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Glama

fiscal_tmi

Taux marginal d'imposition (TMI) — Tranche marginale d'imposition du foyer au barème 2026, en tenant compte du plafonnement du quotient familial. Renvoie le taux en POINTS DE POURCENTAGE (unit PERCENT, ex. 30 = 30 %) — à distinguer de prelevements_sociaux qui renvoie une fraction (unit RATE, 0-1). (sources: CGI art. 197 ; BOFiP BOI-IR-LIQ-20)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
partsNoNombre de parts de quotient familial.
situationNoSituation familiale.Célibataire
revenu_net_imposableYesRevenu net imposable du foyer (€).

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It clearly discloses the output unit behavior, the use of the 2026 scale, and the inclusion of the quotient familial cap. It does not describe potential error conditions or the exact response structure, but the most important behavioral nuances are present.

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 compact, front-loads the acronym and core concept, and then provides the essential unit distinction and legal sources. Every sentence adds value, with no filler or redundancy.

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?

The tool has no output schema and no annotations, so the description must explain the return format and calculation scope, which it does well. It states the percentage-point unit and the legal basis. It slightly under-specifies whether the result is a bare number or a structured value, but an agent can invoke the tool correctly with the schema.

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 does not add new meaning to the parameters themselves; it only clarifies the output unit and tax context. The schema already describes 'revenu_net_imposable' as household net income, and 'parts' and 'situation' are self-explanatory with their descriptions.

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 returns the household's marginal tax rate (TMI) under the 2026 French tax scale, including the quotient familial cap. It uses a specific verb ('Renvoie') and a specific resource, and it explicitly distinguishes itself from fiscal_prelevements_sociaux by unit, so an agent can tell them apart.

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

Usage Guidelines5/5

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

The description gives an explicit when-not by naming the alternative fiscal_prelevements_sociaux and contrasting units: this tool returns percentage points (PERCENT), the other returns a fraction (RATE). It also implicitly states when to use it: whenever a marginal tax rate in percentage points is needed.

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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TDQS

A3.7/5.0
Disambiguation4/5

The tool families are clearly separated by domain prefixes (fiscal, retraite, referentiel), and the descriptions proactively distinguish near-neighbors such as fiscal_tmi vs fiscal_prelevements_sociaux and retraite_estimation vs retraite_pension_totale. Some initial confusion is possible between retraite_pension_regime and retraite_regimes, but the descriptions are detailed enough to resolve it.

Naming Consistency4/5

Most tools follow a predictable snake_case domain_object pattern: fiscal_*, retraite_*, referentiel_*. The clear outlier is qotien_capacites, which uses a misspelled, non-domain prefix and breaks the otherwise consistent naming scheme.

Tool Count3/5

With 18 tools, the server is heavier than the typical 3-15 sweet spot, though it is organized into recognizable fiscal, retirement, and referential clusters. The count is defensible for a two-domain server, but it begins to feel like a large MCP surface that agents must navigate carefully.

Completeness4/5

The server covers the main French income-tax and retirement calculation needs: income tax, marginal rate, social levies, CEHR, property capital-gains surtax, pension estimation, multi-regime totals, net pension, buybacks, progressive retirement, and parental surcharge. Minor gaps exist—such as no explicit long-career early-retirement tool and pensions_fournies being referenced rather than exposed as a first-class tool—but agents can work around them.

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