Roblox Integration

The Tuteliq Roblox module is a pure Luau library that monitors in-game chat for grooming, bullying, and unsafe content via the Tuteliq API. Drop it into any experience and start protecting players with two lines of code.

Landing Page

Features overview and pricing

GitHub

Source code and releases

Wally

Install via Wally registry

.rbxm Download

Download the latest model file

Installation

Wally (recommended)

Add to your wally.toml:

[dependencies]
TuteliqSafety = "tuteliq/tuteliq-safety@1.0.0"

Then run:

wally install

Rojo model file

Download TuteliqSafety.rbxm from the latest GitHub release and insert it into ServerScriptService in Roblox Studio.

Roblox Creator Store

Search for TuteliqSafety in the Creator Marketplace toolbox inside Roblox Studio, then insert the model into ServerScriptService.

Manual

Copy the TuteliqSafety/ folder into ServerScriptService in Roblox Studio.

Prerequisites

Enable HTTP Requests — In Roblox Studio go to Game Settings → Security → Allow HTTP Requests and turn it on.
Get an API key — Sign up at tuteliq.ai and create a key starting with tq_.

Quick start

Create a Script in ServerScriptService:

local TuteliqSafety = require(game.ServerScriptService.TuteliqSafety)

TuteliqSafety.start({
    apiKey = "tq_live_YOUR_API_KEY_HERE",
    sensitivity = "high",
    detect = { "bullying", "grooming", "unsafe" },
})

Never hardcode API keys in production. Use Roblox Secrets Store or a server-side configuration service to load keys at runtime.

How it works

Every chat message goes through a three-stage pipeline:

Crisis keywords — Phrases like “kill myself” or “send me pictures” trigger an immediate API call to /safety/unsafe for instant analysis.
Grooming buffer — Messages are accumulated per channel. When the buffer reaches 5+ messages from 2+ unique senders, a conversation analysis is sent to /safety/grooming.
Batch queue — All other messages are batched (25 per request or every 5 seconds) and sent to /batch/analyze for efficient bullying and unsafe content detection.

When a threat is detected above your sensitivity threshold, the module takes automatic actions based on severity:

Severity	Actions
Low	Log to output
Medium	Log + notify admins via BindableEvent + webhook
High	Log + notify + mute player for 60s + webhook
Critical	Log + notify + mute + kick player (if enabled) + webhook

Listen for detections

Connect to the TuteliqAlert BindableEvent to build custom admin UI or notifications:

local alertEvent = TuteliqSafety.onDetection()

alertEvent.Event:Connect(function(data)
    -- data.type:              "bullying" | "grooming" | "unsafe"
    -- data.severity:          "low" | "medium" | "high" | "critical"
    -- data.confidence:        number (0–1)
    -- data.riskScore:         number (0–1)
    -- data.rationale:         string
    -- data.recommendedAction: string
    -- data.playerName:        string
    -- data.playerId:          number
    -- data.message:           string
    -- data.timestamp:         number

    warn(string.format(
        "[ALERT] %s | %s | Player: %s",
        data.type, data.severity, data.playerName
    ))
end)

Integrate muting with your chat system

Muted players have the attribute TuteliqMuted set to true. Use this to filter messages in your chat UI:

player:GetAttributeChangedSignal("TuteliqMuted"):Connect(function()
    if player:GetAttribute("TuteliqMuted") then
        -- Block this player's messages in your UI
    end
end)

Manual analysis

Analyze a specific message on demand, bypassing the batch queue:

TuteliqSafety.analyzeNow(
    "some suspicious message",
    "bullying",   -- "bullying" | "unsafe"
    player        -- optional Player instance
)

analyzeNow does not support grooming detection directly. Grooming requires conversation context, which is handled automatically by the conversation buffer.

Configuration

TuteliqSafety.start({
    apiKey = "tq_live_...",                  -- Required. Your Tuteliq API key.
    sensitivity = "medium",                  -- Threshold: low (0.7) | medium (0.5) | high (0.3) | maximum (0.1)
    detect = { "bullying", "grooming", "unsafe" },

    actions = {
        mute = true,                         -- Temporarily mute flagged players
        kick = false,                        -- Kick on critical severity (disabled by default)
        notifyAdmins = true,                 -- Fire TuteliqAlert BindableEvent
        log = true,                          -- Log detections to output
    },

    muteDurationSeconds = 60,                -- How long muted players stay muted
    batchSize = 25,                          -- Messages per batch API call (1–50)
    batchFlushIntervalSeconds = 5,           -- Seconds between batch flushes
    httpBudgetPerMinute = 400,               -- Max HTTP requests per minute
    webhookUrl = nil,                        -- Optional external webhook URL
})

Sensitivity levels

Level	Threshold	Best for
`low`	0.7	Minimal false positives, only flags high-confidence threats
`medium`	0.5	Balanced — good default for most experiences
`high`	0.3	Catches more subtle threats, may increase false positives
`maximum`	0.1	Maximum protection — flags nearly everything suspicious

API

Method	Description
`TuteliqSafety.start(config)`	Start monitoring chat
`TuteliqSafety.stop()`	Stop monitoring and clean up connections
`TuteliqSafety.onDetection()`	Returns the `TuteliqAlert` BindableEvent
`TuteliqSafety.analyzeNow(text, type?, player?)`	Manually analyze a message
`TuteliqSafety.isRunning()`	Check if the module is active

Architecture

TuteliqSafety/
├── init.lua               — Main entry point
├── Types.lua              — Luau type definitions
├── Config.lua             — Validation, defaults, thresholds
├── Logger.lua             — Structured logging
├── HttpClient.lua         — API communication via HttpService
├── RateLimiter.lua        — Token bucket rate limiter
├── BatchQueue.lua         — Message batching with timer/size flush
├── ConversationBuffer.lua — Ring buffer for grooming context
├── CrisisDetector.lua     — Keyword matching for immediate analysis
└── ActionDispatcher.lua   — Mute/kick/notify based on severity

Rate limiting

The module uses a token bucket rate limiter defaulting to 400 requests per minute. This is conservative and leaves room for your game’s other HTTP calls. Roblox enforces a global limit of 500 HTTP requests per minute per server. Batch processing lets you analyze up to ~10,000 messages per minute within this budget.

Roblox Integration

Landing Page

GitHub

Wally

.rbxm Download

Installation

Wally (recommended)

Rojo model file

Roblox Creator Store

Manual

Prerequisites

Quick start

How it works

Listen for detections

Integrate muting with your chat system

Manual analysis

Configuration

Sensitivity levels

API

Architecture

Rate limiting

Next steps

API Reference

Unity SDK

Landing Page

GitHub

Wally

.rbxm Download

​Installation

​Wally (recommended)

​Rojo model file

​Roblox Creator Store

​Manual

​Prerequisites

​Quick start

​How it works

​Listen for detections

​Integrate muting with your chat system

​Manual analysis

​Configuration

​Sensitivity levels

​API

​Architecture

​Rate limiting

​Next steps

API Reference

Unity SDK

Installation

Wally (recommended)

Rojo model file

Roblox Creator Store

Manual

Prerequisites

Quick start

How it works

Listen for detections

Integrate muting with your chat system

Manual analysis

Configuration

Sensitivity levels

API

Architecture

Rate limiting

Next steps