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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the calculation formula (340 BTU/m² × sun factor), the regional scope, and the output (BTU plus device class). This goes beyond a simple 'calculates BTU' and helps the agent understand internal logic, though it doesn't specify exact output formatting or error handling.

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 concise, containing only two main clauses, and is front-loaded with the core purpose. The bilingual repetition (German and English) is slightly redundant but not wasteful; it ensures clarity for a wider audience while keeping the description compact.

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 two-parameter calculation tool with no output schema and no annotations, the description is fairly complete. It explains what is returned (BTU and device class), the formula, and the target region. It doesn't describe the exact return data structure, but the simplicity of the tool makes this less critical.

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?

The input schema already covers 100% of parameters with descriptions, but the description adds the formula (340 BTU/m² × sun factor), which clarifies how 'qm' and 'sonne' are used in the calculation. This extra semantic detail enriches understanding beyond the bare schema.

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 function: recommending cooling capacity in BTU for a room, including the matching device class. It uses specific verbs ('recommended', 'how many BTU do I need') and distinct resource ('cooling capacity in BTU for a room'), which distinguishes it from sibling tools like heizleistung_watt (heating) and klimaanlage_stromkosten (costs).

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 an explicit usage scenario ('how many BTU do I need for X m²?') and specifies the target region (Germany/Europe). It doesn't name alternative tools, but the uniqueness of the cooling capacity calculation is clear enough for an agent to select this tool over its siblings.

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