/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.
$ npx -y skills add bytedance/deer-flow --skill podcast-generation --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/podcast-generation
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
podcast-generation.SKILL.mdname: podcast-generation
description: 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.
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. > - 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:
{
"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 fi
Read more
name: podcast-generation description: 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.
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. > - 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:
{
"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 fi
On February 28th, 2026, DeerFlow claimed the 🏆 #1 spot on GitHub Trending following the launch of version 2. Thanks a million to our incredible community — you made this happen!
Repo: bytedance/deer-flow
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