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callremind

CallRemind MCP Server

Official
by callremind

validateTextSafety

Check a message for profanity in English, Malay, Mandarin, and Tamil before it is spoken. Get a safe/found result with detected languages to prevent inappropriate automated calls.

Instructions

Check a message for profanity / swear words (English, Bahasa Malaysia, Mandarin, Tamil) before it is spoken (POST /v1/validate-text-safety). Returns { safe, found, languages }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text/message to check

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.6

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries full behavioral disclosure. It states the operation (profanity check), the input language coverage, and the return shape ({ safe, found, languages }). It doesn't mention side effects or error behavior, but for a validation tool the core behavior is well disclosed.

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 sentence that front-loads the purpose, includes the relevant languages, the endpoint, and the return shape. Every part adds value and there is no redundant information.

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 simple one-parameter validation tool with no output schema, the description explains what it does, when to use it, the input, and the response. Nothing essential is missing.

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 already describes 'text' as 'The text/message to check'. The description adds minor context about the message being spoken but provides no additional parameter details such as length limits or formatting, so the baseline score applies.

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 uses a specific verb ('Check') and resource ('a message for profanity / swear words') and specifies supported languages. It clearly distinguishes itself from the sibling tools, which are all call-making or configuration tools.

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 phrase 'before it is spoken' provides clear context for when this tool is appropriate. While it doesn't explicitly name alternatives or exclusions, none of the sibling tools perform a similar safety-check function, so the context is sufficient.

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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