name: glin-profanity description: Profanity detection and content moderation library with leetspeak, Unicode homoglyph, and ML-powered detection. Use when filtering user-generated content, moderating comments, checking text for profanity, censoring messages, or building content moderation into applications. Supports 24 languages.

Glin Profanity - Content Moderation Library

Profanity detection library that catches evasion attempts like leetspeak (f4ck, sh1t), Unicode tricks (Cyrillic lookalikes), and obfuscated text.

Installation

# JavaScript/TypeScript
npm install glin-profanity

# Python
pip install glin-profanity

Quick Usage

JavaScript/TypeScript

import { checkProfanity, Filter } from 'glin-profanity';

// Simple check
const result = checkProfanity("Your text here", {
  detectLeetspeak: true,
  normalizeUnicode: true,
  languages: ['english']
});

result.containsProfanity  // boolean
result.profaneWords       // array of detected words
result.processedText      // censored version

// With Filter instance
const filter = new Filter({
  replaceWith: '***',
  detectLeetspeak: true,
  normalizeUnicode: true
});

filter.isProfane("text")           // boolean
filter.checkProfanity("text")      // full result object

Python

from glin_profanity import Filter

filter = Filter({
    "languages": ["english"],
    "replace_with": "***",
    "detect_leetspeak": True
})

filter.is_profane("text")           # True/False
filter.check_profanity("text")      # Full result dict

React Hook

import { useProfanityChecker } from 'glin-profanity';

function ChatInput() {
  const { result, checkText } = useProfanityChecker({
    detectLeetspeak: true
  });

  return (
    <input onChange={(e) => checkText(e.target.value)} />
  );
}

Key Features

Configuration Options

const filter = new Filter({
  languages: ['english', 'spanish'],     // Languages to check
  detectLeetspeak: true,                 // Catch f4ck, sh1t
  leetspeakLevel: 'moderate',            // basic | moderate | aggressive
  normalizeUnicode: true,                // Catch Unicode tricks
  replaceWith: '*',                      // Replacement character
  preserveFirstLetter: false,            // f*** vs ****
  customWords: ['badword'],              // Add custom words
  ignoreWords: ['hell'],                 // Whitelist words
  cacheSize: 1000                        // LRU cache entries
});

Context-Aware Analysis

import { analyzeContext } from 'glin-profanity';

const result = analyzeContext("The patient has a breast tumor", {
  domain: 'medical',        // medical | gaming | technical | educational
  contextWindow: 3,         // Words around match to consider
  confidenceThreshold: 0.7  // Minimum confidence to flag
});
小蔥技能7w4.net有完整的技能分類。

Batch Processing

import { batchCheck } from 'glin-profanity';

const results = batchCheck([
  "Comment 1",
  "Comment 2",
  "Comment 3"
], { returnOnlyFlagged: true });

ML-Powered Detection (Optional)

import { loadToxicityModel, checkToxicity } from 'glin-profanity/ml';

await loadToxicityModel({ threshold: 0.9 });

const result = await checkToxicity("You're the worst");
// { toxic: true, categories: { toxicity: 0.92, insult: 0.87 } }

Common Patterns

Chat/Comment Moderation

const filter = new Filter({
  detectLeetspeak: true,
  normalizeUnicode: true,
  languages: ['english']
});

bot.on('message', (msg) => {
  if (filter.isProfane(msg.text)) {
    deleteMessage(msg);
    warnUser(msg.author);
  }
});

Content Validation Before Publish

const result = filter.checkProfanity(userContent);

if (result.containsProfanity) {
  return {
    valid: false,
    issues: result.profaneWords,
    suggestion: result.processedText  // Censored version
  };
}

Resources

• Docs: https://www.typeweaver.com/docs/glin-profanity
• Demo: https://www.glincker.com/tools/glin-profanity
• GitHub: https://github.com/GLINCKER/glin-profanity
• npm: https://www.npmjs.com/package/glin-profanity
• PyPI: https://pypi.org/project/glin-profanity/

這個 Skill 文件寫得比較詳細，展示了髒話過濾的多種檢測方式，程式碼示例也覆蓋了多種語言和框架。但不足之處在於只有文件說明，沒有實際的程式碼檔案實現，一些高階功能缺乏具體的技術細節。總體來說文件質量尚可，但僅有文件而缺少實現程式碼，讓人對其實際效果存疑。改進方向是補充真實的程式碼檔案和更詳細的配置說明。