# Chinese Slang Density Checker AI Agent Connect

> Analyze the prevalence and trendiness of Chinese internet slang in text.

## Overview
- **Category:** data-analysis
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_bIt5D0AdUSTxMCeuT6B1FCaRl6vxEGx8gazUjcwB/ai-agent-connect
- **Tags:** chinese, slang, linguistics, text-analysis, wangluo-yongyu

## Description

This MCP server provides deterministic analysis of Wangluo Yongyu (Chinese internet slang) within text samples. Use `analyze_slang_density` to calculate slang density and trendiness scores, `get_slang_categories` to discover pre-defined slang dictionaries, and `validate_slang_term` to verify specific terms. It is an essential tool for linguistic analysis of digital Chinese communication.

## Tools

### get_slang_categories
Retrieves a list of pre-defined slang categories

### analyze_slang_density
Calculates linguistic metrics for Chinese internet slang density

### validate_slang_term
Checks if a specific string is a recognized valid slang term

## Prompt Examples

**Prompt:** 
```
Analyze the slang density of this text: '这个真的yyds，简直太绝了！'
```

**Response:** 
```
{"slangCount": 2, "totalWords": 7, "slangDensityPercent": 28.57, "trendinessScore": 100, "matchedSlangArray": ["yyds", "绝了"]}
```

**Prompt:** 
```
Check if 'tangping' is a valid slang term using the provided dictionary.
```

**Response:** 
```
{"isValid": true, "term": "tangping"}
```

**Prompt:** 
```
What slang categories are available?
```

**Response:** 
```
{"categories": ["Gen-Z", "Workplace", "Gaming"], "selectedCategory": []}
```

## Frequently Asked Questions

**How is the word count calculated for Chinese text?**
The total word count is approximated by dividing the total character count of the text by two.

**What does the trendiness score represent?**
The trendiness score categorizes text based on slang density: 100 for high density (>5%), 50 for moderate density (1-5%), and 0 for low density.

**Can I use my own custom slang dictionary?**
Yes, you can provide your own list of terms via the `slangDictionary` input in the `analyze_slang_density` tool.