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nordic-data

by io.github.Mnymann

fr_history

Read-onlyIdempotent

French company history timeline. Returns one event per change to the company's name, activity (NAF code), status (active/closed), legal form, or social-economy flag, derived from INSEE Sirene 3.11's bitemporal periodesUniteLegale array. Includes 'initial:' events that show the state at company creation (date, name, NAF code, etc.). Input: 9-digit SIREN number. Cost: 1 quota unit; free tier supported (France is not tier-gated, unlike NL and DE). Cache: 24h server-side. Errors: 400 invalid_id_format (not 9 digits), 403 non_diffusible (SIREN exists but is privacy-protected under art. R123-232-1), 404 not_found, 503 upstream_unavailable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sirenYes9-digit French SIREN number. Examples: 652014051 (Carrefour), 775670417 (LVMH). No spaces or punctuation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of history events derived.
sigleNoAcronym / short name, if any.
sirenNo9-digit SIREN echoed back.
eventsNoChronologically ordered events. Each event has 'initial:<field>' type for the baseline period or a plain field name for subsequent changes.
sourceNoUpstream data source — 'api.insee.fr'.
fetchedAtNoISO-8601 timestamp when the data was fetched upstream.
sourceNoteNoProvenance note describing the upstream API and field set used.
periodCountNoNumber of bitemporal periods returned by INSEE.
dateCreationNoISO-8601 date the legal entity was created.
categorieEntrepriseNoINSEE company size category: PME, ETI, GE.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent, non-destructive), the description richly discloses behavior: source data (INSEE Sirene 3.11), bitemporal nature, event structure including 'initial:<field>' events, cost, cache duration, and detailed error codes. This is far more than baseline and helps the agent anticipate outcomes.

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 but information-dense, using four sentences to cover purpose, output structure, input, cost, cache, and errors. It is front-loaded with the main purpose and every sentence contributes practical information without redundancy.

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 an output schema present, return values are already specified, and the description fills in additional operational context: source data, event semantics, cost, cache, and error handling. Given the tool's single parameter and safe read-only nature, the description is complete for an agent to invoke it correctly.

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% and the schema description already explains the SIREN parameter with examples. The tool description merely restates 'Input: 9-digit SIREN number,' adding no semantic value beyond the schema, so the baseline 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 'French company history timeline' and explains it returns one event per change to name, activity, status, legal form, or social-economy flag. This is specific and distinct from sibling tools like lookup_company or company_enriched, which typically return current or enriched snapshot data rather than a chronological event list.

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 provides clear context: it is for French companies, uses a SIREN number, has specific quota/caching behavior, and lists error scenarios. However, it does not explicitly name alternative tools or state when not to use this tool, though the France-specific nature and timeline focus imply appropriate use.

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

A4.3/5.0
Disambiguation5/5

Each tool targets a clearly distinct function: address autocomplete, company lookup, enriched company data, KYB report, LEI lookup, sanctions screening, VAT validation, French history, and three discovery meta-tools. The discovery tools (list_endpoints, get_endpoint_schema, call_endpoint) form a clean trio with distinct roles. There is minor overlap between company_enriched, kyb_full, and lookup_company, but their scopes are well-differentiated in the descriptions.

Naming Consistency4/5

The naming pattern is largely consistent with noun-based descriptive names (company_enriched, lookup_company, lookup_lei, validate_vat, screen_sanctions, autocomplete_address). Three discovery tools use verb-based names (list_endpoints, get_endpoint_schema, call_endpoint), and fr_history breaks the pattern as a country-specific tool. Minor inconsistency but readable and predictable overall.

Tool Count4/5

11 tools is within a reasonable range for a data-provider server that covers 15 countries and multiple data domains (entities, sanctions, VAT, addresses, LEI). Each tool addresses a distinct need. Slightly heavy given some overlap, but the count is justified by the breadth of coverage.

Completeness4/5

The core business-intelligence surface is well covered: company lookup, enriched data, full KYB, LEI, sanctions, VAT, address autocomplete, and French history. The discovery meta-tools (list_endpoints, get_endpoint_schema, call_endpoint) elegantly bridge gaps by exposing 230+ additional endpoints. Minor gaps: no dedicated UK-specific or non-French history tool, and screening is limited to sanctions/PEP without a dedicated adverse-media tool separate from kyb_full.

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