Speech To Text

What it does

When your agent uses it

• Converting audio/video to text
• Generating subtitles
• Transcribing meetings
• Processing spoken content

Example prompts

• “/speech-to-text”

Requirements

• Python 3
• A credential in ELEVENLABS_API_KEY
• Compatibility (from SKILL.md): Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY).

What it can do on your machine

Read from SKILL.md and the folder at commit 452e950. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • curl

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • api.elevenlabs.io

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • ELEVENLABS_API_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY).

  From compatibility in the SKILL.md frontmatter.

Context cost

Speech To Text loads about 2k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 46 tokens; SKILL.md has 377 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~46

When it runs · the whole SKILL.md, loaded when a task matches

~2k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~11k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from tadaspetra/loop at commit 452e950, republished under its MIT licence (© tadaspetra). 377 words, ~2,040 tokens.

name

speech-to-text

description

Transcribe audio to text using ElevenLabs Scribe v2. Use when converting audio/video to text, generating subtitles, transcribing meetings, or processing spoken content.

compatibility

Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY).

license

MIT

from elevenlabs import ElevenLabs

client = ElevenLabs()

with open("audio.mp3", "rb") as audio_file:
    result = client.speech_to_text.convert(file=audio_file, model_id="scribe_v2")

print(result.text)

import { ElevenLabsClient } from '@elevenlabs/elevenlabs-js';
import { createReadStream } from 'fs';

const client = new ElevenLabsClient();
const result = await client.speechToText.convert({
  file: createReadStream('audio.mp3'),
  modelId: 'scribe_v2'
});
console.log(result.text);

curl -X POST "https://api.elevenlabs.io/v1/speech-to-text" \
  -H "xi-api-key: $ELEVENLABS_API_KEY" -F "file=@audio.mp3" -F "model_id=scribe_v2"

result = client.speech_to_text.convert(
    file=audio_file, model_id="scribe_v2", timestamps_granularity="word"
)

for word in result.words:
    print(f"{word.text}: {word.start}s - {word.end}s (type: {word.type})")

result = client.speech_to_text.convert(
    file=audio_file,
    model_id="scribe_v2",
    diarize=True
)

for word in result.words:
    print(f"[{word.speaker_id}] {word.text}")

result = client.speech_to_text.convert(
    file=audio_file,
    model_id="scribe_v2",
    keyterms=["ElevenLabs", "Scribe", "API"]
)

result = client.speech_to_text.convert(
    file=audio_file,
    model_id="scribe_v2",
    language_code="eng"  # ISO 639-1 or ISO 639-3 code
)

print(f"Detected: {result.language_code} ({result.language_probability:.0%})")

{
  "text": "The full transcription text",
  "language_code": "eng",
  "language_probability": 0.98,
  "words": [
    { "text": "The", "start": 0.0, "end": 0.15, "type": "word", "speaker_id": "speaker_0" },
    { "text": " ", "start": 0.15, "end": 0.16, "type": "spacing", "speaker_id": "speaker_0" }
  ]
}

try:
    result = client.speech_to_text.convert(file=audio_file, model_id="scribe_v2")
except Exception as e:
    print(f"Transcription failed: {e}")

response = client.speech_to_text.convert.with_raw_response(file=audio_file, model_id="scribe_v2")
result = response.parse()
print(f"Request ID: {response.headers.get('request-id')}")

import asyncio
from elevenlabs import ElevenLabs

client = ElevenLabs()

async def transcribe_realtime():
    async with client.speech_to_text.realtime.connect(
        model_id="scribe_v2_realtime",
        include_timestamps=True,
    ) as connection:
        await connection.stream_url("https://example.com/audio.mp3")

        async for event in connection:
            if event.type == "partial_transcript":
                print(f"Partial: {event.text}")
            elif event.type == "committed_transcript":
                print(f"Final: {event.text}")

asyncio.run(transcribe_realtime())

import { useScribe } from "@elevenlabs/react";

function TranscriptionComponent() {
  const [transcript, setTranscript] = useState("");

  const scribe = useScribe({
    modelId: "scribe_v2_realtime",
    onPartialTranscript: (data) => console.log("Partial:", data.text),
    onCommittedTranscript: (data) => setTranscript((prev) => prev + data.text),
  });

  const start = async () => {
    // Get token from your backend (never expose API key to client)
    const { token } = await fetch("/scribe-token").then((r) => r.json());

    await scribe.connect({
      token,
      microphone: { echoCancellation: true, noiseSuppression: true },
    });
  };

  return <button onClick={start}>Start Recording</button>;
}

// VAD configuration
const connection = await client.speechToText.realtime.connect({
  modelId: 'scribe_v2_realtime',
  vad: {
    silenceThresholdSecs: 1.5,
    threshold: 0.4
  }
});

© tadaspetra, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in .agents/skills/speech-to-text of tadaspetra/loop.

• SKILL.md
• references/installation.md
• references/realtime-client-side.md
• references/realtime-commit-strategies.md
• references/realtime-events.md
• references/realtime-server-side.md
• references/transcription-options.md

Open the folder on GitHubat commit 452e950

Used in 2 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in tadaspetra/loop, which our catalogue first saw on October 7, 2026.

• calesthio/OpenMontage.agents/skills/speech-to-text.claude/skills/speech-to-text
• elevenlabs/skillsspeech-to-text