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tresor4k

macalc

calculate_canada_rrq

Calculate Quebec Pension Plan (RRQ) contributions for an employee. Input gross annual earnings to receive base earnings, tier1 and tier2 contributions, and total contribution.

Instructions

Calculate Quebec Pension Plan (RRQ) contributions for employee. Returns: {gross_annual_cad, rrq_base_earnings, rrq_contribution_tier1, rrq_additional_earnings, rrq_contribution_tier2, total_rrq_contribution, ...}. See list_bundles for related 'finance-afrique-quebec' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gross_annual_cadYesGross annual earnings in CAD

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.
Behavior2/5

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

No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, permission requirements, or error handling. The calculation is implicitly safe, but the description lacks explicit behavioral context.

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 with no filler. The first sentence clearly states the tool's purpose, and the second provides a relevant reference to related tools. Every sentence adds value.

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

Completeness3/5

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

While the output fields are listed, the description does not address edge cases (e.g., input below exemption thresholds) or error scenarios. Since an output schema exists, return format is covered, but completeness is moderate.

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?

The input schema already provides a description for the single parameter (gross_annual_cad). The description adds no additional semantics beyond listing output fields, which are not parameters. With 100% schema coverage, baseline is 3.

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 Quebec Pension Plan (RRQ) contributions for an employee, specifying verb and resource. It also lists output fields, distinguishing it from other calculation tools in the extensive sibling list.

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 does not explicitly state when to use this tool versus alternatives. It only references a related bundle ('finance-afrique-quebec'), but provides no exclusion criteria or direct comparison to other tools like calculate_canada_ei.

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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