Skip to main content
Glama

simuler_impots

Calculate French income tax for 2025/2026 based on family situation, income type, deductions, and children. Handles quotient familial and décote.

Instructions

Simule l'impôt sur le revenu français selon le barème 2025/2026. Prend en compte la situation familiale, le quotient familial, l'abattement selon le type de revenu, et la décote.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
revenuBrutAnnuelYesRevenu brut annuel en euros
typeRevenuYesType de revenu (salaire, BNC profession libérale, BIC services, BIC commerce, foncier micro-foncier, autre)
situationFamilialeYesSituation familiale
enfantsNoNombre d'enfants à charge
enfantsEnGardeAlterneeNoNombre d'enfants en garde alternée
chargesDeductiblesNoCharges déductibles annuelles (pension alimentaire, PER, etc.)
anneeRevenusNoAnnée des revenus (2024 ou 2025, défaut=2024)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions using the tax bracket and several factors but fails to state limitations, assumptions, return format (e.g., a single tax amount or breakdown), or whether the simulation is simplified. This leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description consists of two concise sentences, with the main action in the first sentence and supporting detail in the second. It is front-loaded and efficient, though a more structured format (e.g., bullets) could improve scanability.

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

Completeness2/5

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

Given 7 parameters, no output schema, and no annotations, the description should offer more completeness. It lacks information about return values (e.g., estimated tax amount vs. marginal rate), prerequisites (e.g., need for revenu net), and accuracy or constraints. The agent lacks enough context to fully trust or interpret the output.

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 coverage is 100%, so the baseline is 3. The description adds context by linking parameters to tax concepts (e.g., children affect quotient familial), but does not deepen semantic meaning beyond the schema's own descriptions. It is adequate but not exceptional.

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 the tool simulates French income tax using the 2025/2026 tax bracket. It specifies the key factors considered (family situation, quotient familial, deduction, discount), making it distinct from sibling tools like simuler_aides_logement or simuler_chomage.

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 implies use for French income tax estimation but does not explicitly provide when to use versus alternatives like other simulation tools. No recommendations or exclusion criteria are stated, leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mcp-tools-lab/french-admin-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server