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tresor4k

macalc

calculate_overtime_fr

Compute French overtime pay (heures supplémentaires) per labor code. Input hourly rate, base hours (default 35), and actual hours to get gross overtime with 25%/50% premiums. For HR or employee verification.

Instructions

Compute French overtime pay (heures supplémentaires) per labor code. Use for HR or employee verification. Inputs: hourly rate, normal hours, overtime hours. Returns gross overtime pay with 25%/50% premiums. See list_bundles for related 'finance-france' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_hoursNoBase weekly hours
actual_hoursYesActual weekly hours
hourly_rateYesHourly rate EUR

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.
Behavior3/5

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

With no annotations, the description partially fulfills the burden by stating it returns gross overtime pay with 25%/50% premiums. It does not disclose other potential behaviors like rounding, edge cases, or limitations, but it 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.

Conciseness5/5

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

The description is three sentences, front-loaded with purpose, and contains no extraneous information. Every sentence is meaningful and efficient.

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

Completeness5/5

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

Given the presence of an output schema and full parameter coverage, the description provides sufficient context: purpose, usage, inputs, output structure, and a reference to related tools. It is complete for the tool's complexity.

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

Parameters4/5

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

The schema covers 100% of parameters with descriptions. The description adds value by clarifying that 'normal hours' (base_hours) and 'overtime hours' (inferred from actual_hours) are used, which aids understanding beyond the schema.

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

Purpose4/5

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

The description clearly states the tool computes French overtime pay, which is a specific verb+resource. However, it does not differentiate from the sibling 'calculate_overtime_pay_fr', which appears to have a similar purpose.

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

Usage Guidelines3/5

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

The description suggests use for HR or employee verification, providing context. However, it does not offer explicit guidance on when not to use this tool or mention alternatives, such as the similar sibling 'calculate_overtime_pay_fr'.

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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