executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
elevenlabs-core-workflow-bImplement ElevenLabs speech-to-speech, sound effects, audio isolation, and speech-to-text. Use when converting one voice to another, generating sound effects from a text description, removing background noise from a recording, or transcribing audio. Trigger with "elevenlabs speech to speech", "voice changer", "sound effects", "audio isolation", "remove ba…
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name: elevenlabs-core-workflow-b description: | Implement ElevenLabs speech-to-speech, sound effects, audio isolation, and speech-to-text.
Use when converting one voice to another, generating sound effects from a text description, removing background noise from a recording, or transcribing audio.
Trigger with "elevenlabs speech to speech", "voice changer", "sound effects", "audio isolation", "remove background noise", "elevenlabs transcribe". allowed-tools: Read, Write, Bash(npm:), Bash(curl:) version: 1.6.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:
Secondary ElevenLabs workflows beyond TTS: (1) Speech-to-Speech voice conversion, (2) Sound Effects generation from text descriptions, (3) Audio Isolation for noise removal, and (4) Speech-to-Text transcription. Each maps to one API endpoint and has both a TypeScript SDK and a cURL path.
Full code for every step lives in references/implementation.md; copy-ready invocations are in references/examples.md.
elevenlabs-install-auth setup.The SDK client (new ElevenLabsClient()) reads the API key from the
ELEVENLABS_API_KEY environment variable automatically — never hardcode it. cURL
requests send it as the xi-api-key: ${ELEVENLABS_API_KEY} header. Full auth setup
is covered by the elevenlabs-install-auth skill.
Import the SDK once, then call the relevant module. The client authenticates from the environment:
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createReadStream, createWriteStream } from "fs";
import { Readable } from "stream";
import { pipeline } from "stream/promises";
const client = new ElevenLabsClient();
client.speechToSpeech.convert(voiceId, …)
against POST /v1/speech-to-speech/{voice_id}. Use model_id: "eleven_english_sts_v2"
and set remove_background_noise: true for built-in cleanup.client.textToSoundEffects.convert({ text, … }) against
POST /v1/sound-generation. Tune duration_seconds (0.5–30) and
prompt_influence (0–1; higher follows the prompt more closely).client.audioIsolation.audioIsolation({ audio }) against
POST /v1/audio-isolation, or the streaming variant for large files.client.speechToText.convert({ audio, model_id: "scribe_v1" })
against POST /v1/speech-to-text; optionally enable diarize and word timestamps.Each returns an audio stream (steps 1–3) piped to disk, or a transcript object (step 4). See references/implementation.md for the complete helper functions and cURL equivalents.
async function speechToSpeech(sourceAudioPath, targetVoiceId, outputPath) {
const audio = await client.speechToSpeech.convert(targetVoiceId, {
audio: createReadStream(sourceAudioPath),
model_id: "eleven_english_sts_v2",
voice_settings: JSON.stringify({ stability: 0.5, similarity_boost: 0.8 }),
remove_background_noise: true,
});
await pipeline(Readable.fromWeb(audio as any), createWriteStream(outputPath));
}
| Feature | Method | Endpoint | Billing |
|---|---|---|---|
| Speech-to-Speech | POST | /v1/speech-to-speech/{voice_id} | Per character |
| Sound Effects | POST | /v1/sound-generation | Per generation |
| Audio Isolation | POST | /v1/audio-isolation | 1,000 chars/min of audio |
| Audio Isolation Stream | POST | /v1/audio-isolation/stream | 1,000 chars/min of audio |
| Speech-to-Text | POST | /v1/speech-to-text | Per audio minute |
outputPath you pass and log a
confirmation, e.g. Voice-converted audio saved to converted.mp3 or
Clean audio saved to clean_interview.mp3.result.text holds the full
transcription, and result.words (when present) carries word-level
{ start, end, text } timestamps.--output file.| Error | HTTP | Cause | Solution |
|---|---|---|---|
model_can_not_do_voice_conversion | 400 | Wrong model for STS | Use eleven_english_sts_v2 |
audio_too_short | 400 | STS input under 1 second | Use longer audio clip |
audio_too_long | 400 | STS input over limit | Trim to under 5 minutes |
invalid_sound_prompt | 400 | Nonsensical SFX description | Write descriptive, specific prompts |
file_too_large | 413 | Audio isolation over 500MB | Compress or split the file |
quota_exceeded | 401 | Character/generation limit hit | Check usage dashboard |
Worked, copy-ready invocations for all four workflows — including the three sound-effect variants (rain, laser, seamless forest loop), the "Rachel" voice conversion, an audio-isolation clean-up, and a transcription with word timestamps — are in references/examples.md. A one-liner:
// Generate a 10-second rain sound effect, faithful to the prompt
await generateSoundEffect(
"Heavy rain on a tin roof with distant thunder",
"rain.mp3",
{ duration: 10, promptInfluence: 0.6 }
);
For common errors, see elevenlabs-common-errors. For SDK patterns, see elevenlabs-sdk-patterns.