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https://fachrechner.com/api/v1/mcp

Photovoltaik Eigenverbrauch berechnen

bot_060
Read-onlyIdempotent

Berechnen Sie Ihren PV-Eigenverbrauch und die möglichen Stromkostenersparnisse Ihrer Photovoltaikanlage einfach mit diesem Rechner. Ergebnis: Eigenverbrauch [kWh/Jahr], Netzeinspeisung [kWh/Jahr], Jährliche Ersparnis [CHF/Jahr].

Input Schema

NameRequiredDescriptionDefault
regionNoDE = Deutschland/Österreich (DIN VDE, eBay.de), CH = Schweiz (NIN/SIA, eBay.ch)DE
feedin_tariffNoEinspeisevergütung [CHF/kWh], 0.01–0.5
purchase_priceNoStrompreis ab Netz [CHF/kWh], 0.05–1
pv_production_kwhNoPV-Jahresproduktion [kWh/Jahr], 1000–100000
self_consumption_rateNoEigenverbrauchsanteil [%], 5–90

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so the safety profile is covered. The description usefully discloses the return values (yearly self-consumption, grid feed-in, CHF savings), which adds value beyond annotations. It does not address defaults, unit assumptions, or the CHF-vs-DE currency mismatch visible in the schema.

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?

Two sentences, no filler: the action comes first, followed by the concrete output list. Appropriately sized for a five-parameter calculator with no output schema.

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?

There is no output schema, and the description compensates by enumerating the three returned metrics with units. Combined with the richly documented input schema and the read-only annotations, an agent has enough to invoke it correctly; only default behavior and currency semantics remain implicit.

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 100%, with titles, enums, defaults, and min/max on every property, so the baseline is 3. The description adds no parameter-level explanation (e.g. what self_consumption_rate influences), so it cannot exceed the schema's contribution.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (berechnen) and resource (PV-Eigenverbrauch, Stromkostenersparnisse) and even names the three result metrics, so the agent knows exactly what the tool produces. It cannot be distinguished from siblings, but the sibling names (bot_060 etc.) are opaque IDs that offer no differentiation opportunity.

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

Usage Guidelines3/5

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

Usage is implied by the nature of a calculator ('Berechnen Sie ... einfach mit diesem Rechner'), but there is no explicit when-to-use guidance, no prerequisites, and no reference to any alternative tool. Adequate but leaves the agent to infer the 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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