SKILL.md
Blog Audio: Gemini TTS Narration for Blog Posts
Generate professional audio narration of blog content using Google's Gemini TTS.
Three modes: summary (200-300 word spoken overview), full article read-aloud,
or two-speaker podcast dialogue. 30 voices, 80+ languages, HTML5 embed output.
Quick Reference
| Command | What it does |
|---|---|
/blog audio generate | Generate audio narration of a blog post |
/blog audio voices | Show available voices with characteristics |
/blog audio setup | Check/configure API key for Gemini TTS |
Prerequisites
- Python 3.11+ (venv managed automatically by
run.py)
GOOGLE_AI_API_KEYenvironment variable (same key used by blog-image)
- FFmpeg (for WAV-to-MP3 conversion; falls back to WAV if missing)
Always Use run.py Wrapper
# CORRECT:
python3 scripts/run.py generate_audio.py --text "..." --voice Charon --json
# WRONG:
python3 scripts/generate_audio.py --text "..." # Fails without venv
API Key Check (Gate Pattern)
Before generating audio, check for the API key:
test -n "${GOOGLE_AI_API_KEY:-}" && echo "GOOGLE_AI_API_KEY is set" || echo "GOOGLE_AI_API_KEY is not set"
- If set: proceed with generation
- If not set: guide the user:
"Audio generation requires a Google AI API key. Get one free at https://aistudio.google.com/apikey
Then set it: export GOOGLE_AI_API_KEY=your-key
This can be the same key used by /blog image, but it must be exported in the shell."
- When called internally (from blog-write): return silently if key is missing.
Never block the writing workflow.
Setup
For /blog audio setup:
- Check if
GOOGLE_AI_API_KEYis set in environment
- If blog-image uses project
.mcp.json, confirm the referenced env var is exported
- If not, guide user to https://aistudio.google.com/apikey
- Verify with a dry run:
python3 scripts/run.py generate_audio.py --text "Test" --dry-run --json
Voice Selection
For /blog audio voices:
Load references/voices.md and present the voice catalog to the user.
Ask the user which voice they prefer, or recommend based on content type:
- Article narration: Charon (Informative) or Sadaltager (Knowledgeable)
- Tutorial/how-to: Achird (Friendly) or Sulafat (Warm)
- News/analysis: Rasalgethi (Informative) or Schedar (Even)
- Lifestyle/wellness: Aoede (Breezy) or Vindemiatrix (Gentle)
- Dialogue host: Puck (Upbeat) or Laomedeia (Upbeat)
- Dialogue expert: Kore (Firm) or Charon (Informative)
Generation Workflow
For /blog audio generate <file>:
Step 1: Read the Blog Post
Read the file and extract:
- Title (from H1 or frontmatter)
- Full content (markdown body)
- Approximate word count
Step 2: Choose Mode
Ask the user (or auto-select if they specified --mode):
| Mode | When to use | Output |
|---|---|---|
| Summary | Quick audio overview (1-2 min) | 200-300 word spoken summary |
| Full | Complete read-aloud (5-15 min) | Full article as natural speech |
| Dialogue | Podcast-style (3-8 min) | Two-person conversation about the article |
Step 3: Prepare Text
Claude prepares the text; the script does TTS only.
Summary mode:
Write a 200-300 word spoken summary of the article. Rules:
- Write as natural speech, not written text
- Open with the article's key finding or answer
- Cover 3-5 main takeaways
- Close with actionable advice
- No markdown, no "In this article...", no meta-commentary
- Use conversational transitions ("Here's what matters...", "The key finding is...")
Full mode:
Strip the markdown content to clean spoken text:
- Headings become natural transitions ("Next, let's look at...")
- Links become plain text (remove URLs, keep anchor text)
- Images and charts: omit or briefly describe ("As the data shows...")
- Code blocks: describe verbally ("The code uses a for-loop to...")
- Lists: convert to natural sentences
- Remove frontmatter, schema markup, HTML tags
- Add brief intro: "This is [title], published on [date]."
Dialogue mode:
Write a 2-person conversation script about the article:
- Speaker1 = Host (curious, asks good questions)
- Speaker2 = Expert (knowledgeable, gives clear answers)
- Format each line as:
Speaker1: What's the key takeaway here?
- Cover the article's main points conversationally
- 15-25 exchanges (produces ~3-8 minutes)
- Natural, not stilted ("That's a great point" over "Indeed, as the research indicates")
Step 4: Select Voice
If the user chose a voice, use it. Otherwise, recommend based on mode:
- Summary/Full: default to Charon (Informative)
- Dialogue: default to Puck (Host) + Kore (Expert)
Step 5: Generate Audio
Write the prepared text to a file under the working directory, then call:
# Single voice (summary or full mode)
python3 scripts/run.py generate_audio.py \
--text-file blog_audio_prepared.txt \
--voice Charon \
--model flash \
--output audio/post-slug.mp3 \
--json
# Two voices (dialogue mode)
python3 scripts/run.py generate_audio.py \
--text-file blog_audio_dialogue.txt \
--voice Puck \
--voice2 Kore \
--model pro \
--output audio/post-slug-dialogue.mp3 \
--json
Model selection:
flash(default): maps togemini-3.1-flash-tts-preview, good for summaries and standard narration.
flash31: explicit alias forgemini-3.1-flash-tts-preview.
legacy-flash25: retained only for older compatibility.
proorlegacy-pro25: maps togemini-2.5-pro-preview-tts, use only when needed.
Step 6: Deliver
Present the result to the user:
- File path: where the audio was saved
- Duration: human-readable (e.g., "3:42")
- Embed code: ready-to-paste HTML5 audio tag
- Cost: estimated API cost
- Placement suggestion: where to insert the embed in the blog post
Embedding Guide
Standard HTML (Hugo, Jekyll, static sites)
<audio controls preload="metadata">
<source src="audio/post-slug.mp3" type="audio/mpeg">
Your browser does not support the audio element.
</audio>
MDX (Next.js, Gatsby)
<audio controls preload="metadata">
<source src="/audio/post-slug.mp3" type="audio/mpeg" />
</audio>
WordPress
[audio src="audio/post-slug.mp3"]
Placement
Insert the audio player after the introduction (below the first H2) or at the
very top of the article with a label: "Listen to this article" or "Audio version".
Internal API (for blog-write)
When invoked internally from blog-write:
Input:
text: Prepared text (already cleaned by Claude)
voice: Voice name (default: Charon)
voice2: Second voice for dialogue (optional)
model: flash or pro
output_path: Where to save the file
Output:
### Audio Narration
- **Path:** /path/to/audio/post-slug.mp3
- **Duration:** 3:42
- **Voice:** Charon
- **Embed:** `<audio controls preload="metadata"><source src="audio/post-slug.mp3" type="audio/mpeg"></audio>`
Graceful fallback: If GOOGLE_AI_API_KEY is not set, return immediately
with no error. The writing workflow continues without audio. Never block
blog-write because audio generation is unavailable.
Error Handling
| Error | Resolution |
|---|---|
| GOOGLE_AI_API_KEY not set | Get key at https://aistudio.google.com/apikey |
| FFmpeg not found | Install: sudo apt install ffmpeg. Falls back to WAV output. |
| Rate limited | Wait and retry. Check limits at https://aistudio.google.com/rate-limit |
| Text too long (>8,192 input tokens) | Split into sections around 7,800 tokens; the script chunks and stitches prepared text |
| Unknown voice name | Run /blog audio voices to see valid options |
| API error | Check key validity and model availability |
| API key missing (internal call) | Return silently: writing workflow continues |
Reference Documentation
Load on-demand: do NOT load all at startup:
references/voices.md: Full 30-voice catalog, recommendations by content type, dialogue pairings