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malkreide

swiss-environment-mcp

by malkreide

env_hydro_history

Read-onlyIdempotent

Retrieves historical hourly water level, discharge, and temperature data from BAFU hydrometric stations for trend analysis and extreme event research over up to 30 days.

Instructions

Ruft historische Stundenwerte einer BAFU-Hydromesstations ab.

Ermöglicht zeitliche Analysen von Wasserstand, Abfluss und Temperatur über bis zu 30 Tage. Ideal für Trendanalysen und Extremereignis-Recherche.

Aktuellsten Messwert einer Station holen und den Zugang zu echten historischen Zeitreihen (Tages-/Langzeitmittel) aufzeigen. LINDAS liefert nur den aktuellen Wert (keine Zeitreihe). Historische Tages-/Langzeitmittel sind NICHT frei per API verfügbar und müssen bei der BAFU-Abfragezentrale bezogen werden.

Args: params (HydroHistoryInput): - station_id: BAFU-Stationsnummer - parameter: 'Abfluss', 'Pegel' oder 'Temperatur' (Kontext) - days: Anzahl Tage (Kontext)

Returns: str: Aktuellster Messwert (LINDAS) + Bezugsweg für historische Reihen.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that it returns the current value and a reference path for historical series, and explains limitations about daily averages. This complements the annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat verbose, with an args list that largely duplicates schema information. It has good structure with sections, but could be more concise by removing redundant parameter details.

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?

For a read-only tool with simple output, the description covers the core behavior, limitations (no daily averages), data source (LINDAS), and a reference path. It lacks examples or error info, but is otherwise complete given annotations and simple output.

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% for the top-level parameter, but the description lists station_id, parameter, and days with brief context (e.g., 'Kontext'). It adds value by clarifying the use context, though it mostly repeats schema descriptions. The important notes also add parameter-related guidance.

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 it retrieves historical hourly values for a BAFU hydrometric station, specifying water level, flow, and temperature over up to 30 days. It distinguishes from siblings like env_hydro_current (current values) and env_hydro_stations (station list) by focusing on historical time series.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The <use_case> and <important_notes> explicitly guide when to use: for fetching the current value and pointing to historical daily/long-term series, and notes that daily averages are not available via API, requiring contacting BAFU. This provides clear when-to-use and when-not-to-use context.

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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