podcast-generation

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkDeclared2 observations
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

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

return base64.b64decode(audio_data)

return bytes.fromhex(audio_hex)

Audit 0.4.1 · source sha a45786078c64 · 31 Oct 2026Report an issue or request a re-scan

• Publisherbytedance GitHub organizationOwner of the repository this skill is read from
• Source folderbytedance/deer-flow/skills/public/podcast-generationThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdicta45786078c64A new audit runs when the source changes
• Repository statusNot archivedPushed today
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its 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.

---
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:
```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 fi

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/bytedance/deer-flow
git -C deer-flow checkout a45786078c64

Works in

1. 2026-10-31
   !CAUTION B 89 / 100

   first audit · source a45786078c64

Questions about podcast-generation

• github.com/bytedance/deer-flow/tree/main/skills/public/podcast-g — the audited source at commit a45786078c64 and every finding aboveObserved · 31 Oct 2026

Spotted something wrong? Report a correction · Methodology