calculate_pue

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

No annotations are provided, so the description must disclose behavior. It discloses the return values (PUE score, efficiency rating, annual cost estimate, engineering recommendations), which is helpful. However, it does not state that the tool is read-only, nor does it describe assumptions, error handling, or limitations. The behavioral disclosure is partial.

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 a single, concise sentence that front-loads the purpose and includes a brief list of outputs. There is no redundant or unnecessary language, and every phrase adds value.

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?

Since there is no output schema, the description correctly lists the return items. It covers the inputs via schema and outputs via description, which is sufficient for a straightforward calculation tool. It could elaborate on the meaning of 'efficiency rating' or 'annual cost estimate', but that is not essential for correct invocation.

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 provides 100% coverage for all four parameters with examples, so the description does not need to add parameter-level detail. The description adds no semantics beyond the schema, which aligns with the baseline of 3 for high schema coverage.

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 specific action ('Calculate') and a specific resource ('Power Usage Effectiveness (PUE) for a data centre or server room'), and explicitly lists outputs (PUE score, efficiency rating, annual cost estimate, engineering recommendations). This clearly distinguishes the tool from siblings like 'calculate_carbon' or 'estimate_cooling_load'.

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 clearly identifies the context for use ('data centre or server room') but does not explicitly mention when to avoid using it or provide alternative tool suggestions. It gives a clear usage context without exclusion criteria, matching the 'clear context, no exclusions' level.

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