Speak Tts

speak - Talk to your Claude!

Give your agent the ability to speak to you real-time. Local text-to-speech, voice cloning, and audio generation on Apple Silicon. Give your agent the ability to speak to you real-time. Local TTS with voice cloning on Apple Silicon.

Prerequisites

Input Sources

Web Articles

lynx -dump -nolist "https://example.com/article" | speak --output article.wav

Converting Formats

Output Modes

Default Behavior

speak article.txt          # → ~/Audio/speak/article.wav (no playback)
speak "Hello"              # → ~/Audio/speak/speak_<timestamp>.wav

Directory Auto-Creation

Always create custom directories first:

mkdir -p ~/.chatter/voices/
mkdir -p ~/Audio/custom/

Voice Cloning

Voice cloning generates speech that matches your vocal characteristics (pitch, tone, cadence) from a short recording.

Quality Expectations

• Output captures general voice characteristics but is not a perfect replica
• Quality depends heavily on sample quality
• 15-25 seconds is optimal (10s minimum, 30s maximum)

Recording Your Voice

Using QuickTime: 1. Open QuickTime Player → File → New Audio Recording 2. Record 20 seconds of clear speech 3. File → Export As → Audio Only (.m4a) 4. Convert to WAV (see below)

Using sox (command line):

# -d = use default microphone
# Recording starts immediately and stops after 25 seconds
sox -d -r 24000 -c 1 ~/.chatter/voices/my_voice.wav trim 0 25

Converting to Required Format

Voice samples MUST be: WAV, 24000 Hz, mono, 10-30 seconds.

# From MP3
ffmpeg -i voice.mp3 -ar 24000 -ac 1 voice.wav

# From M4A (QuickTime)
ffmpeg -i voice.m4a -ar 24000 -ac 1 voice.wav

# Trim to 25 seconds
ffmpeg -i long.wav -t 25 -ar 24000 -ac 1 trimmed.wav

# Check sample properties
ffprobe -i voice.wav 2>&1 | grep -E "Duration|Stream"
# Should show: Duration ~15-25s, 24000 Hz, mono

Using Your Voice

# Create directory
mkdir -p ~/.chatter/voices/

# Move sample
mv voice.wav ~/.chatter/voices/my_voice.wav

# Test
speak "Testing my voice" --voice ~/.chatter/voices/my_voice.wav --stream

# Use for content
speak notes.txt --voice ~/.chatter/voices/my_voice.wav --output presentation.wav

Path requirements:

• ✓ Works: ~/.chatter/voices/my_voice.wav (tilde expanded by shell)
• ✓ Works: /Users/name/.chatter/voices/my_voice.wav
• ✗ Fails: my_voice.wav (relative path)
• ✗ Fails: ./voices/my_voice.wav (relative path)

Voice Sample Tips

Default Voice

When --voice is omitted, a built-in default voice is used:

speak "Hello world" --stream  # Uses default voice

Emotion Tags

Tags produce audible effects (actual sounds), not spoken words:

speak "[sigh] Monday again." --stream
# Output: (sigh sound) "Monday again."

NOT supported: [pause], [whisper] (ignored)

For pauses: Use punctuation: "Wait... let me think."

Batch Processing

mkdir -p ~/Audio/book/
speak ch01.txt ch02.txt ch03.txt --output-dir ~/Audio/book/
# Creates: ch01.wav, ch02.wav, ch03.wav

# With auto-chunking (for long files)
speak chapters/*.txt --output-dir ~/Audio/book/ --auto-chunk

# Skip completed files
speak chapters/*.txt --output-dir ~/Audio/book/ --skip-existing

Auto-Chunk Behavior

When using --auto-chunk with batch processing: 1. Each input file is chunked independently 2. Chunks are generated and automatically concatenated per file 3. Final output: one .wav per input file (e.g., ch01.wav) 4. Intermediate chunks deleted (unless --keep-chunks)

You don't need to manually concatenate chunks — only concatenate final chapter files.

Concatenating Audio

# Explicit order (recommended)
speak concat ch01.wav ch02.wav ch03.wav --output book.wav

# Glob pattern (REQUIRES zero-padded filenames)
speak concat audiobook/*.wav --output book.wav

Zero-Padding Rules

Critical for correct concatenation order:

Why: Shell glob expansion sorts alphabetically. 1, 10, 2 vs 01, 02, 10.

PDF to Audiobook (Complete Workflow)

Step 1: Find Chapter Boundaries

# Preview table of contents
pdftotext -f 1 -l 5 textbook.pdf toc.txt
cat toc.txt  # Note chapter page numbers

# Or search for "Chapter" markers
pdftotext textbook.pdf - | grep -n "Chapter"

Step 2: Extract Chapters (Zero-Padded!)

# For 100-page book with ~10 chapters
pdftotext -f 1 -l 12 -layout textbook.pdf ch01.txt
pdftotext -f 13 -l 25 -layout textbook.pdf ch02.txt
pdftotext -f 26 -l 38 -layout textbook.pdf ch03.txt
# ... continue for all chapters

Step 3: Estimate Time

speak --estimate ch*.txt
# Shows: total audio duration, generation time, storage needed

# Quick estimates:
# 1 page ≈ 2 min audio ≈ 1 min generation
# 100 pages ≈ 200 min audio ≈ 100 min generation ≈ 500 MB

Step 4: Generate Audio

mkdir -p audiobook/
speak ch01.txt ch02.txt ch03.txt --output-dir audiobook/ --auto-chunk
# Creates: audiobook/ch01.wav, audiobook/ch02.wav, audiobook/ch03.wav

Step 5: Concatenate

speak concat audiobook/ch01.wav audiobook/ch02.wav audiobook/ch03.wav --output complete_audiobook.wav
# Or with glob (only if zero-padded):
speak concat audiobook/ch*.wav --output complete_audiobook.wav

PDF Troubleshooting

Multi-Voice Content

mkdir -p podcast/scripts podcast/wav

echo "Welcome to the show." > podcast/scripts/01_host.txt
echo "Thanks for having me." > podcast/scripts/02_guest.txt

speak podcast/scripts/01_host.txt --voice ~/.chatter/voices/host.wav --output podcast/wav/01.wav
speak podcast/scripts/02_guest.txt --voice ~/.chatter/voices/guest.wav --output podcast/wav/02.wav

speak concat podcast/wav/01.wav podcast/wav/02.wav --output podcast.wav

Options Reference

Commands

Performance

Resume Capability

For interrupted long generations:

# Single file with auto-chunk — use --resume
speak long.txt --auto-chunk --output book.wav
# If interrupted, manifest saved at ~/Audio/speak/manifest.json
speak --resume ~/Audio/speak/manifest.json

# Batch processing — use --skip-existing
speak ch*.txt --output-dir audiobook/ --auto-chunk
# If interrupted, re-run same command:
speak ch*.txt --output-dir audiobook/ --auto-chunk --skip-existing

Common Errors

Setup

speak "test"     # Auto-setup on first run (downloads model ~500MB)
speak setup      # Or manual setup
speak health     # Verify everything works

Server Management

Server auto-starts and shuts down after 1 hour idle.

speak health        # Check status
speak daemon kill   # Stop manually

Agentic Engineering Artifacts

This directory contains artifacts from agentic AI-assisted engineering processes applied to the speak project. These are living documents that track how AI agents have contributed to improving the project.

Contents

skill-optimization/

Date: 2026-01-11 Method: Agent Focus Group + Iterative Refinement Protocol Models: Claude Haiku 4.5, Sonnet 4.5, Opus 4.5

Systematic optimization of SKILL.md documentation using multi-model consensus testing. The process ran 5 rounds of focus group testing, evolving both the skill document and the evaluation rubric based on agent feedback.

Key artifacts:

• OPTIMIZATION_REPORT.md — Full report with rubric evolution and improvement summary
• SKILL_OPTIMIZED.md — Final optimized skill document
• iterations/ — All intermediate versions (v0-v5) showing evolution

Outcome: 41% content increase with dramatically improved agent comprehension across all tested tasks (voice cloning, PDF audiobooks, multi-voice podcasts).

---

Purpose

These artifacts serve multiple purposes:

1. Transparency — Document how AI agents contributed to the project 2. Reproducibility — Show the methodology and iterations 3. Learning — Capture what worked and what didn't 4. Evolution — Track ongoing improvements over time

Contributing New Artifacts

When adding new agentic engineering work:

1. Create a subdirectory with descriptive name (e.g., api-redesign/, test-generation/) 2. Include a report summarizing the process and outcomes 3. Preserve intermediate artifacts that show evolution 4. Document the models and methods used

Focus Group Test Runs

Raw output from each Agent Focus Group test run during the SKILL.md optimization process.

Run Index

Models Used

• anthropic/claude-haiku-4.5 — Fast, cost-effective
• anthropic/claude-sonnet-4.5 — Balanced quality/cost
• anthropic/claude-opus-4.5 — Highest quality
• qwen/qwen3-coder:free — Free tier (used in early rounds)

How to Read These Files

Each file contains: 1. Run metadata — Date, skill file, task, status 2. Per-model responses including:

• Understanding — What the model understood
• Approach — How it would complete the task
• Confusions — What was unclear in the docs
• Potential Failures — What could go wrong
• Suggested Improvements — Specific recommendations

Key Insights by Round

Round 1 (v0 → v1)

• PDF support completely missing
• Voice path confusion (relative vs absolute)
• --out vs --output inconsistency
• Prerequisites buried at bottom

Round 2 (v1 → v2)

• Batch + auto-chunk interaction unclear
• Voice availability/default not explained
• Emotion tag behavior ambiguous

Round 3 (v2 → v3)

• Clipboard/URL input not documented
• Default output behavior unclear
• Output mode decision tree needed

Round 4 (v3 → v4)

• Voice cloning workflow incomplete
• Audio format conversion missing
• Sox command unexplained

Round 5 (v4 → v5)

• Minor polish items only
• Directory creation order clarified
• Complete workflows validated

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Run 01KENJ39HF92SV72C333XJAWWY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Date: 2026-01-11T03:37:47.823Z Skill: /Users/jay/Documents/speak_optiimisation/speak/SKILL.md Task: Convert a 50-page PDF manual to an audiobook with chapters Status: completed ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

anthropic/claude-haiku-4.5

Status: success (15.8s, $0.002)

Understanding

The speak-tts tool converts text to speech using Chatterbox TTS on Apple Silicon. Based on the documentation, it can:

• Stream or generate audio files
• Handle long documents with auto-chunking
• Process multiple files in batch mode
• Concatenate audio files
• Use custom voices

For a 50-page PDF manual, the relevant features are: batch processing (--output-dir), auto-chunking for long documents, and concatenation.

Approach

1. Extract text from PDF: Convert the 50-page PDF into separate text files per chapter (the docs don't cover PDF extraction, so I'd need to do this externally)

2. Generate audio per chapter: Use batch processing with auto-chunking:

   speak chapter1.txt chapter2.txt chapter3.txt ... --output-dir ~/Audio/manual/ --auto-chunk

3. Verify generation: Check that all chapter audio files were created in ~/Audio/manual/

4. Concatenate chapters (if a single audiobook file is needed):

   speak concat ~/Audio/manual/chapter1.wav ~/Audio/manual/chapter2.wav ... --out manual_complete.wav

Confusions

1. PDF handling is completely absent: The documentation says "reading articles/documents aloud" and shows .md examples, but provides zero guidance on converting PDF to text. The task requires PDF input, but the tool documentation only shows .md and .txt examples.

2. Batch mode output naming is unclear: The docs show --output-dir ~/Audio/book/ but don't specify what the output filenames will be. Will they be named after input files? Will they be numbered? Quote: "Process multiple files at once" with --output-dir but no explanation of the naming scheme.

3. Auto-chunk behavior with batch mode is undefined: Can you use --auto-chunk with multiple input files simultaneously? The docs show --auto-chunk with single files and batch mode separately, but never together. Will each file be chunked independently?

4. Concatenation syntax is ambiguous: The concat example shows speak concat part1.wav part2.wav part3.wav --out combined.wav but the Options Reference table lists --output <path> not --out. Which flag is correct?

5. Resume with batch processing: If batch processing fails partway through, can you resume? The --resume option is only documented for single files with --auto-chunk.

6. Chapter detection: How do you define "chapters"? The docs don't explain whether the tool auto-detects chapters or if you must manually split the PDF into chapter files first.

Potential Failures

1. PDF extraction: The tool doesn't handle PDFs natively. I'd fail immediately without external tools (pdftotext, pypdf, etc.) to convert the PDF to text files first.

2. Unknown output filenames: Without knowing the naming convention for batch output, I might generate files but not know where they are or how to reference them for concatenation.

3. Combining auto-chunk with batch mode: If I try speak chapter*.txt --output-dir ~/Audio/manual/ --auto-chunk, it might fail or behave unexpectedly since this combination isn't documented.

4. Concatenation flag mismatch: Using --out instead of --output (or vice versa) would fail the concatenation step.

5. Timeout on large chapters: A 50-page manual could have chapters exceeding the 300-second default timeout. Without explicit confirmation that --auto-chunk works in batch mode, I might hit timeouts.

6. Resume capability missing for batch: If processing 50 pages and it fails on chapter 30, I might not be able to resume without reprocessing chapters 1-29.

Suggested Improvements

1. Add PDF support section: Document how to convert PDFs to text, or explicitly state the tool doesn't handle PDFs and recommend external tools:

   ## PDF Input
   This tool requires text input. Convert PDFs to text first:
   - pdftotext manual.pdf manual.txt
   - Or split into chapters: pdftotext -f 1 -l 50 manual.pdf chapter1.txt

2. Clarify batch mode output naming:

   | `--output-dir <dir>` | Output directory for batch mode. Files named as input with .wav extension (e.g., chapter1.txt → chapter1.wav) | - |

3. Document auto-chunk + batch interaction explicitly:

   ### Batch Processing with Auto-Chunking
   speak chapter*.txt --output-dir ~/Audio/manual/ --auto-chunk
   
   Each input file is processed independently with auto-chunking enabled. 
   Output: chapter1.wav, chapter2.wav, etc.

4. Fix concatenation syntax inconsistency: Use --output consistently:

   speak concat part1.wav part2.wav part3.wav --output combined.wav

5. Add batch resume capability:

   If batch processing fails, resume with:
   speak --resume ~/Audio/speak/manifest.json
   
   This resumes from the last incomplete file in the batch.

6. Add a complete 50-page example:

   # Extract chapters from PDF (external tool)
   pdftotext -f 1 -l 10 manual.pdf chapter1.txt
   pdftotext -f 11 -l 20 manual.pdf chapter2.txt
   # ... etc
   
   # Generate audio for all chapters
   speak chapter*.txt --output-dir ~/Audio/manual/ --auto-chunk
   
   # Concatenate into single audiobook
   speak concat ~/Audio/manual/chapter*.wav --output manual_audiobook.wav

7. Clarify Apple Silicon requirement upfront: Add a warning that this tool only works on M1/M2/M3 Macs, not Intel or other platforms.

---

anthropic/claude-opus-4.5

Status: success (32.8s, $0.156)

Understanding

The tool converts text to speech audio using local TTS on Apple Silicon. It can read files, stream audio, generate WAV files, handle long documents via auto-chunking, batch process multiple files, and concatenate audio. It does NOT appear to handle PDFs directly—it seems to expect text/markdown input based on all examples showing .md or .txt files.

Approach

Step 1: Extract text from the PDF The documentation never mentions PDF support. All examples use .md or .txt files. I would need to first convert the PDF to text using an external tool (not documented here), something like:

pdftotext manual.pdf manual.txt
# or split by chapters somehow

Step 2: Split into chapters The docs don't explain how to identify or split chapters. I'd need to manually split the extracted text into separate files:

chapter01.txt
chapter02.txt
...

Step 3: Estimate generation time

speak --estimate chapter01.txt

For a 50-page manual, this could be substantial (maybe 2-4 hours of audio).

Step 4: Generate audio for each chapter

speak chapter01.txt --auto-chunk --output ~/Audio/audiobook/chapter01.wav
speak chapter02.txt --auto-chunk --output ~/Audio/audiobook/chapter02.wav
# ... repeat for all chapters

Or batch process:

speak chapters/*.txt --output-dir ~/Audio/audiobook/ --auto-chunk

Step 5: Concatenate into final audiobook (optional)

speak concat ~/Audio/audiobook/*.wav --out ~/Audio/manual_audiobook.wav

Confusions

1. PDF support is completely unmentioned

• The task says "Convert a 50-page PDF manual" but the docs show zero PDF examples
• All examples use .md or .txt: speak document.md, speak long-book-chapter.md
• Does speak manual.pdf work? I have no idea.

2. Does batch mode support `--auto-chunk`?

• The batch example shows: speak chapters/*.md --output-dir ~/Audio/book/
• The auto-chunk example shows: speak book-chapter.md --auto-chunk --output chapter.wav
• Can I combine them? speak chapters/*.md --output-dir ~/Audio/ --auto-chunk — unclear if this is valid

3. What happens with `--output` vs `--output-dir`?

• Quote: --output <path> — "Output file (.wav) or directory"
• Quote: --output-dir <dir> — "Output directory for batch mode"
• When do I use which? If I pass multiple files, do I use --output-dir or can --output accept a directory?

4. Chapter detection/splitting

• The task mentions "with chapters" but the docs provide no guidance on:
• How to detect chapter boundaries
• Whether the tool can auto-split on headings
• Best practices for organizing multi-chapter content

5. What file formats are supported as input?

• Never explicitly stated. Examples show .md and .txt and quoted strings
• Is there a list of supported input formats?

6. Resume behavior with batch processing

• Quote: speak --resume ~/Audio/speak/manifest.json
• Is a manifest created for batch jobs? Or only for single-file --auto-chunk jobs?

Potential Failures

1. PDF not supported — If I run speak manual.pdf, it might fail entirely or read the raw PDF bytes as text (garbage output)

2. Timeout on large chapters — A 50-page manual might have chapters that exceed the 5-minute timeout even with auto-chunking, depending on chapter length

3. Batch + auto-chunk incompatibility — If these flags don't work together, I'd need to run separate commands for each chapter, which is tedious and error-prone

4. Incorrect output naming — Unclear if batch mode preserves chapter names or uses generic numbering

5. Missing `sox` dependency — Quote: "Requires sox for auto-chunking: brew install sox" — if I don't have this installed, auto-chunking silently fails or errors

6. Disk space — 50 pages of audio could be 3-5 hours. At 24kHz mono WAV, that's potentially 1-2GB. No guidance on expected file sizes.

Suggested Improvements

1. Add explicit "Supported Input Formats" section

   ## Supported Input Formats
   - Plain text (.txt)
   - Markdown (.md)
   - Direct string arguments
   
   **Not supported:** PDF, DOCX, HTML (convert these first using external tools)

2. Add a "PDF to Audiobook" workflow example

   ### Converting PDFs
   This tool does not read PDFs directly. First extract text:

Using pdftotext (install via: brew install poppler)

pdftotext -layout manual.pdf manual.txt

Then generate audio

speak manual.txt --auto-chunk --output manual.wav

3. **Clarify batch + auto-chunk compatibility**

Batch Processing Long Documents

   # Auto-chunk works with batch mode
   speak chapters/*.md --output-dir ~/Audio/book/ --auto-chunk --skip-existing

4. Add chapter-splitting guidance

   ### Splitting Documents into Chapters
   For audiobooks, split your document at chapter boundaries:

Manual approach: create separate files

chapter01.txt, chapter02.txt, etc.

Each chapter becomes a separate audio file

speak chapter*.txt --output-dir ~/Audio/book/

5. **Document output file naming in batch mode**
   - What does `speak a.txt b.txt --output-dir ./out/` produce? `a.wav`, `b.wav`? `001.wav`, `002.wav`?

6. **Add disk space estimates**

Storage Requirements

• ~150 MB per hour of audio (24kHz mono WAV)
• 50-page document ≈ 3-5 hours ≈ 500-750 MB

7. **Make dependency requirements more prominent**
   - Move `sox` requirement to a "Prerequisites" section at the top, not buried in "Notes"

---

## anthropic/claude-sonnet-4.5

**Status:** success (41.6s, $0.035)

## Understanding

The tool is a local TTS system for Apple Silicon that converts text to speech using Chatterbox TTS. It supports streaming, file output, voice cloning, auto-chunking for long documents, batch processing, and concatenation. The tool works with text input (direct strings or files) and outputs WAV audio files.

## Approach

Based on the documentation, here's how I would attempt this task:

1. **Extract text from PDF** - The tool doesn't handle PDFs directly, so I'd need to extract text first (not documented how)
2. **Split into chapter files** - Create separate text files for each chapter (e.g., chapter1.txt, chapter2.txt, etc.)
3. **Estimate total time**: `speak --estimate chapter1.txt` (repeat for each to gauge total)
4. **Generate audio per chapter with auto-chunking**:

speak chapter1.txt --auto-chunk --output audiobook/chapter1.wav speak chapter2.txt --auto-chunk --output audiobook/chapter2.wav

... repeat for all chapters

5. **Or use batch processing** (if it works with --auto-chunk):

speak chapter*.txt --output-dir audiobook/ --auto-chunk

6. **Optionally concatenate all chapters**:

speak concat audiobook/chapter*.wav --out complete_audiobook.wav

## Confusions

1. **PDF handling not documented**: "Convert a 50-page PDF manual" - but the tool only accepts text input. The docs say "reading articles/documents aloud" in the description but never mention PDF support or text extraction. Do I need a separate tool first?

2. **Batch processing + auto-chunk compatibility unclear**: The docs show `speak chapter1.md chapter2.md chapter3.md --output-dir ~/Audio/book/` for batch processing, but never show if `--auto-chunk` works with batch mode. Can I do `speak *.txt --output-dir audiobook/ --auto-chunk`?

3. **Chapter naming in batch mode**: When using `--output-dir`, what are the output files named? The docs say "Process multiple files at once" but don't show the naming convention. Is it `chapter1.wav`, `chapter1.txt.wav`, or something else?

4. **Resume with batch processing**: If batch processing fails partway through, can I resume? The docs only show resume for single-file auto-chunking: `speak --resume ~/Audio/speak/manifest.json`. Does batch mode create a manifest?

5. **Skip-existing behavior**: `--skip-existing` is mentioned but not explained. Does it check if `chapter1.wav` exists and skip `chapter1.txt`? What if the file exists but is incomplete?

6. **50 pages = how many characters?**: The docs give estimates for characters/words but not pages. A 50-page PDF could be 25,000-100,000+ characters depending on formatting. No guidance on estimating from page count.

7. **Timeout with batch processing**: Default timeout is 300s (5 min). If processing 50 chapters in batch mode, does the timeout apply per file or to the entire batch?

## Potential Failures

1. **No PDF input support** - Task requires PDF, tool requires text. I'd fail immediately without external PDF extraction.

2. **Batch + auto-chunk incompatibility** - If these flags don't work together, I'd have to run 50 separate commands manually.

3. **Timeout on long chapters** - Even with `--auto-chunk`, if a single chapter is very long and hits the 300s timeout, it would fail. The docs say auto-chunk helps but don't guarantee it prevents timeouts.

4. **Memory/disk space** - 50 chapters of audio could be 10+ hours. No warning about disk space requirements or memory usage.

5. **Concatenation file limit** - `speak concat audiobook/*.wav` might hit shell argument limits with 50 files. Not documented.

6. **Wrong file order in concat** - `chapter*.wav` would sort as chapter1, chapter10, chapter11... chapter2. I'd need to pad numbers (chapter01.wav) but this isn't mentioned.

7. **Resume doesn't work for batch** - If batch processing fails at chapter 30, I might have to manually figure out where to restart.

## Suggested Improvements

1. **Add PDF handling section**:

Working with PDFs

speak requires text input. For PDFs:

   # Extract text first (requires pdftotext or similar)
   pdftotext document.pdf document.txt
   speak document.txt --auto-chunk --output audiobook.wav

Or use a separate PDF extraction tool before processing.

2. **Clarify batch + auto-chunk compatibility**:

Batch Processing with Auto-Chunking

You can combine batch processing with auto-chunking:

   speak chapter*.txt --output-dir audiobook/ --auto-chunk

Each file is processed independently with its own chunking.

   
   OR explicitly state: "Note: `--auto-chunk` only works with single-file input. For batch processing, each file must fit within the timeout."

3. **Document output naming**:

Batch Output Naming

When using --output-dir, output files match input names:

• chapter1.txt → audiobook/chapter1.wav
• intro.md → audiobook/intro.wav

4. **Add multi-chapter audiobook example**:

Creating Multi-Chapter Audiobooks

For long documents like books:

1. Split into numbered chapter files (use zero-padding):

      chapter_01.txt
      chapter_02.txt
      ...
      chapter_50.txt

2. Generate all chapters:

      speak chapter_*.txt --output-dir audiobook/ --auto-chunk --skip-existing

3. Concatenate in order:

      speak concat audiobook/chapter_*.wav --out complete_book.wav

Tip: Use zero-padded numbers (01, 02...) to ensure correct sort order.

5. **Add timeout guidance for batch**:

| --timeout <sec> | Generation timeout per file in batch mode | 300 |

6. **Add disk space warning**:

Storage Requirements

Audio files are ~2.5 MB per minute of speech:

• 1 hour = ~150 MB
• 10 hours = ~1.5 GB

Ensure adequate disk space before processing long documents.

7. **Improve skip-existing docs**:

| --skip-existing | Skip input files if corresponding output exists (checks by filename, not content) | false |

8. **Add page-to-character estimation**:

Estimating from Page Count

Rough estimates:

• 1 page ≈ 500 words ≈ 2,500 characters ≈ 2 minutes audio
• 50 pages ≈ 125,000 characters ≈ 100 minutes audio ≈ 50 minutes generation

Use --estimate for accurate predictions.

---

## qwen/qwen3-coder:free

**Status:** success (29.5s, $0.004)

## Understanding
The tool is a local text-to-speech system called "speak-tts" that runs on Apple Silicon Macs using Chatterbox TTS and MLX for private, on-device processing. It can convert text to audio in various formats, supports streaming, batch processing, auto-chunking for long documents, and resume capability. It also supports voice cloning and emotion tags.

To complete the task of converting a 50-page PDF manual to an audiobook with chapters, I would need to:
1. Extract text from the PDF
2. Split it into chapters
3. Convert each chapter to audio
4. Combine the chapters into a single audiobook file

However, the documentation doesn't mention PDF handling or text extraction capabilities, which is a critical gap for this task.

## Approach
1. First, I would need to extract text from the PDF manual (this step is not covered by the tool documentation)
2. Split the extracted text into separate files for each chapter
3. Use the speak tool with auto-chunking to generate audio for each chapter:

speak chapter1.txt --auto-chunk --output chapter1.wav --voice ~/.chatter/voices/narrator_voice.wav speak chapter2.txt --auto-chunk --output chapter2.wav --voice ~/.chatter/voices/narrator_voice.wav

4. Concatenate all chapter audio files:

speak concat chapter*.wav --out manual_audiobook.wav

## Confusions
1. The documentation states "Use this when users request converting text to audio, reading articles/documents aloud" but doesn't specify how to handle PDF documents. There's no mention of PDF text extraction capabilities.

2. The documentation says "Runs entirely on-device via MLX for private TTS" but doesn't clarify if this includes handling of various document formats like PDFs.

3. The voice cloning section mentions "Get a clean 10-30 second audio sample" but doesn't specify what constitutes "clean" or the required technical specifications beyond WAV format.

4. The emotion tags section mentions tags like [laugh] and [sigh] but doesn't explain how these would be appropriately applied to technical manual content.

## Potential Failures
1. The task cannot be completed directly with the tool as documented since there's no mention of PDF handling capabilities. The user would need to first convert the PDF to text format.

2. If the PDF has complex formatting, tables, or images with important information, converting to plain text might lose crucial content.

3. The tool might timeout during generation of long chapters despite auto-chunking if the content exceeds the default 5-minute timeout without proper chunking parameters.

4. Without knowing the exact text extraction method needed for the PDF, the quality of the audiobook could be poor if the text isn't properly formatted.

5. The tool requires Apple Silicon, so it would fail entirely on Intel Macs or other platforms.

## Suggested Improvements
1. Add explicit documentation about supported input formats. If PDF is not supported, clearly state this and recommend preprocessing steps:

Note: speak-tts only accepts plain text input. PDF documents must be converted to text format first using tools like pdftotext or Adobe Acrobat's export feature.

2. Include a specific example for converting documents to audiobooks that acknowledges the need for text extraction:

Converting PDF documents to audiobooks

First extract text: pdftotext manual.pdf manual.txt

Then split into chapters and generate audio

speak chapter1.txt --auto-chunk --output chapter1.wav

3. Clarify the voice sample requirements with specific technical details:

Voice samples should be: 24kHz mono WAV files, 10-30 seconds duration, with signal-to-noise ratio >20dB, and minimal background noise.

4. Add a section on preprocessing complex documents:

For technical documents with complex formatting: 1. Extract text preserving heading structure 2. Add appropriate punctuation for natural speech flow 3. Remove or convert special characters that might cause issues

5. Include platform requirements more prominently:

REQUIREMENTS:

• Apple Silicon Mac (M1/M2/M3)
• macOS 12.0 or later
• sox (brew install sox)

---

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Run 01KENJ5YTER3RMHF9DCRMD7XJ3 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Date: 2026-01-11T03:39:15.150Z Skill: /Users/jay/Documents/speak_optiimisation/speak/SKILL.md Task: Create a 3-voice podcast debate about AI safety with host and two guests Status: partial ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

anthropic/claude-haiku-4.5

Status: success (16.0s, $0.002)

Understanding

The tool generates speech audio from text using Chatterbox TTS on Apple Silicon. It supports:

• Basic text-to-speech with streaming or file output
• Custom voice selection via full file paths
• Multi-voice content by splitting scripts, generating separately with different voices, then concatenating
• Emotion tags for expressiveness
• Long document handling with auto-chunking

For this task, I need to: create separate text files for each speaker, generate audio for each with a different voice, then concatenate them.

Approach

1. Create three speaker script files:

• 01_host_intro.txt - Host introduction
• 02_guest1_opening.txt - First guest opening statement
• 03_host_question.txt - Host follow-up question
• 04_guest2_opening.txt - Second guest opening statement
• (Continue alternating as needed)

2. Check available voices:

   ls ~/.chatter/voices/*.wav 2>/dev/null

3. Generate audio for each segment with appropriate voice using full paths:

   speak 01_host_intro.txt --voice ~/.chatter/voices/stephen_fry.wav --output podcast/01.wav
   speak 02_guest1_opening.txt --voice ~/.chatter/voices/morgan_freeman.wav --output podcast/02.wav
   speak 03_host_question.txt --voice ~/.chatter/voices/stephen_fry.wav --output podcast/03.wav
   speak 04_guest2_opening.txt --voice ~/.chatter/voices/ursula_leguin.wav --output podcast/04.wav

4. Concatenate all segments:

   speak concat podcast/*.wav --out final_podcast.wav

Confusions

1. Voice cloning vs. voice selection ambiguity: The docs say "Always use the full path to voice files" and show examples like ~/.chatter/voices/morgan_freeman.wav, but then state "The voice is now available via --voice speaker_name.wav" in the "Adding New Voice Samples" section. This contradicts the earlier warning. Which is correct?

2. Emotion tags and natural conversation: The emotion tags section shows examples like [sigh] and [laugh], but there's no guidance on whether these work mid-sentence or only at specific positions. The example "[sigh] I can't believe it's Monday again." shows it at the start, but can I use "I think AI safety is [pause]... critical" for natural debate pacing? The docs explicitly say [pause] is NOT supported but don't explain the workaround.

3. Concatenation audio quality: The docs don't specify if speak concat handles different sample rates, bit depths, or if there are gaps between concatenated files. Will three separately-generated WAV files concatenate seamlessly?

4. Debate flow and timing: No guidance on whether I should add silence/pauses between speakers. Should I manually add pauses to script files, or does concatenation handle this?

5. Output directory creation: When I specify --output podcast/01.wav, does the tool create the podcast/ directory, or will it fail if it doesn't exist?

Potential Failures

1. Voice file not found: If I use --voice ~/.chatter/voices/speaker_name.wav and that file doesn't exist, the command will fail. The docs don't show error messages or how to handle missing voices.

2. Contradictory voice path instructions: Following "The voice is now available via --voice speaker_name.wav" (without full path) will likely fail based on the earlier warning requiring full paths.

3. Missing sox dependency: The docs mention "Requires sox for auto-chunking" but I'm not using auto-chunking. Will concatenation fail without sox installed? This is unclear.

4. Directory doesn't exist: If podcast/ directory doesn't exist, --output podcast/01.wav may fail.

5. Concatenation order: Using podcast/*.wav in glob expansion depends on shell behavior. If files aren't numbered consistently (01, 02, 03...), they may concatenate in wrong order.

6. No voices available: If ~/.chatter/voices/ is empty or doesn't exist, I have no custom voices to choose from.

Suggested Improvements

1. Resolve voice path contradiction: Remove the conflicting statement "The voice is now available via --voice speaker_name.wav" OR clarify that BOTH work and explain when each is appropriate. Currently it says "Always use the full path" then contradicts itself.

2. Add error handling documentation: Show what happens when:

• Voice file doesn't exist
• Output directory doesn't exist
• Concatenation fails
• Include actual error messages and solutions

3. Clarify pause/silence handling:

• Explicitly state whether [pause] can be replaced with punctuation (e.g., ellipsis, em-dash)
• Show example: "I think... AI safety is critical"
• Document if there's a way to add silence between concatenated segments

4. Document concatenation technical details:

• Specify that all input WAV files must be same sample rate/bit depth
• State whether gaps are added between files or if they're seamless
• Clarify if sox is required for concatenation (separate from auto-chunking)

5. Add directory creation behavior: State explicitly: "The --output directory is created automatically if it doesn't exist" OR "You must create the output directory before running the command."

6. Improve glob ordering guidance: Add: "Use numbered filenames (01_, 02_, 03_) to ensure correct concatenation order when using wildcards like podcast/*.wav"

7. Add multi-voice workflow example: Expand the existing multi-voice section with a complete podcast/debate example showing:

• How to structure the debate (intro, opening statements, rebuttals, closing)
• Whether to add pauses between speakers in the script or via concatenation
• Complete end-to-end command sequence

8. Document voice discovery better: Show what to do if ~/.chatter/voices/ is empty or the directory doesn't exist. Should users create it? Are default voices provided?

---

anthropic/claude-sonnet-4.5

Status: success (40.4s, $0.038)

Understanding

The tool is a local TTS system that:

• Converts text to speech using Chatterbox TTS on Apple Silicon
• Supports voice cloning from WAV samples in ~/.chatter/voices/
• Can concatenate multiple audio files
• Has streaming and batch processing capabilities
• Includes emotion tags for expressiveness

For multi-voice content, the workflow is: split script by speaker → generate each segment with appropriate voice → concatenate all segments.

Approach

1. Check available voices:

   ls ~/.chatter/voices/*.wav 2>/dev/null

2. Create script files (split by speaker):

• 01_host_intro.txt - Host introduces topic
• 02_guest1_opening.txt - Guest 1's position
• 03_guest2_opening.txt - Guest 2's counter-position
• 04_host_question1.txt - Host asks follow-up
• 05_guest1_response.txt - Guest 1 responds
• 06_guest2_rebuttal.txt - Guest 2 rebuts
• (continue pattern for full debate)
• XX_host_closing.txt - Host wraps up

3. Generate each segment (assuming I found stephen_fry.wav, morgan_freeman.wav, ursula_leguin.wav):

   speak 01_host_intro.txt --voice ~/.chatter/voices/stephen_fry.wav --output wav/01.wav
   speak 02_guest1_opening.txt --voice ~/.chatter/voices/morgan_freeman.wav --output wav/02.wav
   speak 03_guest2_opening.txt --voice ~/.chatter/voices/ursula_leguin.wav --output wav/03.wav
   # ... continue for all segments

4. Concatenate all segments:

   speak concat wav/*.wav --out ai_safety_debate.wav

Confusions

1. Voice discovery ambiguity: The docs say "Always check what's available" and show ls ~/.chatter/voices/*.wav, but what if this directory doesn't exist or is empty? No guidance on:

• What to do if no voices are available
• Whether there's a "default" voice that works without samples
• If the tool ships with any pre-installed voices

2. Concatenation order: The example shows speak concat wav/*.wav --out final_debate.wav. Will *.wav glob in the correct alphanumeric order (01, 02, 03...)? Or do I need to explicitly list them? The docs don't specify glob expansion behavior.

3. Emotion tags in multi-voice workflow: Can I use emotion tags like [laugh] in the individual text files before generating? The docs show emotion tags in Quick Start examples but don't mention them in the multi-voice workflow section.

4. Output directory creation: Do I need to create the wav/ directory manually before running --output wav/01.wav, or does the tool create it automatically?

5. Batch processing vs. manual iteration: The docs show a batch processing example with --output-dir, but the multi-voice workflow shows manual iteration. Could I use:

   speak 01_host_intro.txt 02_guest1_opening.txt 03_guest2_opening.txt --output-dir wav/

But then how do I specify different voices per file? The docs don't address this.

6. Voice file validation: What happens if I specify a voice file that doesn't exist or is corrupted? No error handling guidance.

Potential Failures

1. No voices available: If ~/.chatter/voices/ is empty or doesn't exist, I cannot complete the task. The docs don't explain what happens or provide fallback.

2. Wrong concatenation order: If glob expansion doesn't sort correctly, the debate will be scrambled. I'd need to manually list all files in order, which isn't shown in the example.

3. Missing output directory: If wav/ doesn't exist and the tool doesn't auto-create it, all generation commands will fail.

4. Voice path typos: The docs emphasize "always use full path" but if I make a typo in any of the 20+ generation commands, that segment fails silently or with unclear error.

5. Inconsistent audio levels: No mention of whether concatenated segments will have consistent volume levels. Different voice samples might have different recording levels.

6. Long generation time: If the debate script is long, generating 20+ individual segments could take significant time. No guidance on whether to use --stream or --play for intermediate feedback, or if I should just generate all silently.

7. Timeout issues: Each segment generation has a 300s default timeout. If any single segment is very long, it might timeout. Should I use --auto-chunk for individual segments?

Suggested Improvements

1. Add voice availability section:

   ## Checking Voice Availability
   
   Before starting multi-voice projects, verify available voices:
   

ls ~/.chatter/voices/*.wav 2>/dev/null

   
   If no voices are found:
   - The tool will use the default voice for all generation
   - To add voices, see "Adding New Voice Samples" section
   - Pre-installed voices: [list if any, or state "none included"]

2. Clarify concatenation ordering:

   ### Concatenating Audio Files
   

Glob expansion uses shell sorting - ensure numeric prefixes

speak concat wav/*.wav --out combined.wav

For explicit control, list files in order:

speak concat wav/01.wav wav/02.wav wav/03.wav --out combined.wav

   
   **Important:** Use zero-padded numeric prefixes (01, 02, 03) to ensure correct glob sorting.

3. Add multi-voice workflow troubleshooting:

   ### Multi-Voice Workflow Tips
   
   - Create output directory first: `mkdir -p wav/`
   - Use zero-padded numbering: `01_`, `02_`, not `1_`, `2_`
   - Test one segment first before generating all
   - Consider using `--quiet` to reduce output clutter during batch generation
   - If a voice file doesn't exist, you'll see: [example error message]

4. Add emotion tags to multi-voice example:

   2. **Generate each segment with appropriate voice (use full paths)**

Emotion tags work in text files too

echo "Welcome to the debate! [chuckle]" > 01_host_intro.txt speak 01_host_intro.txt --voice ~/.chatter/voices/stephen_fry.wav --output wav/01.wav

5. **Add complete end-to-end example:**

Complete Multi-Voice Example

   # 1. Check voices
   ls ~/.chatter/voices/*.wav
   
   # 2. Create output directory
   mkdir -p debate_wav
   
   # 3. Create script files
   echo "Welcome to AI Safety Debates." > 01_host.txt
   echo "I believe AI alignment is solvable." > 02_guest1.txt
   echo "I'm more pessimistic about our chances." > 03_guest2.txt
   
   # 4. Generate with different voices
   speak 01_host.txt --voice ~/.chatter/voices/stephen_fry.wav --output debate_wav/01.wav
   speak 02_guest1.txt --voice ~/.chatter/voices/morgan_freeman.wav --output debate_wav/02.wav
   speak 03_guest2.txt --voice ~/.chatter/voices/ursula_leguin.wav --output debate_wav/03.wav
   
   # 5. Concatenate
   speak concat debate_wav/01.wav debate_wav/02.wav debate_wav/03.wav --out final_debate.wav

6. Add error handling section:

   ## Common Errors
   
   | Error | Cause | Solution |
   |-------|-------|----------|
   | "Voice file not found" | Wrong path or missing file | Check `ls ~/.chatter/voices/` |
   | "Output directory doesn't exist" | Missing parent directory | Create with `mkdir -p` |
   | Scrambled concatenation | Wrong file order | Use explicit file list or zero-padded names |

---

qwen/qwen3-coder:free

Status: error (-, -)

Error: HTTP_429 - OpenRouter API error: 429 {"error":{"message":"Provider returned error","code":429,"metadata":{"raw":"qwen/qwen3-coder:free is temporarily rate-limited upstream. Please retry shortly, or add your own key to accumulate your rate limits: https://openrouter.ai/settings/integrations","provider_name":"Venice"}},"user_id":"user_36vNK5v5p7yNuKnz0AM7SyRB9q2"}

---

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Run 01KENJABBZG751N6JWZWYQM8TS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Date: 2026-01-11T03:41:39.071Z Skill: /Users/jay/Documents/speak_optiimisation/iterations/SKILL_v1.md Task: Convert a 50-page PDF manual to an audiobook with chapters Status: completed ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

anthropic/claude-haiku-4.5

Status: success (19.8s, $0.003)

Understanding

The speak-tts tool converts text to speech on Apple Silicon Macs. It can:

• Read text files, markdown, or plain strings
• Stream audio or generate files
• Handle long documents via auto-chunking
• Concatenate multiple audio files
• Use custom voices for cloning
• Add emotion tags for expressiveness

For this task, I need to: convert PDF → text chapters → audio files → concatenate into single audiobook.

Approach

1. Convert PDF to text chapters (using external tool pdftotext)

   brew install poppler  # if needed
   pdftotext -f 1 -l 10 manual.pdf chapter01.txt
   pdftotext -f 11 -l 25 manual.pdf chapter02.txt
   pdftotext -f 26 -l 50 manual.pdf chapter03.txt

2. Estimate total generation time

   speak --estimate chapter01.txt chapter02.txt chapter03.txt

3. Create output directory

   mkdir -p audiobook/

4. Generate all chapters with auto-chunking (for reliability on long content)

   speak chapter01.txt chapter02.txt chapter03.txt --output-dir audiobook/ --auto-chunk

This should create: audiobook/chapter01.wav, audiobook/chapter02.wav, audiobook/chapter03.wav

5. Concatenate into single file

   speak concat audiobook/chapter01.wav audiobook/chapter02.wav audiobook/chapter03.wav --output complete_audiobook.wav

6. Play result (optional)

   afplay complete_audiobook.wav

Confusions

1. PDF conversion tool not included: The docs say "requires poppler: brew install poppler" but this is mentioned only in a code example, not in the Prerequisites section. It's unclear if pdftotext is a separate tool or part of the speak tool.

2. Batch processing output naming ambiguity: The docs state "Output naming: input filename with .wav extension" but don't clarify if chapter01.txt becomes chapter01.wav or if the full path is audiobook/chapter01.wav. The example shows both formats inconsistently.

3. Auto-chunk with batch processing interaction unclear: The docs say "Batch processing with auto-chunking (works together)" but don't explain:

• Are intermediate chunks saved per file or globally?
• What happens to the manifest file when processing multiple files?
• Can you resume a multi-file batch?

4. Concatenation file ordering: The docs warn about zero-padding: "01.wav, 02.wav, 03.wav → correct order" but the PDF-to-audiobook example uses chapter*.txt which expands to chapter01.txt, chapter02.txt, etc. It's unclear if the glob expansion respects zero-padding or if I need to manually list files.

5. Missing detail on chapter splitting: The example shows pdftotext -f 1 -l 10 but doesn't explain:

• How to determine optimal page ranges for 50 pages
• Whether page numbers in PDFs always match -f/-l parameters
• What happens if a chapter boundary falls mid-sentence

Potential Failures

1. `pdftotext` not installed: If poppler isn't installed, the PDF conversion fails. The tool doesn't provide this, so I'd need to install it separately. The docs mention it only in a code example, not prerequisites.

2. Output directory not created: The docs explicitly state "Output directories are NOT auto-created." If I forget mkdir -p audiobook/, the batch processing will fail with "Output directory doesn't exist."

3. Glob expansion order: If I use speak chapter*.txt in batch mode and the shell expands it to the wrong order (e.g., chapter1.txt chapter10.txt chapter2.txt), the concatenation will be scrambled. The docs warn about this for concatenation but don't clarify if batch processing has the same issue.

4. Timeout on large chapters: A 50-page manual could have chapters >10 minutes. Without --auto-chunk, generation might timeout at the default 300 seconds. The docs recommend auto-chunk for >10 min audio, but don't specify what happens if you exceed timeout without it.

5. Resume doesn't work for batch: If batch processing fails partway (e.g., chapter 2 of 3), the --resume option references a manifest file. It's unclear if this works for multi-file batches or only single files.

6. Concatenation with wrong filenames: If the batch output doesn't create zero-padded filenames (e.g., creates chapter1.wav instead of chapter01.wav), using speak concat audiobook/*.wav will concatenate in wrong order.

Suggested Improvements

1. Add PDF conversion to Prerequisites section:

   | Requirement | Check | Install |
   |-------------|-------|---------|
   | poppler (for PDF conversion) | `which pdftotext` | `brew install poppler` |

2. Clarify batch output naming with explicit example:

   # Batch processing output naming:
   speak chapter01.txt chapter02.txt --output-dir audiobook/
   # Creates: audiobook/chapter01.wav, audiobook/chapter02.wav
   # (input filename + .wav extension, placed in output-dir)

3. Explain auto-chunk + batch interaction explicitly:

   # When using --auto-chunk with multiple files:
   # - Each file is chunked independently
   # - Chunks saved to: ~/Audio/speak/chapter01_chunk_001.wav, etc.
   # - Final output: audiobook/chapter01.wav (concatenated chunks)
   # - Resume works per-file: speak --resume ~/Audio/speak/manifest_chapter01.json

4. Clarify glob expansion in batch mode:

   # IMPORTANT: Batch mode uses shell glob expansion
   # Use explicit file list or zero-padded names:
   speak chapter01.txt chapter02.txt chapter03.txt --output-dir audiobook/  # Safe
   speak chapter*.txt --output-dir audiobook/  # Risky - depends on shell sorting

5. Add a "Troubleshooting Batch Processing" section:

   | Problem | Cause | Solution |
   |---------|-------|----------|
   | Batch stops at file 2 of 3 | Timeout on large chapter | Use `--timeout 600` or `--auto-chunk` |
   | Can't resume batch | Manifest file unclear | Use `speak --resume ~/Audio/speak/manifest_chapter02.json` for specific file |
   | Concatenation in wrong order | Non-zero-padded output | Manually list files: `speak concat audiobook/chapter01.wav audiobook/chapter02.wav ...` |

6. Specify page range calculation for PDFs:

   # For 50-page manual, suggested splits:
   # - 10-15 pages per chapter (5-10 min audio)
   # - Test first chapter to estimate: speak --estimate chapter01.txt
   # - Adjust ranges if chapters exceed 10 min audio

7. Add explicit warning about manifest files in batch mode:

   # If batch processing is interrupted:
   # - Check ~/Audio/speak/ for manifest_*.json files
   # - Resume individual files: speak --resume ~/Audio/speak/manifest_chapter02.json
   # - Or restart entire batch (--skip-existing will skip completed files)

8. Clarify what "works together" means for auto-chunk + batch:

   # --auto-chunk with --output-dir:
   # YES: speak chapter*.txt --output-dir audiobook/ --auto-chunk
   # This chunks each file, saves final output to audiobook/, keeps intermediate chunks
   # Use --keep-chunks to inspect: ls ~/Audio/speak/chapter*_chunk*.wav

---

anthropic/claude-sonnet-4.5

Status: success (53.6s, $0.052)

Understanding

This tool converts text to speech using Chatterbox TTS on Apple Silicon. It supports:

• Multiple input formats (txt, md, direct strings) but NOT PDF directly
• Streaming and file output modes
• Auto-chunking for long documents
• Batch processing multiple files
• Voice cloning with custom voice samples
• Concatenating audio files
• Resume capability for interrupted jobs

For the PDF audiobook task, I need to: convert PDF to text, split into chapters, generate audio for each, and concatenate.

Approach

1. Install prerequisites:

   brew install poppler sox

2. Convert PDF to text and split by chapters:

   pdftotext -f 1 -l 10 manual.pdf chapter01.txt
   pdftotext -f 11 -l 20 manual.pdf chapter02.txt
   # ... continue for all 50 pages

3. Estimate total generation time:

   speak --estimate chapter*.txt

4. Create output directory:

   mkdir -p audiobook/

5. Generate audio for all chapters with auto-chunking:

   speak chapter*.txt --output-dir audiobook/ --auto-chunk

6. Concatenate chapters:

   speak concat audiobook/chapter01.wav audiobook/chapter02.wav ... --output complete_audiobook.wav

7. Play to verify:

   afplay complete_audiobook.wav

Confusions

1. Chapter splitting is manual and tedious: The documentation shows splitting a PDF into chapters using page ranges (-f 1 -l 10), but for a 50-page document, I need to know where chapters actually begin/end. The docs don't explain:

• How to determine chapter boundaries in the PDF
• Whether there's a way to auto-detect chapters
• What to do if the PDF doesn't have clear chapter divisions

2. Zero-padding requirements unclear for initial files: The docs state: "files sorted alphanumerically - use zero-padded names!" and show examples like 01.wav, 02.wav, but in the PDF example, it uses chapter01.txt, chapter02.txt, chapter03.txt. Is this zero-padded enough? What if I have more than 99 chapters? Should it be chapter001.txt?

3. Batch output naming ambiguous: The docs say "Output naming: input filename with .wav extension" but then show chapter01.txt → ~/Audio/book/chapter01.wav. Does it preserve the full filename including the extension? So chapter01.txt becomes chapter01.txt.wav or chapter01.wav? The example suggests the latter but it's not explicitly stated.

4. No guidance on optimal chapter length: The docs mention "Use --auto-chunk for documents >10 minutes of audio" and show estimates like "1 page ≈ 500 words ≈ 2,500 chars ≈ 2 min audio". For a 50-page PDF, that's ~100 minutes total. Should I:

• Split into many small chapters (5 pages each = 10 chapters)?
• Keep larger chapters (10 pages each = 5 chapters)?
• Does it matter for reliability?

5. Concatenation with glob is risky: The docs warn about glob ordering but then show speak concat audiobook/chapter*.wav --output complete_audiobook.wav in the example. If I have chapter1.txt through chapter50.txt, the glob will sort as: chapter1, chapter10, chapter11, ..., chapter19, chapter2, chapter20, .... The docs say "use zero-padding" but don't clarify if this applies to the initial text files or just the intermediate chunks.

6. Resume capability unclear for batch processing: If batch processing with --output-dir fails partway through, the docs show speak --resume ~/Audio/speak/manifest.json. But:

• Is there one manifest per file or one for the entire batch?
• Where exactly is the manifest saved when using --output-dir?
• The example shows ~/Audio/speak/manifest.json but the output-dir is audiobook/

Potential Failures

1. Incorrect file ordering in concatenation: If I name files chapter1.txt through chapter50.txt, the glob chapter*.txt will produce wrong order. Must use chapter01.txt through chapter50.txt.

2. Missing output directory: The docs explicitly state "Output directories are NOT auto-created - use mkdir -p first". If I forget mkdir -p audiobook/, the batch processing will fail.

3. Timeout on long chapters: If any single chapter exceeds 5 minutes of generation time (default 300s timeout), it will fail. The docs suggest using --auto-chunk but don't clarify if this is automatically applied per-file in batch mode or needs to be specified.

4. Running out of disk space: 50 pages ≈ 100 minutes of audio ≈ 250 MB per the storage table. If I use --keep-chunks, this could balloon significantly. No warning about this.

5. Wrong voice file path: If I try to use a custom voice, I must use the full path ~/.chatter/voices/name.wav, not just name.wav. Easy to forget.

6. pdftotext not preserving structure: The docs show using -layout flag in one example but not in the chapter-splitting examples. Unclear which is correct for preserving readability.

7. No validation of PDF page count: If I specify -f 1 -l 10 but the PDF only has 8 pages, what happens? No error handling guidance.

Suggested Improvements

1. Add a section on determining chapter boundaries:

   ### Finding Chapter Boundaries
   
   To determine page ranges for chapters:

View PDF outline/bookmarks

pdfinfo manual.pdf

Or manually inspect

open manual.pdf # Note page numbers where chapters start

   
   If PDF has no chapters, split by page count:
   - Short manual (50 pages): 5 chapters of 10 pages each
   - Long book (300 pages): 10-15 chapters of 20-30 pages each

2. Clarify zero-padding requirements upfront:

   ### File Naming for Batch Processing
   
   **CRITICAL**: Always use zero-padded numbers for files that will be processed in order:
   
   ✓ Correct: `chapter01.txt`, `chapter02.txt`, ..., `chapter50.txt`
   ✗ Wrong: `chapter1.txt`, `chapter2.txt`, ..., `chapter50.txt`
   
   Rule: Use as many zeros as needed for your highest number:
   - 1-9 files: `01`, `02`, ... `09`
   - 10-99 files: `01`, `02`, ... `99`
   - 100-999 files: `001`, `002`, ... `999`

3. Add explicit output filename behavior:

   When using `--output-dir`, the output filename is derived by:
   1. Taking the input filename without path
   2. Removing the extension
   3. Adding `.wav`
   
   Examples:
   - `chapter01.txt` → `chapter01.wav`
   - `~/docs/intro.md` → `intro.wav`
   - `file.txt.backup` → `file.txt.wav` (only last extension removed)

4. Add a complete workflow with explicit page count:

   ## Complete Example: 50-Page PDF to Audiobook
   
   Assuming 50 pages, split into 5 chapters of 10 pages each:
   

1. Install dependencies

brew install poppler sox

2. Split PDF into chapters (adjust page ranges for your PDF)

pdftotext -f 1 -l 10 -layout manual.pdf chapter01.txt pdftotext -f 11 -l 20 -layout manual.pdf chapter02.txt pdftotext -f 21 -l 30 -layout manual.pdf chapter03.txt pdftotext -f 31 -l 40 -layout manual.pdf chapter04.txt pdftotext -f 41 -l 50 -layout manual.pdf chapter05.txt

3. Verify files are named correctly

ls chapter*.txt

Should show: chapter01.txt chapter02.txt chapter03.txt chapter04.txt chapter05.txt

4. Estimate time (50 pages ≈ 100 min audio ≈ 50 min generation)

speak --estimate chapter*.txt

5. Create output directory

mkdir -p audiobook/

6. Generate all chapters (auto-chunk for reliability)

speak chapter*.txt --output-dir audiobook/ --auto-chunk

7. Verify all chapters generated

ls audiobook/

Should show: chapter01.wav chapter02.wav chapter03.wav chapter04.wav chapter05.wav

8. Concatenate (explicit order to be safe)

speak concat audiobook/chapter01.wav audiobook/chapter02.wav audiobook/chapter03.wav audiobook/chapter04.wav audiobook/chapter05.wav --output complete_audiobook.wav

9. Play result

afplay complete_audiobook.wav

5. Clarify resume behavior for batch processing:

   ### Resume Behavior
   
   - **Single file with `--auto-chunk`**: Creates manifest at `~/Audio/speak/manifest.json`
   - **Batch processing with `--output-dir`**: Each file is independent. If interrupted:
     - Use `--skip-existing` to avoid regenerating completed files
     - No cross-file resume capability
   - **Resume only works for single-file auto-chunked jobs**

6. Add disk space warning:

   ### Storage Planning
   
   Before generating long audiobooks:

Check available space

df -h ~

Estimate required space

speak --estimate chapter*.txt

Look for "Estimated audio: ~100 minutes"

Calculate: 100 min × 2.5 MB/min = 250 MB

With --keep-chunks: multiply by 2-3x

7. Add troubleshooting for pdftotext:

   ### PDF Conversion Issues
   
   If `pdftotext` produces garbled text:
   - Try without `-layout`: `pdftotext -f 1 -l 10 manual.pdf chapter01.txt`
   - For scanned PDFs, use OCR first: `brew install tesseract && ...`
   - For encrypted PDFs: `qpdf --decrypt input.pdf output.pdf`

---

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Run 01KENJCBM9293BP2M9P3ZPA34S ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Date: 2026-01-11T03:42:44.873Z Skill: /Users/jay/Documents/speak_optiimisation/iterations/SKILL_v1.md Task: Create a 3-voice podcast debate about AI safety with host and two guests Status: completed ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

anthropic/claude-haiku-4.5

Status: success (22.6s, $0.004)

Understanding

The tool is a local text-to-speech generator for Apple Silicon Macs that converts text to WAV audio files. Key capabilities:

• Converts plain text, markdown, or direct strings to speech
• Supports custom voice cloning via WAV files stored in ~/.chatter/voices/
• Can concatenate multiple audio files
• Supports emotion tags like [sigh], [laugh], etc.
• Requires manual directory creation before output

For this task, I need to: 1. Create script files for three speakers (host + 2 guests) 2. Generate audio for each speaker using different voice files 3. Concatenate the three audio files in order

Approach

Step 1: Verify prerequisites

which sox                    # Confirm sox installed
ls ~/.chatter/voices/*.wav   # Check available voices

Step 2: Create directory structure

mkdir -p podcast/scripts podcast/wav

Step 3: Create three script files with emotion tags

cat > podcast/scripts/01_host_intro.txt << 'EOF'
[clear throat] Welcome to the AI Safety Debate. I'm your host. Today we're 
discussing whether artificial intelligence poses an existential risk to humanity. 
With us are two leading researchers with opposing views.
EOF

cat > podcast/scripts/02_guest1_optimist.txt << 'EOF'
Thank you for having me. I believe the concerns about AI safety are overblown. 
We have robust alignment techniques and the AI research community is taking 
safety seriously. I'm optimistic we'll solve these challenges.
EOF

cat > podcast/scripts/03_guest2_cautious.txt << 'EOF'
[sigh] I respectfully disagree. The pace of AI development is outstripping 
our ability to ensure safety. We need stronger governance and more research 
before deploying advanced systems.
EOF

Step 4: Generate audio for each segment with different voices

speak podcast/scripts/01_host_intro.txt \
  --voice ~/.chatter/voices/stephen_fry.wav \
  --output podcast/wav/01.wav

speak podcast/scripts/02_guest1_optimist.txt \
  --voice ~/.chatter/voices/morgan_freeman.wav \
  --output podcast/wav/02.wav

speak podcast/scripts/03_guest2_cautious.txt \
  --voice ~/.chatter/voices/ursula_leguin.wav \
  --output podcast/wav/03.wav

Step 5: Concatenate in order

speak concat podcast/wav/01.wav podcast/wav/02.wav podcast/wav/03.wav \
  --output ai_safety_debate.wav

Step 6: Verify result

afplay ai_safety_debate.wav

Confusions

1. Voice file availability unclear: The docs say "Voice samples are stored in ~/.chatter/voices/" but don't specify what voices come pre-installed. The example uses stephen_fry.wav, morgan_freeman.wav, and ursula_leguin.wav but there's no confirmation these exist by default. Quote: "If empty or directory doesn't exist: The tool uses a default voice" — this suggests the directory might not exist initially, but then how do I know what voices are available?

2. Voice cloning vs. pre-recorded voices ambiguous: The section titled "Voice Cloning & Multi-Voice Content" conflates two different things:

• Using pre-recorded voice samples (the examples)
• Cloning a voice from a sample you provide

Quote: "To add a new voice for cloning: Get a clean 10-30 second audio sample" — this implies you can only clone voices you provide, but the examples use specific named voices. Are those pre-installed or do I need to add them?

3. Emotion tag behavior undefined: The docs list supported emotion tags but don't explain:

• Do they affect the audio output or are they just metadata?
• Are they removed from the spoken text or spoken aloud?
• Quote: "Add expressive sounds inline with text" — does this mean the emotion is added to the speech, or the tag is literally spoken?

4. Default voice unspecified: When no --voice is specified, what voice is used? The docs say "default" but never name it.

5. Concatenation order with glob patterns: Quote: "Using glob (files sorted alphanumerically - use zero-padded names!)" — but what if I use explicit file paths instead of glob? Will they concatenate in the order I specify them, or alphabetically?

Potential Failures

1. Voice files don't exist: If stephen_fry.wav, morgan_freeman.wav, and ursula_leguin.wav aren't pre-installed in ~/.chatter/voices/, the commands will fail with "Voice file not found" and I won't know what voices are actually available.

2. Directory creation fails silently: The docs state "Output directories are NOT auto-created" but don't specify what error occurs if I forget mkdir -p. The tool might fail cryptically.

3. Emotion tags not working as expected: If [sigh] and [clear throat] don't actually produce audible effects (just affect prosody), the podcast will sound flat and the task will be incomplete.

4. Concatenation order wrong: If I use speak concat podcast/wav/*.wav without zero-padding, files might concatenate as 01.wav, 02.wav, 03.wav (correct) or 01.wav, 03.wav, 02.wav (wrong) depending on glob behavior.

5. sox not installed: If sox is required for concatenation and not installed, speak concat will fail. The docs list it as a prerequisite for "auto-chunking/concat" but it's unclear if it's required for basic concat.

6. Voice path format: The docs emphasize "Always use the full path to voice files" but if I use a relative path like voices/stephen_fry.wav instead of ~/.chatter/voices/stephen_fry.wav, it will fail silently or with a cryptic error.

Suggested Improvements

1. Explicitly list pre-installed voices: Add a section like:

   ## Pre-Installed Voices
   The following voices come pre-installed in ~/.chatter/voices/:
   - stephen_fry.wav
   - morgan_freeman.wav
   - ursula_leguin.wav
   - [others...]
   
   Run: ls ~/.chatter/voices/ to see all available voices

2. Clarify emotion tag behavior: Add to the Emotion Tags section:

   Emotion tags produce audible effects in the speech (e.g., actual 
   laughter, sighing sounds). They are NOT spoken aloud and are 
   removed from the output text. Example:
   Input: "[laugh] That's funny!"
   Output audio: (audible laugh sound) "That's funny!"

3. Specify default voice: Add to Options Reference:

   | `--voice` | Voice .wav file for cloning (full path required) | default_voice.wav (built-in) |

4. Clarify concatenation order: Update the concat section:

   # Explicit file order (concatenates in specified order)
   speak concat part1.wav part2.wav part3.wav --output combined.wav
   
   # Glob pattern (sorts alphanumerically - use zero-padded names!)
   speak concat wav/*.wav --output combined.wav

5. Add error handling section: Expand "Common Errors" with:

   | Error | Cause | Solution |
   | "Output directory doesn't exist" | Parent directory missing | Create first: mkdir -p dirname/ |
   | Emotion tags not working | sox not installed | brew install sox |
   | Concatenation fails | sox not installed | brew install sox |

6. Make sox requirement explicit: Update Prerequisites table:

   | sox (for concatenation) | `which sox` | `brew install sox` |

Currently it only lists sox for "auto-chunking/concat" but it's unclear if both features require it.

7. Add voice discovery command: Document a built-in command:

   speak voices  # List all available voices

Instead of requiring users to manually ls ~/.chatter/voices/.

8. Provide fallback instructions: Add to Voice Cloning section:

   If ~/.chatter/voices/ is empty or doesn't exist:
   1. The tool will use a built-in default voice
   2. To use custom voices, create the directory: mkdir -p ~/.chatter/voices/
   3. Add your voice samples there

---

anthropic/claude-sonnet-4.5

Status: success (37.2s, $0.039)

Understanding

This tool converts text to speech using Chatterbox TTS on Apple Silicon. It supports voice cloning, emotion tags, streaming, batch processing, and concatenation. For multi-voice content, I need to: create separate text files per speaker, generate audio for each with different voices, then concatenate them. The tool requires full paths for voice files and zero-padded filenames for proper ordering.

Approach

1. Check available voices:

   ls ~/.chatter/voices/*.wav

2. Create directory structure:

   mkdir -p podcast/scripts podcast/wav

3. Create script files (zero-padded):

• podcast/scripts/01_host_intro.txt
• podcast/scripts/02_guest1_opening.txt
• podcast/scripts/03_guest2_counter.txt
• podcast/scripts/04_host_question.txt
• podcast/scripts/05_guest1_response.txt
• podcast/scripts/06_guest2_rebuttal.txt
• podcast/scripts/07_host_closing.txt

4. Generate each segment with appropriate voice:

   speak podcast/scripts/01_host_intro.txt --voice ~/.chatter/voices/stephen_fry.wav --output podcast/wav/01.wav
   speak podcast/scripts/02_guest1_opening.txt --voice ~/.chatter/voices/morgan_freeman.wav --output podcast/wav/02.wav
   # ... etc for all 7 segments

5. Concatenate:

   speak concat podcast/wav/*.wav --output ai_safety_debate.wav

6. Play result:

   afplay ai_safety_debate.wav

Confusions

1. Voice availability assumption: The documentation shows example voices like "stephen_fry.wav", "morgan_freeman.wav", "ursula_leguin.wav" but states "If empty or directory doesn't exist: The tool uses a default voice". What if ~/.chatter/voices/ is empty? Do I need to create these voice samples first? The task says "create a 3-voice podcast" but doesn't tell me if voices exist.

2. What constitutes a "debate"?: The task says "debate about AI safety" but doesn't specify length, structure, or content. Should I write 2 sentences per person or 200? The example shows very short snippets, but is that realistic for a "debate"?

3. Emotion tag placement: The doc says "Add expressive sounds inline with text" but the examples show tags at the start of sentences. Can they go mid-sentence? "I think [sigh] this is wrong" vs "[sigh] I think this is wrong"?

4. Default voice behavior: If I don't specify --voice, what voice is used? Is it consistent across calls? This matters if voices don't exist.

5. File naming in concat: The doc warns about "scrambled concatenation order" with non-zero-padded names, but then the example uses speak concat podcast/wav/*.wav. If I have 10+ files, do I need 001_ or is 01_ sufficient?

Potential Failures

1. No voices exist: If ~/.chatter/voices/ is empty or doesn't contain the example voices, the --voice flag will fail with "Voice file not found". The task would be impossible without creating voice samples first.

2. Wrong voice path format: Forgetting the full path (--voice morgan_freeman.wav instead of --voice ~/.chatter/voices/morgan_freeman.wav) causes failure.

3. Directory not created: Forgetting mkdir -p podcast/wav before generating audio causes "Output directory doesn't exist" error.

4. Non-zero-padded filenames: If I create 10+ segments and use 1_, 10_, 2_ instead of 01_, 10_, 02_, concatenation order will be wrong.

5. Glob expansion order: The *.wav glob might not sort correctly on all systems. The doc says "files sorted alphanumerically" but doesn't clarify if this is shell behavior or tool behavior.

6. Missing sox: If sox isn't installed, concat fails. The doc mentions this for auto-chunking but concat also requires it (implied but not explicit).

7. Content length unclear: If I write very long debate segments, I might hit timeout issues, but the doc doesn't say when to use --auto-chunk for individual segments.

Suggested Improvements

1. Add voice availability check to task prerequisites:

   # Before starting, verify voices exist:
   ls ~/.chatter/voices/*.wav
   # If empty, either:
   # - Use default voice (omit --voice flag)
   # - Add voice samples (see "Adding New Voice Samples")

2. Clarify default voice behavior explicitly:

"If --voice is omitted, the tool uses a built-in default voice. This voice is consistent across all calls in the same session."

3. Add explicit sox requirement for concat: In the "Concatenating Audio Files" section:

"Requires sox: brew install sox (same as auto-chunking)"

4. Show explicit example with 10+ files:

   # For 10+ segments, use 3-digit padding:
   001_host.txt, 002_guest1.txt, ..., 010_guest2.txt
   # Not: 01_host.txt, 02_guest1.txt, ..., 10_guest2.txt

5. Add troubleshooting for voice files:

   # If "Voice file not found" error:
   # 1. Verify file exists:
   ls -la ~/.chatter/voices/stephen_fry.wav
   # 2. Check you used full path with ~/.chatter/voices/
   # 3. Or omit --voice to use default voice

6. Clarify concat ordering mechanism:

"Concatenation uses shell glob expansion (alphanumeric sort). On macOS/Linux, *.wav sorts as: 01.wav, 02.wav, 10.wav, 11.wav. Always use zero-padding for predictable ordering."

7. Add content length guidance for segments:

"For multi-voice segments, keep each file under 5,000 characters (~5 min audio) to avoid timeouts. For longer segments, use --auto-chunk on individual files before concatenating."

8. Add complete working example with fallback:

   # Multi-voice podcast (with fallback if voices don't exist)
   
   # Check voices
   if [ -z "$(ls ~/.chatter/voices/*.wav 2>/dev/null)" ]; then
     echo "No custom voices found, using default voice"
     VOICE_FLAG=""
   else
     VOICE_FLAG="--voice ~/.chatter/voices/stephen_fry.wav"
   fi
   
   # Generate with voice or default
   speak 01_host.txt $VOICE_FLAG --output wav/01.wav

9. Add emotion tag placement clarification:

"Emotion tags work at sentence start or mid-sentence: [sigh] I think... or I think [sigh] this is.... Effect is similar but start-of-sentence is more natural."

10. Make the multi-voice example more realistic: Show actual debate-length content (100-200 words per segment) instead of single sentences, so users understand realistic scope.

---

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Run 01KENJGY4MC2Q7C2WCSQVET2C9 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Date: 2026-01-11T03:45:14.900Z Skill: /Users/jay/Documents/speak_optiimisation/iterations/SKILL_v2.md Task: Read this news article aloud and save as an audio file I can listen to later Status: completed ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

anthropic/claude-haiku-4.5

Status: success (22.5s, $0.004)

Understanding

The speak-tts tool converts text to speech using Chatterbox TTS on Apple Silicon Macs. To complete this task, I need to: 1. Get the news article text into a supported format (.txt or .md) 2. Use the speak command with --output to save it as a WAV file 3. The tool will generate audio that I can play later with afplay or another audio player

Approach

Step-by-step:

1. Obtain the article text - The documentation doesn't specify how to get the article. I would need to:

• Copy the article text manually, OR
• Save it as a .txt or .md file, OR
• Use a tool to extract text from a web page (not covered in docs)

2. Verify prerequisites:

• Confirm I'm on Apple Silicon Mac: uname -m (should show arm64)
• Check macOS version: sw_vers
• Verify sox is installed: which sox (needed for emotion tags and concatenation)

3. Create output directory:

   mkdir -p ~/Audio/speak/

(The docs explicitly state output directories are NOT auto-created)

4. Generate and save the audio:

   speak article.txt --output ~/Audio/news_article.wav

Or if pasting directly:

   speak "Article text here..." --output ~/Audio/news_article.wav

5. Verify the file was created:

   ls -lh ~/Audio/news_article.wav

6. Play it later:

   afplay ~/Audio/news_article.wav

Confusions

1. How do I get the article text? The documentation says "Use this when users request converting text to audio, reading articles/documents aloud" but provides NO guidance on:

• Extracting text from web pages
• Converting HTML articles to plain text
• Handling paywalled or JavaScript-heavy articles

The docs only cover converting existing .txt/.md files or direct strings.

2. "Save as an audio file I can listen to later" - What format? The docs state "Audio format: WAV 24kHz mono" but don't explain:

• Can I convert to MP3 afterward?
• Is WAV the only output format?
• The --output option just says "Output file (.wav)" - is the .wav extension required?

3. Streaming vs. saving - The docs show --stream for immediate playback and --play for "play after generation," but for "listen to later," should I use neither flag? The docs don't explicitly state what happens with --output alone (does it auto-play? does it just save silently?).

4. Emotion tags - The docs say "Tags produce audible effects" but then state: "Not supported: `[pause]`, `[whisper]`" and "For pauses: Use punctuation". This is confusing because:

• Will the tool error if I include unsupported tags?
• Should I pre-process the article to remove or replace unsupported tags?
• The docs don't say what happens if you use an unsupported tag.

5. Voice selection - The docs say "When --voice is omitted, the tool uses a built-in default voice" but also state: "The example voice names in this documentation (stephen_fry, morgan_freeman, ursula_leguin) are illustrative. You must provide your own voice samples - they are NOT pre-installed."

This is contradictory. If I don't provide a voice, does it use a built-in default, or do I need to provide one?

Potential Failures

1. Article text not in supported format - If the article is a PDF, DOCX, or HTML file, the tool will fail. The docs say "PDF ✗" and require manual conversion via pdftotext. I would need to know the article's source format.

2. Output directory doesn't exist - The docs explicitly warn: "Output directories are NOT auto-created - use mkdir -p first." If I skip this step, I'll get "Output directory doesn't exist" error.

3. Missing sox - If sox isn't installed and the article contains emotion tags like [sigh] or [laugh], the tool will fail with "sox not found" error. The docs state emotion tags require sox.

4. Article too long - If the article is >5 minutes of audio (~25,000 characters), it may timeout. The docs say default timeout is 300 seconds (5 min). I would need to use --auto-chunk to handle this, but the task doesn't mention this requirement.

5. Not on Apple Silicon - The tool only works on M1/M2/M3/M4 Macs. If I'm on Intel, it will fail immediately.

6. Unsupported tags in article - If the article text contains [pause] or [whisper] tags, the tool will fail (these are explicitly not supported), but the docs don't say what error message I'd get.

7. Stale daemon state - The docs mention "Server not running" error can occur due to "Stale daemon state." The solution is speak daemon kill && speak health, but I wouldn't know to do this unless I hit the error.

Suggested Improvements

1. Add a section on article extraction:

   ## Getting Article Text
   
   ### From a Web Page
   - Copy and paste article text into a .txt file, OR
   - Use a tool like `lynx` or `w3m` to extract text:
     lynx -dump -nolist https://example.com/article > article.txt
   - Use `curl` + HTML parser (example with pandoc):
     curl https://example.com/article | pandoc -f html -t plain > article.txt
   
   ### From PDF
   Use pdftotext (included with poppler):
   pdftotext article.pdf article.txt

2. Clarify voice behavior:

   ### Voice Selection
   
   If --voice is omitted:
   - The tool uses a built-in default voice automatically
   - No voice file is required
   - All generations use the same consistent default voice
   
   To use a custom voice:
   - Provide your own voice sample as a WAV file
   - Use full path: --voice ~/.chatter/voices/custom.wav
   - See "Adding Voice Samples" section above

3. Clarify output behavior:

   ## Output Modes
   
   | Option | Behavior |
   |--------|----------|
   | `--output file.wav` | Save to file, no playback |
   | `--output file.wav --play` | Save to file, then play |
   | `--stream` | Stream audio immediately (no file saved) |
   | `--stream --output file.wav` | Stream AND save simultaneously |

4. Add error handling for unsupported tags:

   ### Unsupported Tags
   
   If your article contains these tags, remove or replace them:
   - [pause] → Use ellipsis or period instead: "Wait... let me think."
   - [whisper] → Not supported; use regular speech
   
   The tool will error if unsupported tags are present.

5. Add a quick-start example for this exact task:

   ## Quick Start: Save Article for Later
   
   # 1. Get article text into a file
   # (copy-paste into article.txt, or use pdftotext/lynx)
   
   # 2. Create output directory
   mkdir -p ~/Audio/
   
   # 3. Generate audio file
   speak article.txt --output ~/Audio/article.wav
   
   # 4. Listen anytime
   afplay ~/Audio/article.wav
   
   # For long articles (>10 min), add --auto-chunk:
   speak article.txt --output ~/Audio/article.wav --auto-chunk

6. Clarify timeout and chunking:

   ### Long Articles
   
   If your article is longer than ~25,000 characters (~25 min audio):
   - Use --auto-chunk to split into smaller pieces
   - Default chunk size: 6,000 characters
   - Chunks are concatenated automatically into final output
   - Intermediate chunks are deleted unless --keep-chunks is used

7. Add a troubleshooting section specific to this task:

   ## Troubleshooting: "Save Article for Later"
   
   | Problem | Solution |
   |---------|----------|
   | "Output directory doesn't exist" | Run: mkdir -p ~/Audio/ |
   | Generation times out | Add --auto-chunk flag |
   | No audio file created | Check: ls -l ~/Audio/article.wav |
   | File is empty | Article text may be empty; verify input |
   | Can't play file later | Use afplay: afplay ~/Audio/article.wav |

---

anthropic/claude-opus-4.5

Status: success (29.2s, $0.167)

Understanding

The tool converts text to speech on Apple Silicon Macs. I need to: 1. Take a news article (text input) 2. Generate audio from it 3. Save it as a WAV file for later listening

The tool supports plain text, markdown, and direct strings. It outputs WAV files at 24kHz mono.

Approach

Step 1: Determine the article source The task says "this news article" but doesn't specify what article or where it is. I need to clarify:

• Is it a file on disk? (e.g., article.txt, article.md)
• Is it in the clipboard?
• Is it a URL I need to fetch first?
• Is it text the user will paste?

Step 2: If it's a file, run:

speak article.txt --output ~/Audio/article.wav

Step 3: If it's text content, run:

speak "The full article text here..." --output ~/Audio/article.wav

Step 4: Verify the output exists:

ls -la ~/Audio/article.wav

Confusions

1. "this news article" - what article? The task references an article but doesn't provide it. The documentation doesn't explain how to handle clipboard content despite the description mentioning "reading articles/documents aloud, generating speech from clipboard content."

From the tool description: "generating speech from clipboard content" - but there's NO documentation on how to actually do this. No --clipboard flag or pbpaste example.

2. Default output location unclear The docs say:

--output <path> | Output file (.wav) or directory | ~/Audio/speak/

But what's the default filename? If I run speak article.txt without --output, what file gets created? Is it ~/Audio/speak/article.wav? ~/Audio/speak/output.wav? Something timestamped? This is never explicitly stated.

3. Does ~/Audio/speak/ get auto-created? The docs repeatedly warn:

"Output directories are NOT auto-created - use mkdir -p first"

But then lists ~/Audio/speak/ as the default. Do I need to mkdir -p ~/Audio/speak/ before first use? Contradictory.

4. Should I use --stream or --play or neither? The task says "save as an audio file I can listen to later" - so I don't want to play it now. But the Quick Start examples all use --stream or --play. The docs say:

# Stream audio (recommended - starts playing immediately)

For my use case (save for later), I should probably use neither flag, just --output. But this isn't explicitly shown as a pattern.

Potential Failures

1. No article provided - The task is impossible without knowing what article to read. I'd need to ask the user.

2. Output directory doesn't exist - If ~/Audio/ or ~/Audio/speak/ doesn't exist and isn't auto-created, the command might fail silently or with an error.

3. Article is a PDF or URL - If the user provides a PDF, I'd need to convert it first with pdftotext. If it's a URL, the docs don't explain how to fetch web content at all.

4. Article is too long - If the article is very long, I might hit the 300-second timeout. The docs suggest --auto-chunk for long content, but I don't know the article length upfront.

5. First run setup - If this is the first time running the tool, it might need setup time. The docs mention "Cold start: ~4-8s" but also "Auto-setup on first run" - unclear if setup is blocking or if it happens transparently.

Suggested Improvements

1. Add clipboard example - The description promises clipboard support but docs never show it:

   # Read from clipboard
   pbpaste | speak --output ~/Audio/clipboard.wav
   # OR if there's native support:
   speak --clipboard --output ~/Audio/clipboard.wav

2. Clarify default output filename - Add a clear example:

   # Without --output, saves to ~/Audio/speak/<input_name>.wav
   speak article.txt
   # Creates: ~/Audio/speak/article.wav
   
   speak "Hello world"
   # Creates: ~/Audio/speak/speak_<timestamp>.wav (or whatever it actually does)

3. Clarify default directory creation - Either:

• State that ~/Audio/speak/ IS auto-created as the default
• Or add to Quick Start: mkdir -p ~/Audio/speak/ as step 0

4. Add "save for later" pattern - Under Common Patterns, add:

   ### Save Audio for Later (No Playback)
   speak document.txt --output ~/Audio/saved.wav
   # Generates file without playing - for later listening

5. Add URL/web article handling - Since "news article" often means a URL:

   # Fetch and convert web article (requires curl + html2text)
   curl -s "https://example.com/article" | html2text | speak --output article.wav

6. Clarify what happens without --stream/--play/--output - What's the actual default behavior? Does it just print to stdout? Save to default location? This is never stated.

---

anthropic/claude-sonnet-4.5

Status: success (33.0s, $0.034)

Understanding

The tool is a local text-to-speech system for Apple Silicon Macs that converts text to audio using Chatterbox TTS. It can handle various text formats, supports streaming playback, custom voice cloning, auto-chunking for long documents, and batch processing. The tool runs entirely on-device and outputs 24kHz mono WAV files.

Approach

To complete this task, I would:

1. Verify prerequisites - Check if running on Apple Silicon Mac with required dependencies 2. Obtain the article text - The task says "this news article" but no article is provided. I would need to:

• Ask the user for the article (URL, file path, or text)
• Or check if there's a clipboard/context I should access

3. Determine input format - Check if it's a URL (needs conversion), PDF (needs pdftotext), or plain text 4. Generate the audio file:

   speak article.txt --output ~/Audio/news_article.wav

Or if it's a long article:

   speak article.txt --auto-chunk --output ~/Audio/news_article.wav

5. Verify the output - Confirm the WAV file was created at the specified location

Confusions

1. Missing input source: The task says "Read this news article" but no article is provided in the documentation or task description. The documentation doesn't explain how to handle:

• URLs (does the tool fetch web content?)
• Clipboard content (mentioned in the description: "generating speech from clipboard content" but no --clipboard flag documented)
• Piped input from stdin

2. Ambiguous "read aloud": Does "read aloud" mean:

• Generate and play immediately? (use --play)
• Just generate the file? (use --output)
• Stream while generating? (use --stream)

The task says "save as an audio file I can listen to later" which suggests just generating without playing, but "read aloud" typically implies immediate playback.

3. Default output location: The documentation states:

--output <path> | Output file (.wav) or directory | ~/Audio/speak/

But it's unclear if this means:

• Default output directory is ~/Audio/speak/ with auto-generated filename?
• Or is ~/Audio/speak/ just an example?
• What is the auto-generated filename format?

4. No URL/web fetching documented: The description mentions "reading articles" but there's no documentation on how to fetch web content. Do I need to manually download/convert first?

Potential Failures

1. No article provided - I cannot complete the task without knowing what article to read 2. Article is a URL - No documented way to fetch web content; would need external tool like curl or wget first 3. Article is in unsupported format - If it's PDF/DOCX/HTML, I'd need to convert it first (documented for PDF, but not for HTML) 4. Output directory doesn't exist - Documentation warns "Output directories are NOT auto-created" but doesn't specify if parent directories of --output files are auto-created 5. Article too long - Might timeout without --auto-chunk, but no guidance on when to use it (documentation says ">10 minutes of audio" but how do I know length before generating?) 6. Clipboard access - If the article is supposed to come from clipboard (mentioned in description), there's no documented way to access it

Suggested Improvements

1. Add stdin/clipboard input documentation:

   # From clipboard
   speak --clipboard --output article.wav
   
   # From stdin
   curl https://example.com/article | speak --output article.wav
   
   # From URL directly
   speak --url https://example.com/article --output article.wav

2. Clarify default output behavior:

   When --output is omitted:
   - Single file: Saves to ~/Audio/speak/<input_filename>.wav
   - Direct text: Saves to ~/Audio/speak/output_<timestamp>.wav
   - Creates ~/Audio/speak/ directory if it doesn't exist

3. Add decision tree for common tasks:

   "Read article aloud and save for later":
   → speak article.txt --output ~/Audio/article.wav
   
   "Read article aloud now":
   → speak article.txt --stream
   
   "Read article aloud now AND save":
   → speak article.txt --stream --output ~/Audio/article.wav

4. Document web content workflow:

   # Fetch and convert web article
   curl -s https://example.com/article | \
     pandoc -f html -t plain | \
     speak --output article.wav

5. Add auto-chunk decision guidance:

   Use --auto-chunk when:
   - Article is >25,000 characters (~10 pages)
   - Estimated generation time >5 minutes
   - You see timeout errors
   
   Check first: speak --estimate article.txt

6. Clarify "read aloud" terminology: Add a glossary section explaining that "read aloud" in the context of TTS means "convert to speech audio" not necessarily "play immediately."

7. Add example for the exact task given:

   # Task: Read news article aloud and save for later
   # Assuming article is in article.txt
   speak article.txt --output ~/Audio/news_article.wav
   
   # Listen later
   afplay ~/Audio/news_article.wav

---

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Run 01KENJMNHXEDHDZ8Z5DK9QQJP8 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Date: 2026-01-11T03:47:17.181Z Skill: /Users/jay/Documents/speak_optiimisation/iterations/SKILL_v3.md Task: Clone my voice from a 30 second sample and read my presentation notes aloud Status: completed ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

anthropic/claude-haiku-4.5

Status: success (19.5s, $0.003)

Understanding

The tool is a local TTS system that converts text to speech using Chatterbox TTS on Apple Silicon. It supports custom voices from WAV samples, batch processing, and various output modes (stream, play, save). The documentation claims voice cloning capability in the description but provides limited detail on how to actually do it.

Approach

Based on the documentation, here's how I would attempt this task:

1. Prepare the voice sample:

• Ensure I have a 30-second WAV file (the docs say "10-30 seconds" is acceptable)
• Verify it's 24kHz mono format, clear speech, minimal background noise
• Place it in ~/.chatter/voices/ directory

2. Use the custom voice:

• Run: speak presentation_notes.txt --voice ~/.chatter/voices/my_voice.wav --stream
• Or save it: speak presentation_notes.txt --voice ~/.chatter/voices/my_voice.wav --output presentation.wav

3. Play the result:

• If using --stream, it plays immediately
• If using --output, play later with: afplay presentation.wav

Confusions

1. "Voice cloning" is undefined. The tool description says it supports "voice cloning" but the documentation only describes using pre-recorded voice samples. There is no explanation of what "cloning" means here—is it:

• Simply using a custom voice sample as-is?
• Some ML process that learns from the sample?
• Something else?

2. Voice sample preparation is unclear. The docs state:

"WAV format, 10-30 seconds, 24kHz mono preferred, Clear speech, minimal background noise"

But don't explain:

• How to convert my sample to 24kHz mono if it isn't already
• What happens if I use a different format (will it fail silently or error?)
• Whether "preferred" means required or optional

3. No voice training/setup process documented. The docs show checking for existing voices (ls ~/.chatter/voices/*.wav) but don't explain how to create or train a custom voice from a sample. Is there a setup step? Does the tool automatically process the sample on first use?

4. Unclear if voice sample is used directly or processed. When I provide --voice ~/.chatter/voices/my_voice.wav, does the tool:

• Use it as-is for synthesis?
• Analyze it and create a voice model?
• Something else?

5. No error handling for voice quality. The docs don't specify what happens if my sample is:

• Too short (< 10 seconds)
• Too long (> 30 seconds)
• Wrong format
• Poor quality (background noise, unclear speech)

Potential Failures

1. Voice sample format mismatch: If my 30-second sample isn't in WAV format or isn't 24kHz mono, the tool might fail silently or produce poor results. The docs don't specify error messages.

2. Voice file not found error: If I mistype the path or the file doesn't exist, I'll get the documented error "Voice file not found" but the docs only say "Use full path"—they don't explain how to verify the path works first.

3. No voice model created: If the tool requires a setup/training step that isn't documented, simply placing a WAV file in ~/.chatter/voices/ might not work.

4. Presentation notes format issue: The docs don't specify what format the presentation notes should be in. If they're in PPTX, PDF, or another format, I'd need to convert them first (docs show how for PDF/DOCX but not PPTX).

5. Directory doesn't exist: If ~/.chatter/voices/ doesn't exist, the tool might fail. The docs say "Save to ~/.chatter/voices/" but don't confirm this directory is auto-created.

6. Timeout on long presentation: If the presentation notes are very long, generation might timeout without --auto-chunk.

Suggested Improvements

1. Define "voice cloning" explicitly:

   ### Voice Cloning
   Voice cloning uses your voice sample to synthesize speech in your voice.
   The tool analyzes your sample and applies your voice characteristics to 
   new text. This happens automatically when you provide a voice file.

2. Add voice sample preparation instructions:

   ### Preparing Your Voice Sample
   
   Your sample must be:
   - **Format:** WAV only (required)
   - **Duration:** 10-30 seconds (required)
   - **Sample rate:** 24kHz mono (required - convert with: sox input.wav -r 24000 -c 1 output.wav)
   - **Quality:** Clear speech, minimal background noise
   
   If your sample doesn't meet these specs, the tool will error with: 
   "Invalid voice sample: [reason]"

3. Add voice setup/initialization step:

   ### Setting Up a Custom Voice
   
   1. Prepare your voice sample (see above)
   2. Place in: ~/.chatter/voices/my_voice.wav
   3. Initialize the voice (first use only):
      speak setup --voice ~/.chatter/voices/my_voice.wav
   4. Verify it works:
      speak "Hello, this is a test." --voice ~/.chatter/voices/my_voice.wav --stream

4. Add troubleshooting for voice files:

   | Error | Cause | Solution |
   |-------|-------|----------|
   | "Invalid voice sample format" | Not WAV or wrong sample rate | Convert: `sox input.wav -r 24000 -c 1 output.wav` |
   | "Voice sample too short" | < 10 seconds | Provide 10-30 second sample |
   | "Voice sample too long" | > 30 seconds | Trim to 30 seconds max |
   | "Voice quality too poor" | Background noise/unclear speech | Re-record in quiet environment |

5. Add presentation notes conversion examples:

   ### Converting Presentation Notes
   
   | Format | Convert First |
   |--------|--------------|
   | PowerPoint (.pptx) | `python3 -c "from pptx import Presentation; p = Presentation('notes.pptx'); print('\n'.join([s.text for slide in p.slides for s in slide.shapes if hasattr(s, 'text')]))" > notes.txt` |
   | Google Slides | Export as PDF, then: `pdftotext slides.pdf notes.txt` |
   | Plain text | Use directly: `speak notes.txt --voice ~/.chatter/voices/my_voice.wav` |

6. Clarify voice directory auto-creation:

   The ~/.chatter/voices/ directory is NOT auto-created. Create it first:
   mkdir -p ~/.chatter/voices/

7. Add a complete example for this specific task:

   ### Example: Clone Your Voice for Presentations
   
   # 1. Prepare your voice sample
   sox my_voice_recording.mp3 -r 24000 -c 1 ~/.chatter/voices/my_voice.wav
   
   # 2. Convert presentation notes (if needed)
   pdftotext presentation.pdf notes.txt
   
   # 3. Generate audio with your voice
   speak notes.txt --voice ~/.chatter/voices/my_voice.wav --stream
   
   # 4. Or save for later
   speak notes.txt --voice ~/.chatter/voices/my_voice.wav --output presentation_audio.wav

8. Document voice quality expectations:

   ### Voice Quality Notes
   
   - Cloned voice quality depends on sample quality
   - Background noise in sample will appear in output
   - Accents and speech patterns are preserved
   - Emotional tone of sample may influence output
   - For best results: quiet room, clear diction, natural pace

---

anthropic/claude-opus-4.5

Status: success (26.9s, $0.149)

Understanding

The tool is a local text-to-speech system for Apple Silicon Macs. It can generate speech from text files, and supports custom voices via WAV samples. The documentation describes voice cloning as a use case in the description, but the actual mechanism is simply providing a voice sample file via --voice.

Approach

1. Prepare the voice sample:

• Ensure my 30-second recording is in WAV format, 24kHz mono, with clear speech and minimal background noise
• Save it to ~/.chatter/voices/myvoice.wav

2. Prepare the presentation notes:

• Ensure notes are in a supported format (.txt or .md)
• If in another format, convert first (e.g., textutil -convert txt notes.docx)

3. Generate speech:

   speak notes.txt --voice ~/.chatter/voices/myvoice.wav --stream

4. Or save for later:

   speak notes.txt --voice ~/.chatter/voices/myvoice.wav --output ~/Audio/presentation.wav

Confusions

1. "Voice cloning" is mentioned but never explained:

"Use this when users request... voice cloning"

The description promises voice cloning, but the documentation never uses that term again. Is providing a voice sample the same as "cloning"? Does the tool actually clone/replicate the voice characteristics, or just use it as a reference? This is completely unclear.

2. Voice sample requirements are vague:

"WAV format, 10-30 seconds"

"24kHz mono preferred"

"Preferred" is ambiguous. Will other sample rates work? Will stereo work? What happens if my sample is 44.1kHz stereo—will it fail, auto-convert, or produce bad results?

3. No instructions for creating the voices directory: The docs say to save to ~/.chatter/voices/ but never mention creating this directory. Does it exist by default? Do I need mkdir -p ~/.chatter/voices/ first?

4. No validation or feedback mechanism: How do I know if my voice sample is acceptable? Is there a command to test/validate a voice file before using it?

5. "Clear speech, minimal background noise" is subjective: What's the threshold? Will it fail with some background noise, or just produce worse results?

Potential Failures

1. Voice sample format mismatch: If my 30-second sample is MP3, M4A, or wrong sample rate, I don't know how to convert it or if the tool will reject it.

2. Missing directory: If ~/.chatter/voices/ doesn't exist and I try to save there, the copy will fail.

3. Misunderstanding "voice cloning": The tool might just use the sample as a reference tone rather than actually cloning my voice. I might expect it to sound like me and be disappointed.

4. Long presentation: If my notes are long, I might hit the timeout without knowing to use --auto-chunk.

Suggested Improvements

1. Add a dedicated "Voice Cloning" section:

   ## Voice Cloning
   
   The tool replicates voice characteristics from a sample recording.
   
   ### Creating a Voice Sample
   1. Record 10-30 seconds of clear speech
   2. Convert to WAV format: `ffmpeg -i recording.m4a -ar 24000 -ac 1 myvoice.wav`
   3. Create the voices directory: `mkdir -p ~/.chatter/voices/`
   4. Save: `mv myvoice.wav ~/.chatter/voices/`
   
   ### Validating Your Sample

speak "Test sentence" --voice ~/.chatter/voices/myvoice.wav --play

   
   ### What to Expect
   The output will approximate your voice's tone and cadence. It won't be a perfect replica.

2. Add format conversion instructions:

   ### Converting Voice Samples
   | Source Format | Convert Command |
   |---------------|-----------------|
   | MP3 | `ffmpeg -i voice.mp3 -ar 24000 -ac 1 voice.wav` |
   | M4A | `ffmpeg -i voice.m4a -ar 24000 -ac 1 voice.wav` |
   | Stereo WAV | `ffmpeg -i voice.wav -ar 24000 -ac 1 voice_mono.wav` |

3. Clarify "preferred" requirements: Change:

"24kHz mono preferred"

To:

"24kHz mono required. Other formats will fail/produce degraded results. Convert with: ffmpeg -i input.wav -ar 24000 -ac 1 output.wav"

4. Add directory creation to voice setup:

"Save to ~/.chatter/voices/ (create first: mkdir -p ~/.chatter/voices/)"

5. Set expectations for voice cloning quality: Add a note like: "Voice cloning captures general characteristics (pitch, cadence) but is not a perfect replica. Results vary based on sample quality."

---

anthropic/claude-sonnet-4.5

Status: success (39.1s, $0.039)

Understanding

The tool is a local TTS system for Apple Silicon that can:

• Generate speech from text using a default voice OR custom voice samples
• Clone voices from WAV samples (10-30 seconds)
• Read various text formats aloud
• Stream or save audio output

For voice cloning, I need to provide a WAV file and use --voice flag with the full path.

Approach

1. Prepare the voice sample:

• Ensure the 30-second sample is in WAV format, 24kHz mono
• Save it to ~/.chatter/voices/my_voice.wav

   mkdir -p ~/.chatter/voices/
   cp /path/to/sample.wav ~/.chatter/voices/my_voice.wav

2. Prepare presentation notes:

• Assume notes are in a file like presentation.txt or presentation.md

3. Generate speech with cloned voice:

   speak presentation.txt --voice ~/.chatter/voices/my_voice.wav --stream

OR to save for later:

   speak presentation.txt --voice ~/.chatter/voices/my_voice.wav --output ~/Audio/presentation.wav

4. If notes are long (>10 min estimated):

   speak --estimate presentation.txt
   # If >10 min, add --auto-chunk:
   speak presentation.txt --voice ~/.chatter/voices/my_voice.wav --auto-chunk --stream

Confusions

1. "Clone my voice from a 30 second sample" - The documentation never uses the word "clone" or explains what voice cloning means in this context. Does --voice actually clone/train on the sample, or does it just use it as a reference? The docs say "Voice sample requirements" but don't explain the mechanism.

2. Voice sample format conversion - The docs say "WAV format, 10-30 seconds, 24kHz mono preferred" but provide ZERO guidance on:

• How to convert an existing audio file to this format
• What happens if it's not 24kHz mono (does it fail? auto-convert?)
• What "preferred" means (will it work with stereo? 48kHz?)

3. Where does the voice sample come from? - The task says "from a 30 second sample" but doesn't specify the format. The docs don't explain:

• Can I record directly with this tool?
• Do I need external recording software?
• How to extract 30 seconds from a longer recording?

4. "Read my presentation notes aloud" - Does this mean:

• Stream it now (--stream)?
• Save it for later playback?
• Both (--stream --output)?

The task is ambiguous about the desired output mode.

5. Voice quality expectations - No information about:

• How accurate the voice cloning is
• Whether 30 seconds is enough for good quality
• What makes a "good" voice sample (reading style? tone?)

Potential Failures

1. Voice sample in wrong format - If my sample is MP3, M4A, or any non-WAV format, the command will likely fail with "Voice file not found" or similar error. No conversion guidance provided.

2. Voice sample wrong specs - If my WAV is 48kHz stereo, unclear if it will:

• Fail with an error
• Work but sound bad
• Auto-convert (unlikely based on doc tone)

3. Path issues - If I use relative path like --voice my_voice.wav instead of full path ~/.chatter/voices/my_voice.wav, it will fail per the docs: "FULL PATH REQUIRED"

4. Directory doesn't exist - If ~/.chatter/voices/ doesn't exist and I try to save there, unclear if it auto-creates (docs only say ~/Audio/speak/ is auto-created)

5. Presentation notes format - If notes are in PDF, DOCX, or HTML, I need to convert first, but the task doesn't specify format

6. Long presentation - If notes are very long and I don't use --auto-chunk, might hit the 300-second timeout

7. No sox installed - If presentation is long enough to trigger chunking, sox is required but might not be installed

Suggested Improvements

1. Add voice cloning explanation section:

   ## Voice Cloning
   
   The `--voice` flag uses your sample as a reference for voice characteristics.
   The TTS model adapts its output to match the prosody, tone, and timbre of your sample.
   
   **Recording your sample:**
   - Use QuickTime Player: File > New Audio Recording
   - Record 10-30 seconds of clear speech
   - Read naturally in the style you want for output
   - Save as: File > Export > Audio Only

2. Add audio format conversion section:

   ## Converting Audio Formats
   
   If your voice sample isn't WAV format:
   

Convert any audio to required format

ffmpeg -i input.mp3 -ar 24000 -ac 1 output.wav

Or using sox

sox input.m4a -r 24000 -c 1 output.wav

   
   **Required specs:**
   - Format: WAV
   - Sample rate: 24000 Hz (24kHz)
   - Channels: 1 (mono)
   - Non-compliant files will fail with error: [specific error message]

3. Clarify "read aloud" in examples:

   ## Read Aloud (Listen Now)
   
   To hear your text immediately:

speak notes.txt --stream # Starts playing as it generates

   
   To save AND listen:

speak notes.txt --stream --output presentation.wav

4. **Add complete voice cloning workflow:**

Complete Voice Cloning Workflow

1. Record your voice sample (10-30 seconds) 2. Convert to required format 3. Save to voices directory 4. Use with --voice flag

   # Step 1: Record with QuickTime or:
   sox -d -r 24000 -c 1 recording.wav trim 0 30
   
   # Step 2: Save to voices directory
   mkdir -p ~/.chatter/voices/
   mv recording.wav ~/.chatter/voices/my_voice.wav
   
   # Step 3: Use it
   speak "Test" --voice ~/.chatter/voices/my_voice.wav --stream

5. Add troubleshooting for voice files:

   | Error | Cause | Solution |
   |-------|-------|----------|
   | "Invalid WAV format" | Wrong sample rate/channels | Convert: `sox input.wav -r 24000 -c 1 output.wav` |
   | "Voice file too short" | <10 seconds | Record longer sample |
   | "Voice file too long" | >30 seconds | Trim: `sox input.wav output.wav trim 0 30` |

6. Specify auto-created directories explicitly:

   ## Directory Auto-Creation
   
   **Auto-created:** Only `~/Audio/speak/`
   **NOT auto-created:** `~/.chatter/voices/`, custom output dirs
   
   Always create directories before use:

mkdir -p ~/.chatter/voices/ mkdir -p ~/Audio/custom/

---

speak - Text to Speech for Agents

Convert text to natural speech audio using Chatterbox TTS on Apple Silicon.

Quick Start

# Stream audio (recommended - starts playing immediately)
speak "Hello, I'm your AI assistant." --stream

# Generate and play after completion
speak "Let me read that for you." --play

# Generate audio file with specific name
speak "Hello" --output ~/Audio/greeting.wav

# Check duration estimate before generating
speak --estimate document.md

Common Patterns

Reading Documents to Users

# Best for long documents - starts playing within ~3s
speak document.md --stream

# For very long documents - auto-chunk for reliability
speak long-book-chapter.md --auto-chunk --output chapter.wav

Quick Responses

# Stream for lowest latency to first audio
speak "I've completed that task for you." --stream

# Or generate then play (waits for full generation)
speak "Done!" --play

Background Audio Generation

# Generate audio file for later use
speak "Welcome to our service" --output ~/Audio/welcome.wav

# Preview estimate without generating
speak --estimate "Long text here..."

Batch Processing Multiple Files

# Process multiple files at once
speak chapter1.md chapter2.md chapter3.md --output-dir ~/Audio/book/

# Skip files that already have output
speak chapters/*.md --output-dir ~/Audio/book/ --skip-existing

Long Document Workflow

# For documents that might timeout (>5 min generation)
speak book-chapter.md --auto-chunk --output chapter.wav

# If interrupted, resume from where it left off
speak --resume ~/Audio/speak/manifest.json

# Keep intermediate chunks for inspection
speak document.md --auto-chunk --output doc.wav --keep-chunks

Concatenating Audio Files

# Combine multiple audio files
speak concat part1.wav part2.wav part3.wav --out combined.wav

Options Reference

Commands

Performance

• Cold start: ~4-8s to first audio (model loading + generation)
• Warm start: ~3-8s to first audio (model already loaded)
• Generation speed: ~0.3-0.5x RTF on Apple Silicon (faster than real-time)
• Streaming: Audio starts after first chunk (~250 chars)

Estimation

# Get time estimate before committing
speak --estimate document.md

# Output:
# Input: 24,011 characters (~4,800 words)
# Estimated audio: ~25 minutes
# Estimated generation time: ~12 minutes
# RTF: 0.40x

Long Document Handling

For documents that exceed the 5-minute timeout:

1. Auto-chunking splits text at sentence boundaries 2. Progressive saving - each chunk saved immediately 3. Resume capability - continue from where you left off

# Generate with auto-chunking (recommended for >10 min audio)
speak long-document.md --auto-chunk --output output.wav

# If it fails partway through, resume:
speak --resume ~/Audio/speak/manifest.json

Voice Cloning & Multi-Voice Content

Discovering Available Voices

Voice samples are stored in ~/.chatter/voices/. Always check what's available:

# List available voice samples
ls ~/.chatter/voices/*.wav 2>/dev/null

# Example output:
# alan_watts.wav
# david_attenborough.wav
# morgan_freeman.wav
# stephen_fry.wav
# ursula_leguin.wav

Using a Custom Voice

Always use the full path to voice files:

# Clone a specific voice (full path required)
speak "Hello world" --voice ~/.chatter/voices/morgan_freeman.wav --stream

Important: Do not use just the filename (e.g., --voice morgan_freeman.wav).

Always use the full path: --voice ~/.chatter/voices/morgan_freeman.wav

Multi-Voice Content (Debates, Dramas, Podcasts)

For content with multiple speakers:

1. Split script into separate files per speaker

   01_host_intro.txt
   02_guest1_response.txt
   03_host_followup.txt
   04_guest2_rebuttal.txt

2. Generate each segment with appropriate voice (use full paths)

   speak 01_host_intro.txt --voice ~/.chatter/voices/stephen_fry.wav --output wav/01.wav
   speak 02_guest1_response.txt --voice ~/.chatter/voices/morgan_freeman.wav --output wav/02.wav
   speak 03_host_followup.txt --voice ~/.chatter/voices/stephen_fry.wav --output wav/03.wav
   speak 04_guest2_rebuttal.txt --voice ~/.chatter/voices/ursula_leguin.wav --output wav/04.wav

3. Concatenate in order

   speak concat wav/*.wav --out final_debate.wav

Adding New Voice Samples

To add a new voice for cloning: 1. Get a clean 10-30 second audio sample (WAV format, clear speech, minimal background noise) 2. Save to ~/.chatter/voices/speaker_name.wav 3. The voice is now available via --voice speaker_name.wav

Emotion Tags

Add expressive sounds inline with text:

speak "[sigh] I can't believe it's Monday again." --stream
speak "[laugh] That's hilarious!" --stream

Supported Tags

Note: [pause] and [whisper] are NOT supported. Use punctuation for pauses.

Setup

First run automatically sets up the environment:

speak "test"  # Auto-setup on first run

Or manually: speak setup

Server Management

Server auto-starts and shuts down after 1 hour idle.

speak health        # Check status
speak daemon kill   # Stop manually

Additional Documentation

For more details, see:

• docs/usage.md - Complete usage guide with all options
• docs/configuration.md - Config file, environment variables
• docs/troubleshooting.md - Common issues and fixes

Notes

• Requires Apple Silicon Mac (M1/M2/M3)
• Requires sox for auto-chunking: brew install sox
• Audio format: WAV 24kHz mono
• Use --stream for text longer than a few sentences
• Use --auto-chunk for documents >10 minutes of audio