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Look up a French company for e-invoicing readiness

check_french_readiness
Read-onlyIdempotent

Look up a French company by SIREN, SIRET or name in INSEE SIRENE open data, for the 2026-2027 French e-invoicing mandate. Confirms the company exists and is active. It CANNOT confirm whether the company has registered with an approved platform — that lives only in the CAPTCHA-protected DGFiP annuaire, which has no open API — and the result says so. FREE and needs no API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA 9-digit SIREN, a 14-digit SIRET, or a company name.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond these: it explicitly states the tool cannot confirm platform registration and that the result says so, plus emphasizes it is free and keyless, which sets expectations about authentication and output limitations.

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 two sentences, front-loaded with the primary purpose and supported by a clear limitation and access note. Every sentence carries necessary information with no redundancy or filler.

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

Completeness5/5

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

For a single-parameter, read-only lookup with no output schema, the description is self-contained: it defines what the tool does, what inputs it accepts, what it confirms (existence and active status), and what it cannot confirm, including where that missing data lives. This is sufficient for an agent to decide when and how to invoke it.

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?

The input schema already provides 100% coverage of the 'query' parameter, describing it as a 9-digit SIREN, 14-digit SIRET, or company name. The description restates this but adds no new formatting constraints or usage nuances, so the baseline score of 3 is appropriate.

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 looks up a French company in INSEE SIRENE data by SIREN, SIRET, or name for the 2026-2027 e-invoicing mandate. This is a specific verb+resource combination that distinguishes it from siblings like check_vies_status (VAT status) and list_approved_platforms (platform registry).

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 states when not to use it: it cannot confirm platform registration, and directs the user to the CAPTCHA-protected DGFiP annuaire as the only source for that. It also sets context for the e-invoicing mandate and notes it needs no API key, making it a clear first-stop lookup tool.

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

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: validation (two input formats), generation, rule explanation, company readiness, VIES status, platform listing, key issuance, and upgrade link. Even the two validation tools are clearly split by input type (JSON vs XML), and the descriptions explicitly prevent confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (check_, explain_, generate_, get_, issue_, list_, validate_). The verbs are precise and the nouns clearly indicate the target, with no mixing of conventions or vague terms.

Tool Count5/5

Nine tools is well within the ideal scope for a specialized e-invoicing compliance server. Each tool serves a distinct purpose in the workflow—validate, generate, explain, check company/VIES/platform status, and manage API keys—without redundancy or bloat.

Completeness5/5

The tool surface covers the full lifecycle of e-invoicing compliance: validation (JSON and XML), generation, rule explanation, and external status checks (company, VIES, approved platforms). API key management and upgrade paths are also included. No obvious missing operations for the stated purpose.

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