SLOP Detector

“The SLOP Meter doesn’t measure truth or beauty. It measures how loudly your sentences clap for themselves. When the needle bursts through the dial and a small goblin emerges to applaud, you are probably no longer writing—you are performing.”

Detect AI-like writing patterns in creative prose. Returns a 0-100 score where higher = more AI-like.

SLOP Detector is inspired by the original slop-score project and is designed for creative writing analysis, not as a general-purpose AI detection system. It currently supports English text only.

Quick Start

npx -y slop-detector

This starts an MCP server. Add it to your AI assistant:

Claude Code:

claude mcp add slop-detector -- npx -y slop-detector

Codex:

codex mcp add slop-detector -- npx -y slop-detector

Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "slop-detector": {
      "command": "npx",
      "args": ["-y", "slop-detector"]
    }
  }
}

What It Detects

| Component | Weight | What it finds | |-----------|--------|---------------| | Slop Words | 60% | Overused words like delve, tapestry, paradigm, leverage | | Contrast Patterns | 25% | "Not X but Y" structures that LLMs love | | Trigrams | 15% | Common 3-word phrases like "it is important" |

Score Interpretation

| Score | Meaning | |-------|---------| | 0-20 | Human-like writing | | 20-40 | Mostly human, some AI patterns | | 40-60 | Mixed, unclear origin | | 60-80 | Likely AI-generated | | 80-100 | Strong AI signature |

Rule of thumb: Scores above 30 are suspicious.

Usage

As an MCP Tool

The score_text tool accepts text and returns:

• slopScore: 0-100 score
• wordCount, charCount: Text statistics
• metrics: Detailed breakdown (words/trigrams/patterns per 1k)

Command Line

# Install and build
npm install && npm run build

# Score a file
node dist/cli.js article.txt

# Score from stdin
echo "Let's delve into this tapestry of ideas" | node dist/cli.js -
pbpaste | node dist/cli.js -   # macOS clipboard

As a Library

import { slopScoreService } from 'slop-detector';

const result = await slopScoreService.computeScoreFromText(text, 'en');
console.log(result.slopScore); // 42.5

Example Output

=== SLOP Score Analysis ===

Final Score: 67.3/100
Word Count: 342

Top Slop Words:
  "delve": 3×
  "tapestry": 2×

Contrast Patterns Found:
  "not just a product but a comprehensive solution"

Interpretation: Likely AI-generated with some editing

How It Works

See docs/IMPLEMENTATION.md for:

• Detailed algorithm explanation
• Project structure
• How to add custom patterns

Development

npm install          # Install dependencies
npm run build        # Compile TypeScript
npm test             # Run tests
npm run mcp          # Start MCP server locally

Requirements

• Node.js 18+

License

MIT

Credits

Based on slop-score by Samuel J. Paech and the EQBench methodology.