podcast-generation
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
What this skill does
# 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:
```json
{
"locale": "en",
"lines": [
{"speaker": "male", "paragraph": "dialogue text"},
{"speaker": "female", "paragraph": "dialogue text"}
]
}
```
### Step 3: Execute Generation
Call the Python script:
```bash
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.
> - The TTS provider and its concurrency are selected automatically from environment variables — you do not choose or tune them.
## Script JSON Format
The script JSON file must follow this structure:
```json
{
"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`:
```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:
```bash
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](templates/tech-explainer.md) - 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:
- For Volcengine: `VOLCENGINE_TTS_APPID` and `VOLCENGINE_TTS_ACCESS_TOKEN`
- For MiniMax: `MINIMAX_API_KEY`
- `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
## Providers (Volcengine / MiniMax)
Auto-selected by environment variables:
- `VOLCENGINE_TTS_APPID` + `VOLCENGINE_TTS_ACCESS_TOKEN` set → Volcengine TTS (default).
- Only `MINIMAX_API_KEY` set → MiniMax TTS (`/v1/t2a_v2`).
- Force with `PODCAST_GENERATION_PROVIDER=volcengine|minimax`.
MiniMax overrides: `MINIMAX_API_HOST` (default `https://api.minimaxi.com`),
`MINIMAX_TTS_MODEL` (default `speech-2.6-hd`), `MINIMAX_TTS_VOICE_MALE`
(default `male-qn-qingse`), `MINIMAX_TTS_VOICE_FEMALE` (default `female-tianmei`).
Concurrency is owned by each provider internally — MiniMax runs single-threaded
to reduce rate-limit failures, Volcengine uses 4 workers. There is no
caller-facing concurrency knob; transient rate limits areRelated in Image & Video
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