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Detect company identifiers in text (free)

detect_company_identifiers
Read-only

FREE. Paste any text (email, invoice, contract, web page) and detect French/EU company identifiers: SIREN, SIRET (Luhn-checked), EU VAT numbers, LEI (ISO 17442 checksum) — each with the recommended Sirenic call and its price. Use this FIRST whenever a company appears in your workflow (supplier onboarding, payment to send, due diligence) to know exactly what to verify and what it costs. Deterministic pattern matching; the text is never stored or logged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
texteYesRaw text to scan (max 10,000 chars)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNoHow to settle the quote, present when payment_required is true.
quoteNoThe signable x402 payment requirements when payment_required is true: {x402Version, accepts[]} where each entry carries scheme, network, amount, asset and payTo (USDC and EURC options at the same numeric amount). Sign one entry and call again with `x_payment`.
resultatNoThe endpoint's JSON response when payment_required is false. Paid responses carry `source`, `disclaimer` and an Ed25519 signature; KYB, batch KYB, sanctions, intelligence and the five invoicing tools (prepare_french_invoice_file, prepare_european_invoice_file, prepare_french_einvoicing_recipient, verify_iban_bank, validate_eu_vat_number) also carry a `provenance` array — one entry per block served, with the official register, licence, version, `as_of` date and `precision_as_of` (what that date means). Codes are documented at GET /v1/provenance/registres (free).
payment_requiredYesTrue when this response is an x402 payment quote instead of data: settle one of the quote's `accepts` options and call the tool again with `x_payment`.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description usefully discloses that the tool is FREE, uses deterministic pattern matching, performs Luhn/checksum validation, returns recommended calls with prices, and never stores or logs the text. These are meaningful behavioral traits that help an agent infer cost, privacy, and reliability expectations.

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?

Three tight sentences with no wasted words. The 'FREE' hook is front-loaded, the core detection scope follows immediately, and the behavioral caveats (deterministic, no logging) are compressed into one succinct closing sentence.

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?

With a single required parameter, an output schema present, and annotations covering read-only/open-world behavior, the description supplies everything needed for correct invocation. It covers what to feed it, what it detects, what it returns, when to use it, and privacy/cost implications. No meaningful gap remains.

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?

Schema coverage is 100%, so the baseline is 3. The description adds practical input semantics by specifying acceptable text sources ('email, invoice, contract, web page'), which helps the agent decide what to pass in the 'texte' parameter beyond the schema's raw type/length constraints.

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 names a specific verb ('detect'), a concrete resource ('French/EU company identifiers'), and enumerates the exact identifier types (SIREN, SIRET, EU VAT, LEI). It also distinguishes itself from the sibling tools by adding that it returns the recommended Sirenic call and price, making its role as a detection/triage tool unmistakable.

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

Usage Guidelines4/5

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

The description gives clear usage context: 'Use this FIRST whenever a company appears in your workflow' and lists concrete scenarios (supplier onboarding, payment, due diligence). It does not explicitly name when not to use it or contrast with specific alternatives, but the priority instruction provides strong guidance.

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

A3.6/5.0
Disambiguation2/5

Several French company bundles overlap in purpose (get_french_company_file, get_french_company_kyb_file, get_french_company_intelligence, get_french_company_health_summary) and procurement/competitor tools overlap (get_french_company_public_procurement, get_eu_procurement_awards, get_company_procurement_competitors). Although descriptions try to differentiate, an agent could easily select the wrong tool when looking for a company overview or procurement history.

Naming Consistency4/5

Most tools follow a consistent get_/list_/search_ + country + entity pattern, e.g. get_french_company_profile, list_danish_company_filings, so navigation is predictable. Deviations like check_french_regulator_alerts, suggest_company_names, verify_iban_bank, and the prepare_* verbs are understandable but break the strict verb_noun pattern.

Tool Count1/5

77 tools is excessive for a single server regardless of how broad the domain is; the calibration treats 50+ as an extreme mismatch. While France is well covered and several countries appear, much of the surface is micro-endpoints (list_/get_ filing pairs per country) that could be consolidated.

Completeness3/5

France coverage is impressively complete (identity, financials, legal events, procurement, IP, risk, surveillance, invoicing), and the surveillance lifecycle has create/get/renew/stop. But European coverage is inconsistent: Germany has only insider transactions, Spain only acts, and several major jurisdictions lack accounts/officers/insolvency; an agent expecting 'European company due diligence' will hit dead ends.

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