Transform Xiaoyuzhou Podcasts into Structured Markdown Notes

Transform Xiaoyuzhou Podcasts into Structured Markdown Notes with Ease

Unlock the power of streamlined podcast analysis with our specialized skill that effortlessly converts Xiaoyuzhou FM episodes into organized Markdown notes. Experience a seamless workflow from episode parsing to structured note generation, all tailored to your podcast processing needs.

What This Skill Does

Our skill transforms Xiaoyuzhou FM podcast episodes into structured notes in just a few steps:

• Data Extraction: Parse the podcast episode link to retrieve vital details such as the episode title, podcast name, publication date, duration, direct audio link, shownotes, and chapters. If an official transcript is available, it is automatically utilized.
• Transcription: If no official transcript exists, audio files are downloaded, and an accurate transcription is generated.
• Content Classification: Determine the content type, such as finance, technology, business, interviews, general knowledge, or general content, using cues from the podcast name, shownotes, and the beginning of the transcription. If unclear, prompt user input.
• Note Creation: Populate the chosen template with the transcription and shownotes content, producing a ready-to-use Markdown note.
• File Output: Deliver two comprehensive files to the user: a detailed Markdown note and a transcript in text format.

Use Cases

• Automatically transcribe and summarize a Xiaoyuzhou episode when a user provides a podcast link.
• Organize existing audio files or transcripts into structured notes according to content type.
• Batch process and catalog multiple episodes of a podcast series for efficient data reuse and reference.

Technical Details

• ASR (Automated Speech Recognition): Utilizes advanced transcription processes to capture audio content accurately.
• AI Application Integration: Seamlessly integrates with Claude Code, Cursor, and Codex for optimal coding agent functionality.
• Xiaoyuzhou Podcast Notes: Specifically tailored features for handling Xiaoyuzhou FM podcast episodes.

Revolutionize your coding workflow by converting podcast episodes into actionable data with our targeted AI-driven solution. Ideal for developers and teams leveraging AI coding agents, this skill supports efficient podcast analysis and management.

Source & Licence

This package is built on open-source work published by weisi-gu (weisi-gu/xiaoyuzhou-podcast-notes) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.