Podcast Generation Skill

Overview

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.

Core Capabilities

• Convert any text content (articles, reports, documentation) into podcast scripts

• Generate natural two-host conversational dialogue (male and female hosts)

• Synthesize speech audio using text-to-speech

• Mix audio chunks into a final podcast MP3 file

• Support both English and Chinese content

Workflow

Step 1: Understand Requirements

When a user requests podcast generation, identify:

• Source content: The text/article/report to convert into a podcast

• Language: English or Chinese (based on content)

• Output location: Where to save the generated podcast

• You don't need to check the folder under /mnt/user-data

Step 2: Create Structured Script JSON

Generate a structured JSON script file in /mnt/user-data/workspace/ with naming pattern: {descriptive-name}-script.json

The JSON structure:

{ "locale": "en", "lines": [ {"speaker": "male", "paragraph": "dialogue text"}, {"speaker": "female", "paragraph": "dialogue text"} ] }

Step 3: Execute Generation

Call the Python script:

python /mnt/skills/public/podcast-generation/scripts/generate.py
--script-file /mnt/user-data/workspace/script-file.json
--output-file /mnt/user-data/outputs/generated-podcast.mp3
--transcript-file /mnt/user-data/outputs/generated-podcast-transcript.md

Parameters:

• --script-file : Absolute path to JSON script file (required)

• --output-file : Absolute path to output MP3 file (required)

• --transcript-file : Absolute path to output transcript markdown file (optional, but recommended)

[!IMPORTANT]

• Execute the script in one complete call. Do NOT split the workflow into separate steps.

• The script handles all TTS API calls and audio generation internally.

• Do NOT read the Python file, just call it with the parameters.

• Always include --transcript-file to generate a readable transcript for the user.

Script JSON Format

The script JSON file must follow this structure:

{ "title": "The History of Artificial Intelligence", "locale": "en", "lines": [ {"speaker": "male", "paragraph": "Hello Deer! Welcome back to another episode."}, {"speaker": "female", "paragraph": "Hey everyone! Today we have an exciting topic to discuss."}, {"speaker": "male", "paragraph": "That's right! We're going to talk about..."} ] }

Fields:

• title : Title of the podcast episode (optional, used as heading in transcript)

• locale : Language code - "en" for English or "zh" for Chinese

• lines : Array of dialogue lines

• speaker : Either "male" or "female"

• paragraph : The dialogue text for this speaker

Script Writing Guidelines

When creating the script JSON, follow these guidelines:

Format Requirements

• Only two hosts: male and female, alternating naturally

• Target runtime: approximately 10 minutes of dialogue (around 40-60 lines)

• Start with the male host saying a greeting that includes "Hello Deer"

Tone & Style

• Natural, conversational dialogue - like two friends chatting

• Use casual expressions and conversational transitions

• Avoid overly formal language or academic tone

• Include reactions, follow-up questions, and natural interjections

Content Guidelines

• Frequent back-and-forth between hosts

• Keep sentences short and easy to follow when spoken

• Plain text only - no markdown formatting in the output

• Translate technical concepts into accessible language

• No mathematical formulas, code, or complex notation

• Make content engaging and accessible for audio-only listeners

• Exclude meta information like dates, author names, or document structure

Podcast Generation Example

User request: "Generate a podcast about the history of artificial intelligence"

Step 1: Create script file /mnt/user-data/workspace/ai-history-script.json :

{ "title": "The History of Artificial Intelligence", "locale": "en", "lines": [ {"speaker": "male", "paragraph": "Hello Deer! Welcome back to another fascinating episode. Today we're diving into something that's literally shaping our future - the history of artificial intelligence."}, {"speaker": "female", "paragraph": "Oh, I love this topic! You know, AI feels so modern, but it actually has roots going back over seventy years."}, {"speaker": "male", "paragraph": "Exactly! It all started back in the 1950s. The term artificial intelligence was actually coined by John McCarthy in 1956 at a famous conference at Dartmouth."}, {"speaker": "female", "paragraph": "Wait, so they were already thinking about machines that could think back then? That's incredible!"}, {"speaker": "male", "paragraph": "Right? The early pioneers were so optimistic. They thought we'd have human-level AI within a generation."}, {"speaker": "female", "paragraph": "But things didn't quite work out that way, did they?"}, {"speaker": "male", "paragraph": "No, not at all. The 1970s brought what's called the first AI winter..."} ] }

Step 2: Execute generation:

python /mnt/skills/public/podcast-generation/scripts/generate.py
--script-file /mnt/user-data/workspace/ai-history-script.json
--output-file /mnt/user-data/outputs/ai-history-podcast.mp3
--transcript-file /mnt/user-data/outputs/ai-history-transcript.md

This will generate:

• ai-history-podcast.mp3 : The audio podcast file

• ai-history-transcript.md : A readable markdown transcript of the podcast

Specific Templates

Read the following template file only when matching the user request.

• Tech Explainer - For converting technical documentation and tutorials

Output Format

The generated podcast follows the "Hello Deer" format:

• Two hosts: one male, one female

• Natural conversational dialogue

• Starts with "Hello Deer" greeting

• Target duration: approximately 10 minutes

• Alternating speakers for engaging flow

Output Handling

After generation:

• Podcasts and transcripts are saved in /mnt/user-data/outputs/

• Share both the podcast MP3 and transcript MD with user using present_files tool

• Provide brief description of the generation result (topic, duration, hosts)

• Offer to regenerate if adjustments needed

Requirements

The following environment variables must be set:

• VOLCENGINE_TTS_APPID : Volcengine TTS application ID

• VOLCENGINE_TTS_ACCESS_TOKEN : Volcengine TTS access token

• VOLCENGINE_TTS_CLUSTER : Volcengine TTS cluster (optional, defaults to "volcano_tts")

Notes

• Always execute the full pipeline in one call - no need to test individual steps or worry about timeouts

• The script JSON should match the content language (en or zh)

• Technical content should be simplified for audio accessibility in the script

• Complex notations (formulas, code) should be translated to plain language in the script

• Long content may result in longer podcasts