Skip to main content
Glama
manganate006

OpenLMNP

Compute Tva

compute_tva
Read-only

Compute the French TVA return for serviced rental properties liable to VAT for a chosen year. Get collected and deductible VAT, with balance due or refundable, per property, rate, and quarter.

Instructions

Calcule la déclaration de TVA pour les biens para-hôteliers assujettis (régime TVA liable) sur une année donnée. Retourne la TVA collectée, déductible et le solde à payer ou à récupérer, ventilés par bien, par taux et par trimestre. Tous les montants sont en euros.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint annotation already indicates this is a read-only operation, so the description adds value by detailing what is returned (TVA collectée, déductible, solde) and the aggregation dimensions (bien, taux, trimestre). This goes beyond the annotation and clarifies the calculation scope, though it does not mention error handling or prerequisites.

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 exceptionally concise: two sentences that front-load the main verb and purpose, then detail outputs. No redundant information or filler. Every phrase adds meaning, from the target population to the currency.

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 tool has only one parameter and no output schema, the description adequately covers the return value structure and scope. It explains the outputs and their segmentation, which is sufficient for an agent to understand what the tool provides. It misses only minor details like data source dependencies (existing properties, fiscal year definitions), but these are not critical for effective invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only defines 'year' as an integer with no description (0% coverage), so the description must compensate. It does so by stating 'sur une année donnée' (for a given year), directly clarifying the parameter's meaning. However, it does not specify constraints like valid year range or format beyond the implicit integer type, leaving some ambiguity for edge cases.

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 a specific verb ('Calcule' / calculates) and resource (VAT declaration for taxable para-hotel properties) along with the output composition (collected VAT, deductible VAT, balance) and breakdown (by property, rate, quarter). This distinguishes it from sibling tools like compute_depreciation or generate_tax_return, which address different financial scopes.

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 usage by specifying the context (para-hotel properties, taxable regime, given year) but does not explicitly contrast with alternatives such as generate_tax_return or compute_fiscal_year. There is no 'when-not-to-use' or mention of sibling tools, leaving the agent to infer applicability rather than receiving explicit selection guidance.

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