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Hebrew Podcast Post-Production Kit

Trusted87/100
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Complete post-production package for Hebrew podcasts: RTL show notes with Spotify and Apple chapter markers, identification of 3-5 shareable 30-90 second clips, FFmpeg commands for extraction and Hebrew subtitle burn-in, and platform-tuned captions for Instagram Reels, TikTok, X, and LinkedIn. Use when shipping a Hebrew podcast episode from a Whisper transcript or SRT file and you need show notes, chapters, clips, and social captions in one coherent output without stitching together 4-5 separate tools and without tripping over RTL, nikud, and Hebrew subtitle burn-in bugs that generic tools (Kapwing, Maestra, Descript, Podsqueeze) mishandle. Do NOT use for standalone audio transcription (use video-subtitles), podcast RSS feed generation, audio mixing and mastering, or English-only podcasts.

Trust score 87/100 (Trusted) · 22+ installs · MIT license

The Problem

Hebrew podcasters ship every episode through 4-5 disconnected tools: one for transcription, one for show notes, another for clip-hunting, another for social captions, plus FFmpeg for the actual cutting. Generic tools (Kapwing, Maestra, Descript, Podsqueeze) mishandle RTL text, drop nikud, and produce broken subtitle burn-ins because they do not run FriBidi for Hebrew. This skill consolidates the entire post-production workflow into one coherent package from a single transcript input.

skills-ilskills-ilMarketing & Growth
1.1.0MITGitHub
22installs1,064views
0Write a Review
npx skills-il add skills-il/marketing-growth@v1.1.0-hebrew-podcast-postproduction --skill hebrew-podcast-postproduction -a claude-code
Install on Claude.ai, Claude Desktop, ChatGPT, Manus, or other platforms
  1. 1. Click "Download ZIP" to download the skill files.
  2. 2. Open Claude Desktop and go to Customize > Skills.
  3. 3. Click "+" and select "Upload a skill", then upload the ZIP file.
  4. 4. Start a new conversation. The skill will activate automatically when relevant.
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When to Apply

  • When you need to generate RTL show notes with Spotify and Apple chapter markers from a Whisper or ElevenLabs Scribe transcript
  • When you want to identify the 3-5 most shareable moments from an episode and produce FFmpeg clip-extraction commands with Hebrew subtitle burn-in
  • When you need Hebrew platform-specific captions for Instagram Reels, TikTok, X, and LinkedIn for podcast clips
  • When cleaning up a back catalog of episodes that lack proper chapter markers or show notes
  • When publishing to Apple Podcasts for the first time and need an RSS feed with chapters.json

Try These Prompts

Build full bundle

I have a 47-minute Hebrew podcast Whisper transcript. Build me the full bundle: RTL show notes, a chapters.json file, 4 sixty-second clips with FFmpeg commands, and Instagram/TikTok/X/LinkedIn captions for each clip.

Just the chapters

I have an existing episode with show notes but no chapter markers. Take the attached transcript, identify 6-10 natural chapters, and output both the Spotify format (to paste into the description) and chapters.json for the RSS feed.

Clip picker

From the attached transcript, pick the 3 most shareable 30-90 second segments. Give me a score for each with reasoning, and generate FFmpeg commands to extract them from episode-12.mp3.

Burn-in subtitles

I have a Hebrew SRT file and an MP4 video of a clip. Give me an FFmpeg command to burn the subtitles onto the video with proper RTL handling, Heebo font, and positioning that will not be covered by Instagram Reels UI.

Frequently Asked Questions

Changelog

v1.1.0

Fixed silent failure in default Homebrew FFmpeg install (the default formula no longer includes libass/FriBidi/HarfBuzz; use homebrew-ffmpeg/ffmpeg). Added Examples section. Documented Apple Podcasts Hebrew transcript limitation. Restored SKILL_HE.md template parity.

Apr 28, 2026

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