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catnat_lookup

France natural-disaster decrees (arrêtés CatNat, Journal officiel) for 1 to 50 communes by INSEE code. For each commune: every decree with peril and event dates, and whether the 30-day window to file a home-insurance claim is still open, with the exact deadline (art. L125-2 Code des assurances, weekend and holiday extension) and days left. Official open data (Géorisques GASPAR). For insurers, brokers, loss adjusters, property managers, notaries. Price: 0.01 USDC per call (x402).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "communes": "<communes>"
    },
    "name": "catnat_lookup"
  }
}

Input Schema

NameRequiredDescriptionDefault
communesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the upstream source (Géorisques GASPAR open data), the legal basis for deadline computation (art. L125-2, weekend/holiday extension), the batching cap, and a per-call price of 0.01 USDC via x402. Gaps remain on error behavior, rate limits, and response shape limits, keeping it below 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening sentence front-loads the resource, geography, and batching limit, and the remainder layers output content, legal basis, source, audience, and pricing without redundancy. The audience enumeration and pricing sentence are somewhat expendable but still earn their place for an agent deciding whether to call.

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?

With no output schema and no annotations, the description does the heavy lifting by describing exactly what each commune record contains (decrees, peril, event dates, open/closed window, exact deadline, days left) and the cost model. Missing are input-format specifics and failure modes, which for a paid single-parameter tool would be useful before committing a call.

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 0 percent, so the description must compensate, and it does: it establishes that the single 'communes' string is INSEE codes, that between 1 and 50 may be supplied, and that results are returned per commune. The exact serialization (separator, padding) of multiple codes is still unspecified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb-and-resource pair: retrieving French natural-disaster decrees (arrêtés CatNat) per commune by INSEE code, with per-decree peril, event dates, and claim-deadline status. It is unmistakably a lookup tool. It does not, however, explicitly differentiate itself from the sibling catnat_example, so it falls short of a 5.

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

Usage Guidelines3/5

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

The intended audience (insurers, brokers, loss adjusters, property managers, notaries) and the 1-to-50 commune limit imply when the tool fits, but there is no explicit when-to-use/when-not-to-use statement or pointer to the sibling tool for sample data. Usage is inferable rather than stated.

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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