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tresor4k

macalc

calculate_rent_increase_irl

Calculate the allowed rent increase in France using the IRL index. Provides new rent and increase amount.

Instructions

Calculate rent increase allowed by French IRL index. Returns: {new_rent_eur, increase_eur}. See list_bundles for related 'finance-france' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
current_rentYesCurrent rent EUR
old_irlYesIRL at lease start
new_irlYesLatest published IRL

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 burden. It states the calculation and return format but does not disclose behavioral traits like side effects, error handling, or assumptions. For a pure calculation tool, this is minimally adequate.

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 sentences with no unnecessary words. It efficiently states the purpose, return format, and related resources.

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?

Given the straightforward nature of the tool (3 simple number parameters, no nested objects, output schema mentioned), the description covers purpose, return format, and hints at related tools. It is complete enough for an AI to use correctly, though it could optionally explain the IRL formula.

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 has 100% coverage, with each parameter described. The tool description does not add any extra meaning beyond what is already in the schema, so it scores at the baseline.

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 rent increase using the French IRL index, with a specific verb and resource. It distinguishes itself from the many sibling calculators by specifying the French IRL context and mentioning related bundles.

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 provides clear context for when to use this tool (French IRL rent increase) and hints at related tools via 'See list_bundles'. However, it does not explicitly state when not to use it or compare to alternatives, which would merit a 5.

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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