ConformRadar

check_text

Read-onlyIdempotent

Check plain text you are writing (product description, ad or newsletter copy, terms of sale, legal notice) before publishing.

product_description and marketing: banned or vague environmental claims ("biodegradable", "eco-friendly", "carbon neutral",
"recycled" without a percentage); product_description also checks the GPSR manufacturer block and textile composition and origin.
terms: legal guarantee box, consumer mediator, outdated EU ODR link, withdrawal wording, EPR unique identifier.
legal_notice: seller identity, EPR unique identifier, mediator.
French texts are fully supported; English texts only for environmental claims.

Args:
    text: the text to check (up to 200,000 characters).
    text_type: what the text is.
    product_name: for a product description, the product's name (tells textiles, food and services apart).
    lang: "fr" or "en".

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": {
      "text": "<text>",
      "text_type": "<text_type>"
    },
    "name": "check_text"
  }
}

Input Schema

Name	Required	Default
`lang`	No	fr
`text`	Yes
`text_type`	Yes
`product_name`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 15, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations cover read-only/idempotent/open-world status, but the description adds substantial context the annotations don't: read-only nature aside, it discloses a 200,000-character limit, that product_description triggers GPSR/textile checks, and that product_name is used to classify textiles/food/services. That is meaningful behavioral detail beyond the structured fields.

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?

Front-loaded statement of intent, then compact per-type breakdown and arg definitions. Dense but almost every clause carries unique signal. Slight redundancy in listing text types twice (parenthetical and per-type block) keeps it from a 5.

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?

No output schema exists, and the description does not describe return values or findings format, which is the main remaining gap. Everything an agent needs to invoke it correctly (params, language support, text-type-specific behavior) is present, so it is nearly complete for a 4-param tool.

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 coverage is 0%, so the description must compensate, and it does: it defines text (up to 200k chars), text_type categories, lang supported values, and crucially that product_name disambiguates textiles/food/services – none of which the schema conveys. This fully covers what an agent needs.

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 (check) and resource (plain text) and enumerates the concrete text categories it covers (product description, ad/newsletter copy, terms of sale, legal notice). It also names specific checks per text_type, which no sibling does.

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 'before publishing' framing and the per-text_type enumeration implicitly tell the agent when to use it, and the language note ('French fully supported; English only for environmental claims') is an explicit constraint. However, it never names or routes to alternatives, which is the tool's main gap given siblings like check_html.

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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