academic-deep-research
Use this skill for academic reports, literature reviews, experiment reports, user-selected reference styles, innovation-point…
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 Citrus-bit/Anaxa --skill podcast-generation --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/podcast-generationContext 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.
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.
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.
When a user requests podcast generation, identify:
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"}
]
}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:
> [!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 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:
When creating the script JSON, follow these guidelines:
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:
Read the following templat
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