Skill

translate-video

Transcribes video audio to timestamps, translates subtitles to any language, refines for shorts/regular modes, embeds RTL-safe subs with FFmpeg.

Python

Javascript

npx claudepluginhub aviz85/claude-skills-library

Tool Access

This skill uses the workspace's default tool permissions.

Preview

End-to-end video translation pipeline: transcribe → translate → refine subtitles → embed.

Supporting Assets

DEPENDENCIES.mdreferences/languages.mdreferences/modes.mdscripts/build-timestamps.pyscripts/postprocess.pyscripts/rtl-fix.py

SKILL.md

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aviz85-claude-skills-library

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Stars27

Forks8

Last CommitMar 18, 2026

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Translate Video

End-to-end video translation pipeline: transcribe → translate → refine subtitles → embed.

Usage

/translate-video /path/to/video.mp4 he --regular
/translate-video /path/to/video.mp4 he --shorts

$1 — video file path (required)
$2 — target language code (default: he). See references/languages.md
$3 — --shorts (TikTok/Reels) or --regular (YouTube/tutorials). If omitted, ask the user.

Pipeline

Step 1: Transcribe

If audio > 25MB, extract first:

ffmpeg -i "$VIDEO" -vn -acodec libmp3lame -ab 128k "$AUDIO.mp3" -y

Transcribe with word-level JSON (always include --json):

cd ~/.claude/skills/transcribe/scripts && [ -d node_modules ] || npm install --silent
npx ts-node transcribe.ts -i "$INPUT" -o "$BASENAME.srt" --json

Produces: {basename}.srt, {basename}.md, {basename}_transcript.json

Step 2: Translate

Read .md for full context. Translate the .srt — preserve all timestamps and index numbers exactly. See translation rules in references/modes.md.

Step 3: Refine Subtitles

Read references/modes.md for full rules.

--shorts: Fix text only, preserve all timestamps. No merging.

--regular: Merge into full sentences using word-level timestamps.

Plan subtitle groups from .md (word counts per group)
Fill GROUP_SIZES in scripts/build-timestamps.py and run it
Replace English text in output SRT with translated text

Step 4: Post-process (both modes)

Enforces MAX 2 lines, MAX chars/line (38 for --shorts, 42 for --regular):

python3 ~/.claude/skills/translate-video/scripts/postprocess.py "$SRT" 42

Step 5: RTL Fix (Hebrew / Arabic / Farsi only)

python3 ~/.claude/skills/translate-video/scripts/rtl-fix.py "$SRT"

Step 6: Embed & Open

~/.local/bin/ffmpeg-ass -i "$VIDEO" \
  -vf "subtitles=$SRT:force_style='FontSize=24,PrimaryColour=&H00FFFFFF,OutlineColour=&H00000000,Outline=2,Shadow=1,Alignment=2,MarginV=30'" \
  -c:v libx264 -preset fast -crf 23 -c:a copy "$OUTPUT" -y
open "$OUTPUT"

⚠️ Do NOT use Docker ffmpeg for long videos on ARM Mac — x86 emulation is ~100x slower.

Output Files

File	Description
`{name}.srt`	Original language SRT
`{name}.md`	Readable transcript
`{name}_transcript.json`	Word-level timestamps
`{name}_{lang}.srt`	Translated + refined SRT
`{name}_{lang}_subtitled.mp4`	Final video

Supporting Files

File	Purpose
references/modes.md	Detailed --shorts and --regular rules
references/languages.md	Language codes + RTL flags
scripts/build-timestamps.py	Word-index cursor for --regular timestamps
scripts/postprocess.py	Enforce line limits on any SRT
scripts/rtl-fix.py	Apply RTL Unicode markers