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

Annotations already declare the full safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description restates return granularity (daily/monthly/yearly cost) which is also available via the output schema, adding little behavioral context beyond the structured fields.

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?

Compact and front-loaded: purpose, usage, inputs, returns, and a cross-reference in short sentences with no filler. The redundant returns sentence is the only mild waste given the output schema exists.

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 input schema, an output schema covering return values, and annotations covering safety, the description only needs to convey purpose and usage, which it does. Adequate for a simple single-purpose calculator.

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 the schema already documents every parameter. The description mirrors the fields ('power W, daily usage hours, kWh price') but adds no formatting, unit, or default semantics beyond what the schema provides, matching the baseline.

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 electricity cost for an appliance'), which is unambiguous. It does not distinguish itself from close siblings like calculate_electricity_cost_appliance, calculate_led_savings, or calculate_ev_charging_cost, so an agent must infer the boundary.

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 energy budgeting' gives an implied context but no explicit when-to-use vs alternatives or any exclusions. The pointer to list_bundles is navigation, not selection guidance against sibling calculators.

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