refactor: simplify podcast-generation to use direct JSON script input

- Remove LLM script generation from Python script, model now generates
  JSON script directly (similar to image-generation skill)
- Add --transcript-file option to generate markdown transcript
- Add optional "title" field in JSON for transcript heading
- Remove dependency on OPENAI_API_KEY for podcast generation
- Update SKILL.md with new workflow and JSON format documentation

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

skills/public/podcast-generation/SKILL.md

@@ -7,7 +7,7 @@ description: Use this skill when the user requests to generate, create, or produ
 
 ## Overview
 
-This skill generates high-quality podcast audio from text content using a multi-stage pipeline. The workflow includes script generation (converting input to conversational dialogue), text-to-speech synthesis, and audio mixing to produce the final podcast.
+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
 
@@ -24,64 +24,127 @@ This skill generates high-quality podcast audio from text content using a multi-
 When a user requests podcast generation, identify:
 
 - Source content: The text/article/report to convert into a podcast
-- Language: English or Chinese (auto-detected from content)
+- 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: Prepare Input Content
+### Step 2: Create Structured Script JSON
 
-The input content should be plain text or markdown. Save it to a text file in `/mnt/user-data/workspace/` with naming pattern: `{descriptive-name}-content.md`
+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 directly without any concerns about timeout or the need for pre-testing:
-
+Call the Python script:
 ```bash
 python /mnt/skills/public/podcast-generation/scripts/generate.py \
-  --input-file /mnt/user-data/workspace/content-file.md \
+  --script-file /mnt/user-data/workspace/script-file.json \
   --output-file /mnt/user-data/outputs/generated-podcast.mp3 \
-  --locale en
+  --transcript-file /mnt/user-data/outputs/generated-podcast-transcript.md
 ```
 
 Parameters:
 
-- `--input-file`: Absolute path to input text/markdown file (required)
+- `--script-file`: Absolute path to JSON script file (required)
 - `--output-file`: Absolute path to output MP3 file (required)
-- `--locale`: Language locale - "en" for English or "zh" for Chinese (optional, auto-detected if not specified)
+- `--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 (e.g., testing script generation first, then TTS).
-> - The script handles all external API calls and audio generation internally with proper timeout management.
+> - 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:
+
+```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 content file `/mnt/user-data/workspace/ai-history-content.md` with the source text:
-```markdown
-# The History of Artificial Intelligence
-
-Artificial intelligence has a rich history spanning over seven decades...
-
-## Early Beginnings (1950s)
-The term "artificial intelligence" was coined by John McCarthy in 1956...
-
-## The First AI Winter (1970s)
-After initial enthusiasm, AI research faced significant setbacks...
-
-## Modern Era (2010s-Present)
-Deep learning revolutionized the field with breakthrough results...
+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 \
-  --input-file /mnt/user-data/workspace/ai-history-content.md \
+  --script-file /mnt/user-data/workspace/ai-history-script.json \
   --output-file /mnt/user-data/outputs/ai-history-podcast.mp3 \
-  --locale en
+  --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.
@@ -101,15 +164,14 @@ The generated podcast follows the "Hello Deer" format:
 
 After generation:
 
-- Podcasts are saved in `/mnt/user-data/outputs/`
-- Share generated podcast with user using `present_files` tool
+- 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:
-- `OPENAI_API_KEY` or equivalent LLM API key for script generation
 - `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")
@@ -117,8 +179,7 @@ The following environment variables must be set:
 ## Notes
 
 - **Always execute the full pipeline in one call** - no need to test individual steps or worry about timeouts
-- Input content language is auto-detected and matched in output
-- The script generation uses LLM to create natural conversational dialogue
-- Technical content is automatically simplified for audio accessibility
-- Complex notations (formulas, code) are translated to plain language
+- 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