# text-detection

> text-detection — raghulpasupathi-text-detection. Use this tool when you need to identify and analyze text content generated by AI models, helping to detect potential misinformation, automated spam, or synthetic text. It solves problems related to content authenticity and trustworthiness, providing insights into the origins of text data. The tool takes in text inputs and outputs detection results, indicating whether the content is likely AI-generated or human-written.

Canonical page: https://skillsregistry.net/skills/raghulpasupathi-text-detection  
JSON: https://api.skillsregistry.net/v1/skills/raghulpasupathi-text-detection

## Description

Skills for analyzing and detecting AI-generated text content.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-09-26

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/raghulpasupathi-text-detection)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "raghulpasupathi-text-detection"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/raghulpasupathi-text-detection` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/raghulpasupathi-text-detection/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt