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tresor4k

macalc

calculate_housing_aid

Estimate French housing aid (APL) by providing monthly rent, city zone, and household size. Get the potential aid amount and applicable rent ceiling.

Instructions

Estimate French housing aid (APL — Aide Personnalisee au Logement). Returns: {rent, rent_ceiling, estimated_apl, note}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rentYesMonthly rent in euros
city_zoneNoCity zone: 1 (Paris/IDF), 2 (large cities), 3 (rural)2
household_sizeNoNumber of people in household (1-6)

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?

With no annotations, the description must disclose behavior but only states that it estimates and returns values. It does not mention side effects, data sources, update frequency, or limitations like approximation accuracy.

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 extremely concise: one sentence plus a return signature. Every word is necessary, with no redundant or misleading information.

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?

The description covers the basic purpose and output, but given the complexity of APL calculation (e.g., region-specific rules), it lacks important context such as the year of the formula or assumptions used. The presence of an output schema reduces some burden, but the description could be more informative.

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%, so the parameters are already well-documented. The tool description adds no additional meaning beyond the schema, maintaining a baseline score of 3.

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 estimates French housing aid (APL) and lists the return fields, making the purpose specific and unambiguous. However, it does not explicitly differentiate from sibling tools that may also relate to housing calculations.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives, such as other housing-related calculators or general estimation tools. The description lacks context for selection.

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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