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DojoCodingLabsDojoCodingLabs/remotion-superpowers/skills/transcribe/SKILL.md

transcribe

Skill153 starsChanged 16 days agoMITView on GitHub

Transcribe audio or video files to text with timestamps. Produces word-level Caption JSON through the official remotion-captions flow (whisper-webgpu, or ElevenLabs Scribe via @remotion/elevenlabs when there's no GPU), plus an SRT export generated from those captions and plain text, for use with Remotion's captions system.

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The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 40 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Ask the user which file to transcribe if multiple exist.

    line 22
  2. Very specific:

    Every route below produces the same thing: a Caption[] with one entry per word, saved as public/<source>.captions.json (e.g.

    line 26
  3. Very specific:

    If ELEVENLABS_API_KEY isn't set, run npx -y @elevenlabs/cli@latest onboard init from the project root.

    line 40
  4. Very specific:

    Don't use the ElevenLabs MCP speech_to_text tool: it returns plain text with no timestamps.

    line 44
  5. Distinctive:

    After transcription, suggest next steps:

    line 118

“Common” is measured: kept by at least 6 in 10 of the 40 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Transcribe: Audio/Video to Text

You are helping the user transcribe audio or video files into text with precise timestamps.

Load the remotion-production skill for the captions-workflow rule (both routes, including the Scribe script), and the official remotion-captions skill. For the Scribe route, also load the official ElevenLabs speech-to-text skill. The official skills win on any API detail.

Workflow

1. Identify the Source File

Find audio/video files to transcribe:

ls public/ public/footage/ 2>/dev/null | grep -E '\.(mp3|wav|m4a|ogg|mp4|mov|webm)$'

Ask the user which file to transcribe if multiple exist. Transcribe each source file separately, and keep its timestamps relative to the start of that file.

2. Transcribe to Word-Level JSON

Every route below produces the same thing: a Caption[] with one entry per word, saved as public/<source>.captions.json (e.g. vo-scene1.captions.json). The SRT and plain-text outputs in step 4 are generated from it.

RouteUse it whenRuns
A. Official whisper-webgpu (default)A compatible GPU is availableLocally, free, no key
B. ElevenLabs Scribe (fallback)whisper-webgpu can't run: no GPU, CI, Linux arm64, many VMsIn the cloud, paid, needs ELEVENLABS_API_KEY

Route A: whisper-webgpu

Follow official remotion-captions/transcribe-captions.md. It writes a Node script using @remotion/whisper-webgpu (canUseWhisperWebGpu, downloadWhisperModel, loadWhisperModel, transcribe, then toCaptions({ whisperWebGpuOutput })) that decodes audio or video with Mediabunny and saves Caption JSON. small.en is the default model for English. For other languages, use a multilingual model and pass language: there's no auto-detect. If canUseWhisperWebGpu() reports no support, switch to Route B.

Route B: ElevenLabs Scribe

Transcribe with Scribe v2 (timestamps_granularity: "word") and convert with elevenLabsTranscriptToCaptions() from @remotion/elevenlabs (npx remotion add @remotion/elevenlabs). The script is in the captions-workflow rule.

  • If ELEVENLABS_API_KEY isn't set, run npx -y @elevenlabs/cli@latest onboard init from the project root. Never ask for the key in chat.
  • It sends the audio to ElevenLabs and costs credits, so tell the user first.
  • It takes video files directly, auto-detects the language (or pass language_code), and accepts keyterms for names it might mishear (official speech-to-text skill).

Don't use the ElevenLabs MCP speech_to_text tool: it returns plain text with no timestamps.

3. Present the Transcript

Show the transcription with timestamps, grouped into readable lines:

Transcription: [filename]

[00:00:00 → 00:00:03] Welcome to our product demo
[00:00:03 → 00:00:07] Today we're going to show you how easy it is
[00:00:07 → 00:00:11] to create professional videos with code
...

Total duration: [X]s
Word count: [X] words

4. Output Formats

Deliver what the user asked for:

JSON Captions (always): the Caption type from @remotion/captions. Every entry needs timestampMs and confidence (either may be null), and each word starts with a space:

[
  { "text": " Welcome", "startMs": 0, "endMs": 800, "timestampMs": 400, "confidence": 0.95 },
  { "text": " to", "startMs": 800, "endMs": 1000, "timestampMs": 900, "confidence": 0.98 },
  { "text": " our", "startMs": 1000, "endMs": 1200, "timestampMs": 1100, "confidence": 0.97 }
]

SRT export (when the user wants an .srt file, e.g. to upload to YouTube): the official captions skill covers SRT import but not export, so generate it from the JSON with serializeSrt() from @remotion/captions. It takes lines, an array of lines where each line is an array of captions. Group the words into subtitle lines first:

// scripts/export-srt.ts: node scripts/export-srt.ts
import { serializeSrt, type Caption } from "@remotion/captions";
import { readFileSync, writeFileSync } from "node:fs";

const name = "vo-scene1";
const words: Caption[] = JSON.parse(readFileSync(`public/${name}.captions.json`, "utf8"));

// New line after 7 words, at a sentence end, or at a pause longer than 0.6 s
const lines: Caption[][] = [];
let line: Caption[] = [];
words.forEach((word, i) => {
  line.push(word);
  const next = words[i + 1];
  if (!next || line.length >= 7 || /[.!?]$/.test(word.text) || next.startMs - word.endMs > 600) {
    lines.push(line);
    line = [];
  }
});

writeFileSync(`public/${name}.srt`, serializeSrt({ lines }));

serializeSrt() joins a cue's words without adding spaces, which is right because each word's text already starts with one. Each cue runs from its first word's startMs to its last word's endMs. The result is standard SRT:

1
00:00:00,000 --> 00:00:03,200
Welcome to our product demo

2
00:00:03,200 --> 00:00:07,100
Today we're going to show you how easy it is

Plain text: join the words' text and trim, no timestamps:

Welcome to our product demo. Today we're going to show you how easy it is to create professional videos with code.

5. Common Use Cases

After transcription, suggest next steps:

  • Add captions → Run /add-captions; the word-level JSON works with every style, including TikTok and karaoke
  • Sync animations → Use the word timestamps to trigger visual elements at specific words
  • Create a script → Edit the transcript as the basis for a new voiceover
  • Translate → Use the transcript to create versions in other languages
  • Content repurpose → Extract key quotes for social media clips

Route A runs entirely on-device with no API key. Route B is a cloud call to ElevenLabs.

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