03_task1
Coordinates meeting scheduling via Gmail and Calendar APIs. Use when: scheduling a meeting, checking participant availability,…
Text-to-speech, speech-to-text, voice conversion, and audio processing using EachLabs AI models. Supports ElevenLabs TTS, Whisper transcription with diarization, and RVC voice conversion. Use when the user needs TTS, transcription, or voice conversion.
$ npx -y skills add internlm/wildclawbench --skill eachlabs-voice-audio --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/eachlabs-voice-audioContext preview
The summary Claude sees to decide when to auto-load this skill.
Text-to-speech, speech-to-text, voice conversion, and audio processing using EachLabs AI models. Supports ElevenLabs TTS, Whisper transcription with diarization, and RVC voice conversion. Use when the user needs TTS, transcription, or voice conversion.
name: eachlabs-voice-audio description: Text-to-speech, speech-to-text, voice conversion, and audio processing using EachLabs AI models. Supports ElevenLabs TTS, Whisper transcription with diarization, and RVC voice conversion. Use when the user needs TTS, transcription, or voice conversion. metadata: author: eachlabs version: "1.0"
Text-to-speech, speech-to-text transcription, voice conversion, and audio utilities via the EachLabs Predictions API.
Header: X-API-Key: <your-api-key>
Set the `EACHLABS_API_KEY` environment variable. Get your key at [eachlabs.ai](https://eachlabs.ai).
| Model | Slug | Best For | |-------|------|----------| | ElevenLabs TTS | `elevenlabs-text-to-speech` | High quality TTS | | ElevenLabs TTS w/ Timestamps | `elevenlabs-text-to-speech-with-timestamp` | TTS with word timing | | ElevenLabs Text to Dialogue | `elevenlabs-text-to-dialogue` | Multi-speaker dialogue | | ElevenLabs Sound Effects | `elevenlabs-sound-effects` | Sound effect generation | | ElevenLabs Voice Design v2 | `elevenlabs-voice-design-v2` | Custom voice design | | Kling V1 TTS | `kling-v1-tts` | Kling text-to-speech | | Kokoro 82M | `kokoro-82m` | Lightweight TTS | | Play AI Dialog | `play-ai-text-to-speech-dialog` | Dialog TTS | | Stable Audio 2.5 | `stable-audio-2-5-text-to-audio` | Text to audio |
| Model | Slug | Best For | |-------|------|----------| | ElevenLabs Scribe v2 | `elevenlabs-speech-to-text-scribe-v2` | Best quality transcription | | ElevenLabs STT | `elevenlabs-speech-to-text` | Standard transcription | | Wizper with Timestamp | `wizper-with-timestamp` | Timestamped transcription | | Wizper | `wizper` | Basic transcription | | Whisper | `whisper` | Open-source transcription | | Whisper Diarization | `whisper-diarization` | Speaker identification | | Incredibly Fast Whisper | `incredibly-fast-whisper` | Fastest transcription |
| Model | Slug | Best For | |-------|------|----------| | RVC v2 | `rvc-v2` | Voice conversion | | Train RVC | `train-rvc` | Train custom voice model | | ElevenLabs Voice Clone | `elevenlabs-voice-clone` | Voice cloning | | ElevenLabs Voice Changer | `elevenlabs-voice-changer` | Voice transformation | | ElevenLabs Voice Design v3 | `elevenlabs-voice-design-v3` | Advanced voice design | | ElevenLabs Dubbing | `elevenlabs-dubbing` | Video dubbing | | Chatterbox S2S | `chatterbox-speech-to-speech` | Speech to speech | | Open Voice | `openvoice` | Open-source voice clone | | XTTS v2 | `xtts-v2` | Multi-language voice clone | | Stable Audio 2.5 Inpaint | `stable-audio-2-5-inpaint` | Audio inpainting | | Stable Audio 2.5 A2A | `stable-audio-2-5-audio-to-audio` | Audio transformation | | Audio Trimmer | `audio-trimmer-with-fade` | Audio trimming with fade |
| Model | Slug | Best For | |-------|------|----------| | FFmpeg Merge Audio Video | `ffmpeg-api-merge-audio-video` | Merge audio with video | | Toolkit Video Convert | `toolkit` | Video/audio conversion |
1. **Check model** `GET https://api.eachlabs.ai/v1/model?slug=<slug>` — validates the model exists and returns the `request_schema` with exact input parameters. Always do this before creating a prediction to ensure correct inputs. 2. **POST** `https://api.eachlabs.ai/v1/prediction` with model slug, version `"0.0.1"`, and input matching the schema 3. **Poll** `GET https://api.eachlabs.ai/v1/prediction/{id}` until status is `"success"` or `"failed"` 4. **Extract** the output from the response
curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "elevenlabs-text-to-speech",
"version": "0.0.1",
"input": {
"text": "Welcome to our product demo. Today we will walk through the key features.",
"voice_id": "EXAVITQu4vr4xnSDxMaL",
"model_id": "eleven_v3",
"stability": 0.5,
"similarity_boost": 0.7
}
}'curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "elevenlabs-speech-to-text-scribe-v2",
"version": "0.0.1",
"input": {
"media_url": "https://example.com/recording.mp3",
"diarize": true,
"timestamps_granularity": "word"
}
}'curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "wizper-with-timestamp",
"version": "0.0.1",
"input": {
"audio_url": "https://example.com/audio.mp3",
"language": "en",
"task": "transcribe",
"chunk_level": "segment"
}
}'curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "whisper-diarization",
"version": "0.0.1",
"input": {
"file_url": "https://example.com/meeting.mp3",
"num_speakers": 3,
"language": "en",
"group_segments": true
}
}'curl -X POST https://api.eachlabs.ai/v1/prediction \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-d '{
"model": "rvc-v2",
"version": "0.0.1",
"input": {
"input_audio": "https://example.com/vocals.wav",
"rvc_model": "CUSTOM",
"custom_rvc_model_download_url": "https://example.com/my-voice-model.zip",
"pitch_change": 0,
"output_format": "wav"
}
}'curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "
An in-the-wild benchmark for AI agents in the production harness.
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