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tresor4k

macalc

calculate_part_time

Calculate part-time work percentage and pro-rata salary. Input part-time hours and optional full-time salary to get the exact percentage and adjusted pay.

Instructions

Calculate part-time work percentage and optional pro-rata salary. Returns: {percentage, prorata_salary}. See list_bundles for related 'temps-rh' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
full_time_hoursNoFull-time weekly hours (FR default 35h)
part_time_hoursYesPart-time weekly hours
full_salaryNoFull-time salary to pro-rate (optional)

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?

No annotations are provided, so the description carries the full burden. It states the tool returns an object with {percentage, prorata_salary} and has no side effects (pure calculation). For a calculator, this is adequate, but it lacks details on potential constraints like input validation beyond schema.

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 two concise sentences, front-loaded with the main action, and includes the return format and a reference to related tools. No wasted words, making it efficient for an agent to parse.

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 tool's simplicity (pure calculator with 3 well-documented parameters) and the presence of an output schema (implied by return description), the description covers all necessary context. It is complete for an agent to understand and invoke the tool correctly.

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?

Schema description coverage is 100%, and the schema already documents all parameters well. The description adds minimal extra meaning (e.g., 'optional pro-rata salary' aligns with schema). Baseline score of 3 is appropriate since the description does not significantly enhance parameter understanding beyond the schema.

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 it calculates part-time work percentage and optional pro-rata salary, with a specific verb and resource. It distinguishes from siblings by specifying its unique function and referencing list_bundles for related calculators, which shows awareness of the tool's niche.

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 mentions 'See list_bundles for related temps-rh calculators', providing a clear pointer to explore alternative or related tools. It does not explicitly state when not to use this tool, but the context is sufficient for an agent to understand its scope.

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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