Delegate independent tasks to specialized agents working concurrently with isolated context.
Audio Converter
audio-converter
Convert audio files between formats (MP3, WAV, FLAC, OGG, M4A) with bitrate and sample rate control. Batch processing supported.
SKILL.md
Full skill instructions
Audio Converter
Convert audio files between popular formats with control over quality settings. Supports batch processing and maintains metadata where possible.
Quick Start
from scripts.audio_converter import AudioConverter
# Simple conversion
converter = AudioConverter("input.wav")
converter.convert("output.mp3")
# With quality settings
converter = AudioConverter("input.flac")
converter.bitrate(320).sample_rate(44100).convert("output.mp3")
# Batch convert directory
AudioConverter.batch_convert("./input_folder", "./output_folder", format="mp3", bitrate=192)
Features
- Format Support: MP3, WAV, FLAC, OGG, M4A/AAC, AIFF
- Quality Control: Bitrate, sample rate, channels
- Metadata Preservation: Copy tags when possible
- Batch Processing: Convert entire directories
- Normalization: Optional volume normalization
API Reference
Initialization
# From file
converter = AudioConverter("audio.wav")
Settings
converter.bitrate(192) # kbps (for lossy formats)
converter.sample_rate(44100) # Hz
converter.channels(2) # 1=mono, 2=stereo
converter.normalize(True) # Normalize volume
Conversion
# Convert to format (inferred from extension)
converter.convert("output.mp3")
# Explicit format
converter.convert("output", format="mp3")
Batch Processing
# Convert all files in directory
AudioConverter.batch_convert(
input_dir="./wavs",
output_dir="./mp3s",
format="mp3",
bitrate=320
)
CLI Usage
# Simple conversion
python audio_converter.py --input song.wav --output song.mp3
# With quality settings
python audio_converter.py --input song.flac --output song.mp3 --bitrate 320 --sample-rate 44100
# Batch convert
python audio_converter.py --input-dir ./wavs --output-dir ./mp3s --format mp3 --bitrate 192
# Normalize during conversion
python audio_converter.py --input song.wav --output song.mp3 --normalize
CLI Arguments
| Argument | Description | Default |
|---|---|---|
--input | Input audio file | Required |
--output | Output file path | Required |
--input-dir | Input directory for batch | - |
--output-dir | Output directory for batch | - |
--format | Output format | From extension |
--bitrate | Bitrate in kbps | 192 |
--sample-rate | Sample rate in Hz | Original |
--channels | Number of channels | Original |
--normalize | Normalize volume | False |
Supported Formats
| Format | Extension | Type | Notes |
|---|---|---|---|
| MP3 | .mp3 | Lossy | Most compatible |
| WAV | .wav | Lossless | Large files |
| FLAC | .flac | Lossless | Compressed lossless |
| OGG | .ogg | Lossy | Open format |
| M4A | .m4a | Lossy | AAC codec |
| AIFF | .aiff | Lossless | Apple format |
Examples
Convert WAV to MP3
converter = AudioConverter("recording.wav")
converter.bitrate(320).convert("recording.mp3")
Convert FLAC to Multiple Formats
source = AudioConverter("album.flac")
# High quality MP3
source.bitrate(320).convert("album_hq.mp3")
# Standard MP3
source.bitrate(192).convert("album_std.mp3")
# OGG for streaming
source.bitrate(128).convert("album.ogg")
Batch Convert for Podcast
# Convert all WAV recordings to MP3 with podcast settings
AudioConverter.batch_convert(
input_dir="./raw_episodes",
output_dir="./episodes",
format="mp3",
bitrate=128,
sample_rate=44100,
channels=1 # Mono for podcasts
)
Dependencies
pydub>=0.25.0
soundfile>=0.12.0
Note: Requires FFmpeg installed on system for MP3/M4A support.
Limitations
- Requires FFmpeg for MP3 and M4A formats
- Metadata transfer is best-effort
- Some format combinations may not preserve all tags
More Other skills
brand-guidelines
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
theme-factory
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
internal-comms
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Fundamental design principles for writing maintainable, testable Python code.
responsive-design
Modern responsive layouts using container queries, fluid typography, CSS Grid, and mobile-first strategies.
Generate Playwright tests from scenarios using interactive browser exploration and validation.
Automated website exploration and test case generation using Playwright.
Modern React state management with Redux Toolkit, Zustand, Jotai, and React Query for every state category.
gdpr-data-handling
GDPR-compliant data handling with consent management, data subject rights, and privacy controls.
Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.
refactor-plan
Detailed multi-file refactor planning with safety checks and rollback guidance.
