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

Annotations already declare readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds that the result is a wattage figure, but says nothing about assumptions (heater sizing margin, temperature delta) or limits.

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?

Three tight sentences, front-loaded with the computation and result, with no wasted prose. The trailing bundle reference is minor and optional rather than distracting.

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?

With a full output schema the return value need not be explained, and the description still names the returned unit (W). For a small pure-calculation tool this is essentially complete, though assumptions behind the formula are unstated.

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%, so all three parameters (volume_liters, room_temp_c, target_temp_c) are already documented with units. The description merely restates them as 'tank L, current temp, target temp' with no added semantics, so the baseline 3 applies.

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?

States a specific verb and resource ('Compute aquarium heater wattage') plus the driving inputs, which cleanly distinguishes it from near siblings like calculate_aquarium_volume and calculate_water_heater_size.

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?

'Use for aquarium setup' gives an implied context but no conditions, prerequisites, or explicit when-not guidance. The pointer to list_bundles is a mild routing aid rather than genuine alternative selection.

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