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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It discloses the calculation formula and regional applicability, which adds transparency. However, it does not describe the output format, device class details, or limitations (e.g., ceiling height assumptions), leaving gaps for a tool with no annotation support.

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 compact sentences, one in German and one in English, front-load the purpose and immediately provide the formula and scope. There is no filler or repetition, and every sentence earns its place.

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 2-parameter tool with no output schema, the description covers purpose, formula, and geographic scope. It is nearly complete but omits what the response looks like (e.g., plain text vs structured JSON) and the exact device class classification, which would be useful for a fully self-contained description.

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%, providing a baseline of 3. The description adds value by explaining the relationship between qm and sonne via the sun factor formula, and clarifies that sonne modifies the multiplier, which goes beyond the schema's simple field descriptions.

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 uses a specific verb phrase 'Empfohlene Kühlleistung (BTU) für einen Raum' and clearly states the output includes a matching device class. It poses a concrete question ('how many BTU do I need for X m²?') and distinguishes itself from sibling tools like heating (heizleistung_watt) and cost calculators (klimaanlage_stromkosten).

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 description provides clear context: it is for calculating cooling capacity in rooms, with an explicit formula (340 BTU/m² × sun factor) and geographic scope (Germany/Europe). It implicitly differentiates from siblings by focusing on cooling, but does not explicitly state when not to use it or name alternatives.

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