podcast▌

Multi-source content processor for NotebookLM, converting various formats like WeChat articles, web pages, and podcasts into structured outputs.

Generate podcast episodes with 1-2 AI speakers discussing a topic. Supports quick overviews, deep analysis, and debate formats. Input can be a topic description, URL(s), or text. Output is a full audio episode with transcript.

Guides podcast strategy, content creation, distribution, marketing, and SEO. Podcasts compete in a crowded space (3M+ active shows, 500M+ listeners globally); discoverability is the primary challenge. Discovery channels: ~32% search engines, ~28% podcast apps, ~24% social media, ~16% word-of-mouth.

Comprehensive skill for automating podcast production and distribution.

Create AI-powered podcasts and audio content via inference.sh CLI.

This skill generates high-quality podcast audio from text content. The workflow includes creating a structured JSON script (conversational dialogue) and executing audio generation through text-to-speech synthesis.

Multi-voice podcast and audiobook production with TTS, AI music, and audio merging. \n \n Supports three TTS engines (Kokoro, DIA, Chatterbox) with 6+ voice options across American, British, and conversational styles \n Includes AI music generation for intros, outros, and background tracks; media merger handles crossfades and layering \n Workflows cover single narration, multi-voice dialogue, full episode pipelines, and NotebookLM-style document discussions \n Integrates with Claude for script g