combine this with geocodificar_direccion to go from an address to a department, which clarifies the intended role in a two-step workflow. It lacks an explicit when-not-to-use statement (e.g. points outside Uruguay), so it falls short of a 5.

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