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tresor4k

macalc

calculate_electricity_cost_appliance

Compute annual electricity cost and CO2 emissions of a household appliance. Input power in watts, daily usage hours, and kWh price to evaluate energy expenses and support replacement decisions.

Instructions

Compute annual electricity cost of a household appliance. Use for energy audit and replacement decisions. Inputs: power W, daily hours, kWh price. Returns annual cost and CO₂ kg. See list_bundles for related 'energie' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
power_wYesPower in watts
hours_dayYesHours used per day
price_kwhNoEUR per kWh

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior4/5

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

No annotations are provided, so the description carries the burden. It states: 'Returns annual cost and CO₂ kg.' This discloses the outputs. The tool appears to be a simple compute with no side effects. Transparency is good but could mention any constraints (e.g., validation of inputs).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with purpose, then inputs, outputs, and a reference to related tools. No unnecessary words, very efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple calculator tool with an output schema, the description covers purpose, usage, inputs, outputs, and references related tools. It is mostly complete, though it could specify the unit for CO₂ (kg) more clearly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% description coverage. The description lists inputs: 'power W, daily hours, kWh price.' This repeats schema info without adding new semantics. Baseline 3 is appropriate since schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states: 'Compute annual electricity cost of a household appliance.' It specifies the verb (compute) and resource (cost of appliance), and distinguishes from sibling 'calculate_electricity_cost' by focusing on specifically an appliance. It also mentions 'energy audit and replacement decisions' as context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says: 'Use for energy audit and replacement decisions.' This explicitly tells when to use. It also points to 'list_bundles for related 'energie' calculators' as alternatives. However, it does not explicitly state when NOT to use the tool.

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

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