How the OpenClaw ElevenLabs‑AI Skill Powers Text‑to‑Speech, Voice Conversion and Real‑Time Transcription

Introduction

The OpenClaw repository hosts a collection of reusable skills that simplify
integration with popular AI services. One of the most frequently used skills
is the ElevenLabs‑AI skill, which provides a thin, production‑ready wrapper
around the ElevenLabs HTTP APIs. Rather than relying on a heavyweight SDK, the
skill shows developers how to call ElevenLabs endpoints directly using HTTPS,
manage authentication, handle payloads, and observe safety and privacy best
practices. This article explains in detail what the skill does, walks through
its core components, and highlights the scenarios where it shines.

Core Purpose of the Skill

The primary goal of the OpenClaw ElevenLabs‑AI skill is to give developers a
clear, step‑by‑step guide for using ElevenLabs’ powerful voice technologies
without the overhead of installing and learning a dedicated SDK. The skill
focuses on four main capabilities:

• Text‑to‑speech (TTS) synthesis
• Speech‑to‑speech voice conversion
• Realtime speech‑to‑text transcription via WebSocket
• Multi‑voice dialogue generation for interactive applications

Each capability is documented in a separate reference file that shows the
exact HTTP method, endpoint URL, required headers, request body format, and
expected response structure. By following these references, a developer can
implement production‑grade voice features in any language that can make HTTPS
requests.

Authentication and Token Management

Before any API call can succeed, the skill requires a valid ElevenLabs API key
(the xi‑api‑key header) or, for client‑side scenarios, a single‑use token
obtained through the authentication endpoint. The skill’s authentication
reference (references/elevenlabs-authentication.md) explains:

• How to store the API key securely on a server (environment variable, secret manager)
• How to generate a short‑lived token for browsers or mobile apps, reducing exposure of the secret key
• Best practices for rotating keys and auditing usage

The guidance emphasizes never logging the API key or token, and recommends
using HTTP only over TLS to protect credentials in transit.

Text‑to‑Speech (TTS) Workflow

The TTS reference (references/elevenlabs-text-to-speech.md) outlines the
simplest path from text to audible audio:

1. Choose a voice ID (obtained from the voices/models reference)
2. Select a model ID that balances quality and latency (e.g., eleven_multilingual_v2 for multilingual output)
3. Determine the output format: codec (mp3, opus), sample rate (44100 Hz), and bitrate (128k)
4. Build a JSON payload containing text, voice_settings (stability, similarity boost), and output_format
5. Send a POST request to https://api.elevenlabs.io/v1/text-to-speech/{voice_id} with the xi‑api‑key header
6. Receive a binary audio stream in the response body; save it as a file or stream it directly to the user

The skill also notes optional parameters such as optimize_streaming_latency
for low‑latency use cases and voice_settings to fine‑tune the speaker’s
style.

Speech‑to‑Speech Voice Conversion

For scenarios where an existing recording needs to be re‑voiced (e.g.,
dubbing, character voice swaps), the skill points to the speech‑to‑speech
reference (references/elevenlabs-speech-to-speech.md). The workflow mirrors
TTS but adds an audio input:

1. Upload the source audio file (supported formats: wav, mp3, ogg) to a temporary storage accessible by your server
2. Obtain a pre‑signed URL or directly POST the binary to the ElevenLabs upload endpoint if required
3. Specify the target voice ID and model ID
4. Call the POST /v1/speech-to-speech/{voice_id} endpoint with the audio as multipart/form‑data
5. Receive the converted audio in the desired format

The skill highlights that voice conversion preserves prosody and timing while
swapping the vocal timbre, making it ideal for localization pipelines.

Realtime Speech‑to‑Text via WebSocket

When low‑latency transcription is needed (live captioning, voice commands),
the skill directs developers to the realtime STT reference
(references/elevenlabs-speech-to-text-realtime.md). Instead of REST,
ElevenLabs offers a WebSocket endpoint:

• Open a secure WebSocket connection to wss://api.elevenlabs.io/v1/speech-to-text
• Authenticate by sending an initialization message containing the API key and desired output format (e.g., pcm at 16 kHz)
• Stream audio chunks (typically 20 ms PCM frames) as binary messages
• Receive interim and final transcription messages in JSON format
• Close the connection cleanly when the utterance ends

The skill advises implementing exponential backoff on connection failures and
keeping audio payloads small to avoid throttling.

Multi‑Voice Dialogue Generation

For interactive storytelling, virtual agents, or game NPCs, the skill includes
a dialogue reference (references/elevenlabs-text-to-dialogue.md) that
explains how to produce a conversation with multiple distinct voices in a
single request:

1. Prepare a dialogue script where each line is tagged with a speaker ID
2. Map each speaker ID to a voice ID from the voices catalog
3. Optionally assign different models per speaker to match language or style
4. Send a POST request to POST /v1/dialogue with a JSON body containing an array of turns, each turn holding text, voice_id, and model_id
5. Receive a concatenated audio file (or separate tracks) that preserves turn‑taking pauses

This approach reduces round‑trips and ensures consistent audio quality across
speakers.

Voice and Model Discovery

Both TTS and speech‑to‑speech operations depend on knowing which voice and
model IDs are available. The skill’s voices/models reference
(references/elevenlabs-voices-models.md) teaches developers to:

• Call GET /v1/voices to retrieve a paginated list of voices, each with voice_id, name, category, and settings
• Call GET /v1/models to list available models, their supported languages, and latency profiles
• Cache the results server‑side for a configurable TTL (e.g., 1 hour) to reduce unnecessary API calls
• Allow end‑users to browse voices via a UI that displays voice samples (pre‑hosted audio clips provided by ElevenLabs)

Having a reliable lookup table prevents runtime errors caused by misspelled
IDs.

Safety, Privacy, and Operational Guardrails

The skill does not ignore the ethical dimensions of voice AI. The safety and
privacy reference (references/elevenlabs-safety-and-privacy.md) outlines:

• Zero‑retention policy: ElevenLabs does not store audio longer than necessary for processing
• Content moderation: Developers should screen input text for prohibited material before sending it to the API
• Usage limits: Respect rate limits; implement client‑side throttling and server‑side queuing
• Data minimization: Only transmit the minimum audio needed (e.g., downsample to 16 kHz if higher fidelity is not required)
• Audit logs: Keep internal logs of request metadata (timestamps, voice IDs) without capturing the API key or raw audio

Operational notes further advise maintaining an allowlist of downstream
destinations for generated audio (to prevent unintended distribution) and
retrying failed requests with exponential backoff and jitter.

When to Use This Skill

The OpenClaw ElevenLabs‑AI skill is ideal for developers who:

• Need quick, reliable access to high‑quality TTS or voice conversion without installing language‑specific SDKs
• Prefer transparent HTTP calls that can be logged, inspected, and reproduced in CI/CD pipelines
• Are building server‑side services, microservices, or cloud functions where minimizing dependency size matters
• Want full control over request headers, payload formatting, and error handling
• Are comfortable handling WebSocket connections for realtime transcription

Conversely, the skill is not the best fit if you require:

• High‑level abstractions such as built‑in audio players, automatic fallback voices, or integrated dialogue management
• Feature‑rich SDK utilities like automatic retries, streaming helpers, or platform‑specific UI components
• A full conversational agent framework that handles turn‑taking, context management, and NLU alongside audio I/O

In those cases, wrapping the skill’s HTTP calls in a thin custom layer or
opting for an official SDK may be more productive.

Putting It All Together – Example Pseudocode

Below is a language‑agnostic pseudocode snippet that demonstrates a typical
TTS flow using the skill’s guidelines:

FUNCTION synthesizeText(text, voiceId, modelId):
    apiKey ← getSecureEnvVar('ELEVENLABS_API_KEY')
    url ← "https://api.elevenlabs.io/v1/text-to-speech/" + voiceId
    headers ← {
        "xi-api-key": apiKey,
        "Content-Type": "application/json"
    }
    payload ← {
        "text": text,
        "model_id": modelId,
        "voice_settings": {
            "stability": 0.5,
            "similarity_boost": 0.75
        },
        "output_format": "mp3_44100_128"
    }
    response ← HTTP POST url, headers, payload
    IF response.statusCode != 200:
        LOG ERROR response.body
        THROW Exception("TTS request failed")
    END IF
    RETURN response.body   // binary MP3 audio
END FUNCTION

The same pattern applies to speech‑to‑speech (multipart upload) and realtime
STT (WebSocket loop), with only the endpoint, headers, and payload structure
changing.

Conclusion

The OpenClaw ElevenLabs‑AI skill is a concise, production‑oriented guide that
unlocks the power of ElevenLabs’ voice APIs through straightforward HTTPS
calls. By following the skill’s references — authentication, TTS,
speech‑to‑speech, realtime STT, dialogue generation, voice/model discovery,
and safety practices — developers can integrate lifelike voice capabilities
into any application while maintaining control over security, performance, and
cost. Whether you are building a podcast production pipeline, a
live‑captioning service, or an interactive game with dynamic NPC voices, the
skill provides the essential checklist and best‑practice notes to get you up
and running quickly and reliably.

Skill can be found at:
ai/SKILL.md>