# RYLA

> RYLA — ai-ryla-ryla. Use this tool when you need to generate realistic AI influencer photos, face swaps, or character sheets with a consistent face, solving problems such as creating uniform branding or fictional character designs. It takes input parameters such as facial features and outputs customized images. Ideal for use cases like social media marketing, content creation, or game development, where consistent character appearances are essential.

Canonical page: https://skillsregistry.net/skills/ai-ryla-ryla  
JSON: https://api.skillsregistry.net/v1/skills/ai-ryla-ryla

## Description

Generate AI influencer photos, face swaps, and character sheets with a consistent face.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Updated:** 2026-09-04

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.ryla%2Fryla)

## Use it

MCP endpoint published by the skill: `https://mcp.ryla.ai/mcp`

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": "ai-ryla-ryla"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-ryla-ryla` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-ryla-ryla/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