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Calculer le numero de TVA intracommunautaire francais

fr_vat_compute

Calculate a French intra-community VAT number from a SIREN or SIRET, with automatic Luhn key validation. Works locally without network calls.

Instructions

Calcule le numero de TVA intracommunautaire francais (FR + cle a 2 chiffres + SIREN) a partir d'un SIREN ou d'un SIRET, et controle la cle de Luhn. Calcul local instantane, aucun appel reseau. A utiliser avant eu_vat_validate quand on ne connait que le SIREN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sirenYesSIREN (9 chiffres) ou SIRET (14 chiffres). Espaces et points acceptes.
response_formatNoFormat de sortie. 'markdown' pour lecture humaine, 'json' pour traitement programmatique.markdown
Behavior4/5

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

No annotations are provided, so the description carries full burden. It effectively discloses that the computation is local and instantaneous with no network dependency. However, it does not mention error handling or validation behavior for invalid inputs.

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 concise: two sentences that cover the core functionality and usage context. No redundant information.

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 description is adequate for a simple computation tool. It covers purpose, usage, and behavioral traits. It could benefit from mentioning error handling or the expected return value, but overall it provides sufficient context given the lack of output 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 baseline is 3. The description does not add additional meaning beyond what the schema already provides for the two parameters (siren and response_format). The schema already includes descriptions and defaults.

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 computes the French intra-community VAT number from a SIREN/SIRET, validating the Luhn key. It specifies the output format (FR + 2-digit key + SIREN) and distinguishes from sibling tool eu_vat_validate by stating it should be used before when only the SIREN is known.

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 explicitly says when to use: before eu_vat_validate when only the SIREN is known. It also notes it's a local instant computation with no network call, providing clear context for tool 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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