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scan_website

Read-onlyIdempotent

Scan a live website against French consumer and e-commerce law (16 checks) and return findings with excerpts and legal references.

The robot reads up to 20 public pages (home, legal notice, terms of sale, returns, product pages), respects robots.txt,
never bypasses a firewall and does not run JavaScript. Usually takes 20 to 90 seconds; if it is still running after
100 seconds you get a scan_id to pass to get_scan_result. A human-readable report stays online for 30 days at report_url.

Args:
    url: the site or shop to scan (domain or full URL; a product page URL is also read).
    sector: "vente-en-ligne" (online shop), "immobilier" (estate agency) or "entreprise" (other business site).
        Guessed from the site when omitted; it selects the list of rules a human must check.
    lang: language of the findings, "fr" or "en".
    fresh: the same site scanned in the last 30 minutes is reused; set true to read it again after a fix.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
langNofr
freshNo
sectorNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations: up to 20 public pages read, robots.txt respected, no firewall bypass, no JavaScript execution, 20-90 second runtime, 100-second timeout yielding a scan_id, and a 30-day report_url. This is exactly the operational context an agent needs and is not derivable from the readOnly/openWorld hints.

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?

Front-loaded with purpose, then runtime/async behavior, then a clearly delimited Args block. Every sentence carries distinct information with no 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?

Covers the async handoff (scan_id -> get_scan_result), report availability, and all inputs. With no output schema, the description still tells the agent what comes back (findings with excerpts and legal references), so nothing material is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the prose documents all four parameters with meaning beyond the schema: url accepts domain or full URL including a product page, sector enumerates three values and is guessed when omitted, lang selects finding language, and fresh overrides the 30-minute cache.

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?

States a specific verb and resource ('Scan a live website'), names the legal domain (French consumer and e-commerce law) and scope (16 checks). It is clearly distinguished from siblings like check_html/check_text, which operate on snippets rather than a live crawl.

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?

Explains when a scan is reused (same site within 30 minutes) and when to set fresh=true after a fix, and routes the agent to get_scan_result if the run exceeds 100 seconds. It does not explicitly compare against sibling tools such as check_html/check_text, so the alternative selection is left partly to inference.

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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