/blog-audio
Generate audio narration of blog posts using Google Gemini TTS. Supports summary narration, full article read-aloud, and two-speaker podcast/dialogue mode with 30 voice options. Outputs MP3 with HTML5 audio embed code. Works standalone via /blog audio or internally from
$ npx -y skills add AgriciDaniel/claude-blog --skill blog-audio --agent claude-codeHow it fires
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- Slash command
/blog-audio
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The summary Claude sees to decide when to auto-load this skill.
Generate audio narration of blog posts using Google Gemini TTS. Supports summary narration, full article read-aloud, and two-speaker podcast/dialogue mode with 30 voice options. Outputs MP3 with HTML5 audio embed code. Works standalone via /blog audio or internally from
SKILL.md
blog-audio.SKILL.mdname: blog-audio
description: >
Generate audio narration of blog posts using Google Gemini TTS.
Supports summary narration, full article read-aloud, and two-speaker
podcast/dialogue mode with 30 voice options. Outputs MP3 with HTML5
audio embed code. Works standalone via /blog audio or internally from
blog-write. Falls back gracefully when API key is not configured.
Use when user says "blog audio", "narrate blog", "audio version",
"text to speech", "tts", "podcast mode", "read aloud", "audio narration",
"voice", "narration", "generate audio".
user-invokable: true
argument-hint: "[generate|voices|setup] [file-or-text] [--mode summary|full|dialogue] [--voice name]"
license: MIT
metadata:
author: AgriciDaniel
version: "2.1.1"
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 <file>` | 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_KEY` environment 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`:
1. Check if `GOOGLE_AI_API_KEY` is set in environment 2. If blog-image uses project `.mcp.json`, confirm the referenced env var is exported 3. If not, guide user to https://aistudio.google.com/apikey 4. 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 selectio
Read more
name: blog-audio description: > Generate audio narration of blog posts using Google Gemini TTS. Supports summary narration, full article read-aloud, and two-speaker podcast/dialogue mode with 30 voice options. Outputs MP3 with HTML5 audio embed code. Works standalone via /blog audio or internally from blog-write. Falls back gracefully when API key is not configured. Use when user says "blog audio", "narrate blog", "audio version", "text to speech", "tts", "podcast mode", "read aloud", "audio narration", "voice", "narration", "generate audio". user-invokable: true argument-hint: "[generate|voices|setup] [file-or-text] [--mode summary|full|dialogue] [--voice name]" license: MIT metadata: author: AgriciDaniel version: "2.1.1"
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 <file>` | 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_KEY` environment 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`:
1. Check if `GOOGLE_AI_API_KEY` is set in environment 2. If blog-image uses project `.mcp.json`, confirm the referenced env var is exported 3. If not, guide user to https://aistudio.google.com/apikey 4. 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 selectio
claude-blog is a Claude Code skill suite that writes, optimizes, audits, localizes, and refreshes blog content at scale. Every article is evaluated for Google-aligned usefulness and internal AI citation readiness heuristics.
Repo: AgriciDaniel/claude-blog
Other skills on claude-blog.
- /blog-analyze
Audit and score blog posts on a 5-category 100-point scoring system covering content quality, SEO optimization, E-E-A-T signals, technical elements, and AI citation readiness. Includes advisory editorial style diagnostics (sentence-length variation, configured phrase lists,
Open skill - /blog-audit
Full-site blog health assessment scanning all blog files for quality scores, orphan pages, topic cannibalization, stale content, and AI citation readiness. Runs canonical batch analysis before site-wide checks. Produces per-post scores and a prioritized action queue. Use when
Open skill - /blog-brand
Establish durable brand and voice context for cross-skill consumption. Generates BRAND.md (audience, positioning, do/don't editorial rules, taboo phrases, competitor differentiation) and VOICE.md (existing persona JSON re-expressed as readable prose), both written to the project
Open skill - /blog-brief
Generate detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts,
Open skill - /blog-calendar
Generate editorial calendars for blogs with topic clusters, publishing schedules, material-change reviews, update plans, seasonal opportunities, content mix formula, template integration, and distribution scheduling. Plans monthly or quarterly calendars around reader needs,
Open skill - /blog-cannibalization
Detect keyword cannibalization across blog posts by extracting primary keywords from titles and headings, clustering semantically similar targets, and flagging posts competing for the same search intent. Supports local-only mode (grep-based) and DataForSEO API mode (Page
Open skill

