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Glama

Nivel del río en una estación de Salto Grande

nivel_rio
Read-onlyIdempotent

Retrieves daily minimum, average, and maximum river heights for a Salto Grande station, plus the latest reading and change over a selected period.

Instructions

Altura del río (H) en una estación de la Comisión Técnica Mixta de Salto Grande, resumida por día (mínimo, media y máximo), con la última lectura y cuánto subió o bajó en el período. Lecturas cada 15 minutos. estacion es el nombre o el id (por defecto Salto); desde/hasta AAAA-MM-DD, hasta 92 días, por defecto los últimos 14. Para encontrar una estación cerca de un lugar, usar estaciones_cercanas.

Input Schema

NameRequiredDescriptionDefault
desdeNo
hastaNo
estacionNoSalto

Output Schema

NameRequiredDescriptionDefault
diasYes
notaYes
bajadoYes
fuenteYes
estacionYes
coberturaYes
caudal_Q_mediaYes
ultima_lecturaYes
variacion_en_el_periodoYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.13.2

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and non-destructive, so the safety profile is covered. The description adds genuinely useful behavioral facts beyond that: readings every 15 minutes, per-day aggregation, a 92-day maximum window and a 14-day default. It does not discuss behavior at the window limit or how a station name is resolved, keeping it just short of 5.

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?

Front-loaded with what is returned, then parameters, then the sibling fork. Every clause adds information — the interval, the aggregation, the window limits and the default — with no filler.

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?

An output schema exists, and the description still summarizes the return shape (min/mean/max, latest, delta), so an agent has enough to call it confidently. The one gap is the relationship to nivel_rio_comparado, which an agent must infer.

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 0%, so the description must carry all parameter meaning, and it largely does: `estacion` accepts a name or an id (default Salto), `desde`/`hasta` are AAAA-MM-DD with a 92-day cap and a 14-day default. Only edge behavior (invalid station, dates beyond the limit) is left unstated.

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 resource (river height H at a Salto Grande Mixed Technical Commission station) and exactly what it returns: daily min/mean/max, latest reading and net change over the period. It is clearly distinct from siblings like nivel_rio_comparado and estaciones_cercanas, which it names as the alternative for locating a station.

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 explicit routing for one sibling: 'Para encontrar una estación cerca de un lugar, usar estaciones_cercanas.' It also implies the appropriate scope (historical window up to 92 days, default 14). It does not, however, state when to prefer this over nivel_rio_comparado, which is presumably the multi-station comparison tool.

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