MODEL PROMPTS

sound-effect-v2 Prompts — 17 curated examples

Examples for using sound-effect-v2 through RunAPI from agent tools or API calls. Copy a prompt, then use it in Claude Code, Codex, Cursor, Windsurf, or your backend.

MODELS

sound-effect-v2

Modality
Audio
Provider
ElevenLabs
Endpoint
Text To Sound
View model details and pricing →
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate audio: "Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity"
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate audio: "Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity"
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate audio: "Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity"
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate audio: "Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity"
curl -X POST https://runapi.ai/api/v1/elevenlabs/text_to_sound \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "sound-effect-v2",
  "text": "Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity"
}
JSON
import { ElevenlabsClient } from "@runapi.ai/elevenlabs";

const client = new ElevenlabsClient({
  apiKey: process.env.RUNAPI_API_KEY,
});

const result = await client.textToSound.run({
  "model": "sound-effect-v2",
  "text": "Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity"
});
console.log(result.id);
require "runapi/elevenlabs"

client = RunApi::Elevenlabs::Client.new
result = client.text_to_sound.run(
  model: "sound-effect-v2",
  text: "Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity"
)
puts result.id
package main

import (
  "context"
  "fmt"
  "log"
  "net/http"
  "os"
  "strings"
)

func main() {
  body := strings.NewReader("{\"model\":\"sound-effect-v2\",\"text\":\"Distant thunder rumbling across a vast open plain during a summer storm, gradually building in intensity\"}")
  req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/elevenlabs/text_to_sound", body)
  if err != nil {
    log.Fatal(err)
  }

  req.Header.Set("Authorization", "Bearer "+os.Getenv("RUNAPI_API_KEY"))
  req.Header.Set("Content-Type", "application/json")

  resp, err := http.DefaultClient.Do(req)
  if err != nil {
    log.Fatal(err)
  }
  defer resp.Body.Close()

  fmt.Println(resp.Status)
}
sound-effect-v2 /api/v1/elevenlabs/text_to_sound Get API Key
AU
Audio
urban sound-effect-v2

Busy New York intersection at rush hour: honking horns, chat...

Busy New York intersection at rush hour: honking horns, chattering pedestrians, and a passing subway train

View API Code
curl -X POST https://runapi.ai/api/v1/elevenlabs/text_to_sound \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "sound-effect-v2",
  "text": "Busy New York intersection at rush hour: honking horns, chattering pedestrians, and a passing subway train"
}
JSON
FAQ

Using sound-effect-v2 prompts

What is %{model}?

%{model} is available through RunAPI as part of the unified model catalog. These prompts show practical input patterns that agents and backend services can reuse.

How do I use these prompts?

Copy any prompt and paste it into Claude Code, Codex, Cursor, or Windsurf after installing the RunAPI MCP Server. Developers can also copy the API example and send the prompt directly.

Do these prompts cost money to browse?

Browsing and copying prompt examples is free. Generation requests only cost money when you call a RunAPI model with your API key.

Can I adapt the prompts for production?

Yes. Treat each prompt as a starting point, then add your brand rules, output dimensions, safety constraints, and application-specific context before using it in production.