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Elbe water level at Hamburg St. Pauli and Cuxhaven (PEGELONLINE)

get_marine_hydro_context
Read-only

Free. Current Elbe water level in cm at the gauges Hamburg St. Pauli and Cuxhaven from PEGELONLINE (WSV open data), with the trend and level class as published by WSV and water temperature where the station measures it. Not a tide forecast and not a flood warning; a station with ok=false had no reading. Refreshed every 5 minutes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_marine_hydro_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
stationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, it discloses the data freshness cadence (refreshed every 5 minutes), the source authority, the returned fields (trend, level class, water temperature where measured), and the failure semantics ('a station with ok=false had no reading'). That is exactly the context annotations cannot carry.

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 dense sentences, front-loaded with the core purpose, then caveats, then freshness. The leading 'Free.' is marketing filler, but everything else carries substantive information for a reader deciding whether to call it.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read-only tool with no output schema, the description covers source, units, returned fields, staleness, and failure behavior. An agent has everything needed to call it correctly and to interpret an empty or missing reading.

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 0%, but the single parameter is an enum whose values are largely self-explanatory. The description maps the gauges to real place names, aiding interpretation of 'st_pauli' and 'cuxhaven', but it never mentions the 'all' option or what omitting the parameter does.

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 (current Elbe water level in cm) at named gauges (Hamburg St. Pauli, Cuxhaven) with a named source (PEGELONLINE/WSV). No sibling tool covers hydrology, so the scope is unambiguous without needing to name a competitor.

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 clear negative guidance that matters for interpretation: 'Not a tide forecast and not a flood warning,' which steers an agent away from misusing it for prediction or alerting. It does not name an alternative tool for forecasts or warnings, so it falls short of a full when/when-not routing statement.

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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