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

With no annotations provided, the description takes full responsibility. It transparently discloses the calculation formula (340 BTU/m² × sun factor), the sun factor's role, and the geographic scope (Germany/Europe). It also mentions the 'matching device class' output. It does not describe response format or edge cases, but for a simple calculator this is sufficient behavioral disclosure.

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?

The description is two concise lines (bilingual), front-loaded with the primary purpose. Every clause adds value: formula, region, and device class. No filler or redundant repetition of schema details. Very efficient.

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 calculator with two parameters and no output schema, the description covers all essential context: what the tool computes, the formula, the unit, the geographic applicability, and the output class. It is complete enough for an agent to select and invoke it correctly without missing critical information.

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%, giving baseline 3. The description adds extra value by explaining the 'sun factor' concept linked to the 'sonne' parameter and explicitly mapping 'qm' to the 'X m²' in the formula. This goes beyond the schema's simple field names and descriptions, enriching semantic understanding.

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 clearly states the tool's purpose: 'Empfohlene Kühlleistung (BTU) für einen Raum' (recommended cooling capacity in BTU for a room) and "with the matching device class". It uses specific verbs and resources, and distinguishes it from sibling tools like heizleistung_watt (heating) and taupunkt_lueften (dew point). The question 'how many BTU do I need for X m²?' makes the use case explicit.

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 gives context on when to use the tool: for rooms in Germany/Europe, with the formula and sun factor. It implies it's the cooling counterpart to heating tools. However, it does not explicitly name alternatives or exclusions like 'use heizleistung_watt for heating', so it lacks the explicit when-not guidance for a perfect 5.

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