Distil — Machine-Native Public Data Refinery

Search France Enterprises

search_fr_companies

Read-onlyIdempotent

Searches French enterprises across the INPI / SIRENE National Enterprise Register by corporate name or commercial trade label.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of French companies to return (default 5, max 20).
`query`	Yes	French company name, commercial trade name, or SIREN number.
`forceFresh`	No	Spend Control: When true, bypasses Edge KV cache and forces a real-time statutory primary registry call (applies 2.5x Freshness Inconvenience Surcharge). Default: false.
`maxAgeHours`	No	Spend Control: Maximum acceptable data age in hours (e.g. 48 for 2 days tolerance). If cache satisfies this, delivers sub-5ms at standard 1.0x Economy rate. Set to 0 to force live primary fetch.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`content`	Yes
`isError`	No

TDQS

A4.1/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds registry-scope context (INPI / SIRENE), but does not disclose additional behavioral aspects such as caching, freshness behavior, latency, or return characteristics; those are largely delegated to parameter descriptions and the output schema.

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?

A single, front-loaded sentence states the action, target, registry, and searchable fields without redundancy. Every phrase contributes to understanding what the tool does.

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 read-only search tool with a rich input schema, comprehensive annotations, and an output schema, this description is complete enough. The registry scope and query intent are clear, and all parameter semantics, spend-control behavior, and safety traits are available in the structured fields.

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 description coverage is 100%, so all four parameters are already documented. The description reinforces that query is for company name or trade label, but adds no meaning beyond the schema for limit, forceFresh, or maxAgeHours.

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 the specific verb ('Searches'), resource ('French enterprises'), and authoritative data source ('INPI / SIRENE National Enterprise Register'), and specifies search mode ('by corporate name or commercial trade label'). This clearly distinguishes it from country-specific siblings like search_uk_companies and search_us_companies.

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 makes its intended use clear: querying French corporate entities by name or trade label. It does not explicitly state when not to use it or name alternative tools for other countries, though the sibling list and country scope make the context obvious.

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

A4/5.0

Disambiguation5/5

Each tool maps to a distinct data product: country-specific filings, tender records/search, risk scoring, sanctions screening, and entity graphs. The search/get split cleanly separates discovery from retrieval, and even similar country-specific tools are clearly qualified by region and entity type.

Naming Consistency5/5

All tools use a consistent snake_case verb_noun pattern: get_* for retrieval and search_* for discovery, with country or region qualifiers where applicable. Cross-cutting tools like get_corporate_risk_score and get_tender_intelligence fit the same pattern without feeling out of place.

Tool Count4/5

At 16 tools, the server is slightly above the ideal 3-15 range, but the multi-country, multi-domain scope justifies nearly every tool. The set is heavier than a tightly focused server, yet no tool feels redundant.

Completeness4/5

The set covers the core read-only workflow well: search to find entities or tenders, get to retrieve records, plus analytical tools for risk, sanctions, and tender intelligence. Minor gaps exist, such as no Spanish company registry access and no UK tender search, but these are workable and do not block primary due-diligence workflows.

Resources

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