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

With no annotations available, the description carries the full burden. It discloses the use of the Magnus formula and the key assumption that walls are counted 2 °C below room temperature. This gives the user insight into the calculation method. It does not specify output format or edge cases, but the description implies a recommendation (yes/no) which is adequate for a simple calculation tool.

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, with two sentences, and front-loads the core purpose. The bilingual repetition adds a little redundancy but does not significantly inflate length. No unnecessary filler is present.

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?

The tool is simple with only three inputs and no output schema. The description explains the exact scenario (damp room/basement ventilation) and the calculation assumption. It adequately covers what the user needs to know, though it could optionally mention the output type (e.g., 'yes/no recommendation') more explicitly.

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?

All three parameters are fully described in the schema (100% coverage). The description adds context about the formula and wall assumption, but this is mostly restating what is already in the schema (e.g., walls counted 2 °C cooler). Since schema coverage is high, the baseline of 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 clearly states the tool's function: it computes the dew point of outside air and answers whether opening a window would make a basement or damp room wetter. It uses specific terminology (dew point, Magnus formula) and distinguishes itself from sibling tools like BTU calculations or window sealing by focusing on ventilation decisions.

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: this is for deciding whether to ventilate a basement or damp room based on outdoor conditions. It implies when to use it, but does not explicitly mention when not to use it or compare with alternatives. Since the sibling tools are all different domains (heating, sealing, etc.), the context is sufficient to avoid confusion.

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