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Roof figures for a district or town

area_figures
Read-onlyIdempotent

What our own solar roof check found over the family houses of a München district or of a town with a subsidy page: the typical house (modules, kWp, kWh a year), how many houses have room for a good system, the share of the household's power that comes from its own roof without and with a 5 or 10 kWh battery, the shade loss, and the area's own finding (what stands out against the rest of München). Totals and middle values over a sample of the area's houses, never a single house or address. With the link to the area's page. For a particular roof use find_house and plan_roof.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "place": "<place>"
    },
    "name": "area_figures"
  }
}

Input Schema

NameRequiredDescriptionDefault
placeYesA München district (Stadtbezirk, e.g. "Pasing-Obermenzing", "Trudering", "Solln"; also its number or a neighbourhood in it) or a town with a subsidy page (e.g. "Pullach", "Garching"). Not found: the answer lists what is available.
localeNoLanguage of the answer: de (German) or en (English).de

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

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, non-destructive and closed-world, so the safety profile is covered. The description nonetheless adds real behavioral context no annotation carries: results are aggregated and sampled, not per-address, and the response includes a link to the area's page. It stops short of explaining sample sizes or how the 'area's own finding' is derived.

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?

A single dense, front-loaded sentence listing the payload, followed by a short scoping clause and an alternative-route clause. No filler, but the opening 'What our own solar roof check found over the family houses of...' buries the resource behind framing words.

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?

There is no output schema, so the description must carry the return-value burden — and it does, listing every reported metric plus the page link. Combined with the scoping constraint and the sibling pointer, an agent has everything needed to call it correctly.

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%, and the schema already documents both `place` (district, number, neighbourhood, or town with subsidy page, with not-found behavior) and `locale`. The description adds no format or constraint detail beyond that, so the baseline 3 applies.

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?

Names a specific resource (aggregate roof figures) and enumerates exactly what it returns: typical house modules/kWp/kWh per year, share of houses with room for a good system, self-consumption share with and without a 5 or 10 kWh battery, shade loss, and the area finding. The scoping phrase 'Totals and middle values over a sample of the area's houses, never a single house or address' separates it cleanly from the single-roof siblings.

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?

States the eligible inputs (a München district or a town with a subsidy page) and routes the agent explicitly: 'For a particular roof use find_house and plan_roof.' The exclusion of single houses/addresses is stated, so the agent knows when this tool is the wrong choice.

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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