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getecoback-climate-weather

taupunkt_lueften

Taupunkt der Außenluft und die Antwort auf 'darf ich jetzt lüften?'. — Dew point of the outside air and whether opening the window right now would make a basement or damp room wetter (Magnus formula, walls counted 2 °C below room temperature).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
innen_temp_cYesInnen-/Kellertemperatur in °C (Wände werden 2 °C kühler gerechnet)
aussen_temp_cYesAußentemperatur in °C
aussen_luftfeuchte_prozentYesRelative Luftfeuchte außen in % (5–100)

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries full behavioral burden. It discloses the Magnus formula and the assumption that walls are calculated 2 °C below room temperature. It does not describe the output format, but these details add meaningful transparency beyond a simple 'calculates dew point'.

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 compact and front-loaded, with the German purpose followed by the translated/expanded English version. Both parts contribute: the first states the answer to 'should I ventilate?', and the second adds the formula and wall assumption.

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 simple three-parameter calculation tool with no output schema, the description provides enough context: inputs are fully documented in the schema, and the calculation logic is stated. It does not specify the return format, but this is a minor gap.

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 100%, so the baseline is 3. The description repeats the wall temperature assumption already present in the innen_temp_c parameter description and adds no new parameter-specific meaning.

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 computes the dew point of outside air and answers whether opening a window would make a basement or damp room wetter. This specific outcome distinguishes it from sibling tools like heating load or heat wave preview.

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 a clear use case: deciding if ventilating now would worsen dampness in a basement or damp room. It does not explicitly mention alternatives or exclusions, but the context is distinct enough from siblings.

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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TDQS

A4.1/5.0
Disambiguation4/5

Each tool addresses a distinct indoor-climate or energy question: subsidy eligibility, cooling load, window sealing, device selection, heating load, heatwave outlook, running costs, guide retrieval, and dew-point ventilation. Only geraet_wahl vs btu_empfehlung could be muddled by an agent, but their descriptions explicitly layer one above the other.

Naming Consistency4/5

Tool names follow a mostly predictable lowercase underscore pattern with German domain nouns, e.g. btu_empfehlung, heizleistung_watt, taupunkt_lueften. The two ratgeber tools are verb-like (ratgeber_suche, ratgeber_lesen) rather than noun phrases, which is a minor deviation but still readable.

Tool Count5/5

Ten tools is well within the ideal range and each tool pulls its weight for a specialized climate-advice server. The set covers calculations, forecasts, content search, and content retrieval without padding.

Completeness4/5

The domain is well covered: sizing for cooling and heating, device selection, running costs, window sealing, ventilation/dew point, heatwave info, subsidies, and citable guides. A live current-weather or humidity-observation tool would round out the 'weather' side, but agents can work around that gap.

Resources