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

There are no annotations, so the description carries the full burden. It discloses that the tool combines physical reasoning ('honest physics'), room sizing, and a guide selection, and indicates it is a decision/recommendation layer rather than a precise calculator. It does not detail the exact output shape, but for a non-mutating selector this is adequate.

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

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

Two sentences carry the core purpose, inputs, output style, and sibling-tool hierarchy with no filler. The German/English pairing also aids multilingual agent parsing without bloating the text.

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

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

Given only two parameters, no output schema, and no annotations, the description is nearly complete: it explains the tool's role, its problem domain, and its output (device family plus matching guide). It could be more explicit about edge-case behavior, but the core information an agent needs to invoke it correctly is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains both 'qm' and 'problem' with enums and units. The description reinforces the mapping by mentioning the problem categories and room size, but adds no parameter-level semantics beyond what the schema provides.

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

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

The description opens with a concrete selection question and names the resource: 'device family' for an indoor-climate problem. It lists the problem categories and positions itself as 'the decision layer above btu_empfehlung/heizleistung_watt', which clearly distinguishes it from the closest sibling tools.

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

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

The phrase 'The decision layer above btu_empfehlung/heizleistung_watt' gives clear contextual guidance: use this tool first to choose a device family, then use the sizing tools. It does not explicitly enumerate when-not-to-use conditions or alternatives like ratgeber_suche, but the hierarchy provides solid routing context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.