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SaberAloui
SaberAlouiCOMMUNITY
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podcast-marketing

Repurpose podcast episodes into social posts, show notes, quote cards, and video clips.

Updated Jul 10, 2026
Search Tags:#social media#transcription#content repurposing#marketing automation#podcast#video clips#quote cards
One-click install
npx skills add https://github.com/SaberAloui/agri-hub --skill podcast-marketing-saberaloui
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: podcast-marketing
Source: https://github.com/SaberAloui/agri-hub/tree/main/.local/secondary_skills/podcast-marketing
Command: npx skills add https://github.com/SaberAloui/agri-hub --skill podcast-marketing-saberaloui

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires youtube-transcript-api, yt-dlp, openai, anthropic, Pillow, feedparser, requests, pydub, numpy, moviepy.

What problem does it solve? Turning a single podcast episode into a full week of marketing content normally requires hours of manual writing, editing, and reformatting across platforms. This Skill automates that repurposing pipeline from transcript to publishable content. ## Core Features & Use Cases - Content Atom Extraction: Analyzes transcripts to extract 7 types of scored content atoms (narrative arcs, quotable moments, controversial takes, data points, frameworks, stories, predictions) with timestamps and viral scoring. - Multi-Platform Content Generation: Produces show notes, blog posts, Twitter threads, LinkedIn posts, Instagram captions, newsletters, and pull quotes, each leading with a unique angle. - Visual & Video Assets: Generates quote card images in three sizes and Opus Clips-style vertical video clips with animated word-by-word captions. - Use Case: Paste a YouTube link to a podcast episode and receive a complete content package — show notes, a blog post, platform-specific social posts, quote cards, short-form video clips, and a scheduled content calendar. ## Quick Start Repurpose this podcast episode from the attached transcript into show notes, a Twitter thread, a LinkedIn post, and pull quotes.

Frequently Asked Questions about podcast-marketing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn a podcast episode into social media content?▼

Provide an RSS feed, transcript file, or YouTube link. The pipeline extracts scored content atoms from the transcript, then generates a Twitter thread, LinkedIn post, Instagram caption, blog post, newsletter, and pull quotes, each leading with a different angle.

How to create short-form video clips from a podcast episode?▼

The pipeline uses scored content atoms with timestamps to select 30-90 second moments, trims them with ffmpeg, reformats to 9:16 vertical, and adds captions. With an OpenAI API key, Whisper provides word-level timestamps for animated word-by-word captions.

Can I process a YouTube podcast episode without downloading audio?▼

Yes. The pipeline first tries fetching YouTube's auto-generated or manual captions via youtube-transcript-api, which is fast and needs no API key. Audio download with yt-dlp and Whisper transcription is only a fallback when captions are unavailable.

What input formats does podcast transcript processing support?▼

Four input modes are supported: podcast RSS feeds, raw transcript files (plain text, SRT, or VTT), YouTube video links, and batch mode processing the last N episodes from a feed. SRT and VTT files preserve timestamps for show notes.

Why do generated video clips have garbled or overlapping captions?▼

YouTube auto-generated transcript segments have overlapping time ranges that produce garbled text with SRT-based rendering. The pipeline solves this by treating segments as sequential text anchored to start times and rendering captions with drawtext filters instead.

What are the limitations of the quote card and video clip generation?▼

Quote cards require Pillow and system fonts. Basic video clips require ffmpeg and yt-dlp. Animated word-by-word captions additionally require an OpenAI API key for Whisper word-level timestamps; without it, clips fall back to static segment-level captions.

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