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

No annotations are provided, so the description must carry the behavioral disclosure burden. It communicates that this is an advisory/decision tool returning a device family, sizing, and a matching guide, and it adds an honesty expectation via 'honest physics'. However, it does not describe output format, assumptions, or possible side effects, which leaves some behavioral gaps.

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?

A single bilingual sentence packs purpose, scope, quality promise, and sibling relations efficiently. Some redundancy exists because the first clause is essentially repeated in English, and 'honest physics' is slightly vague, but the description remains economical and front-loaded.

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?

For a simple 2-parameter tool with complete schema descriptions and no output schema, the description names expected outcomes (device family, size, matching guide) and situates itself among related tools. It does not specify the exact return format or how the matching guide is provided, but this is a minor gap for a decision-layer recommendation tool.

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 documents the problem enum and the qm unit, range, and default. The description's mention of 'the right size for the room' reinforces qm's role but adds no concrete semantic detail beyond the schema. Baseline 3 is appropriate.

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 states a concrete decision task ('Which device family solves a given indoor-climate problem'), lists the specific problem categories it covers, and explicitly distinguishes it from sibling tools by calling it 'the decision layer above btu_empfehlung/heizleistung_watt'. This makes the tool's purpose clear and differentiated.

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 'decision layer above btu_empfehlung/heizleistung_watt' gives useful navigational context, implying this tool is the family-level recommendation step before detailed calculation tools. It does not explicitly state when not to use it or name alternative conditions, so it stops just short of full exclusion guidance.

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