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David-Li0406/meta-skill-evloving

Audio and video processing with FFmpeg, WebRTC, and streaming. Covers transcoding, format conversion, real-time communication, and media pipelines. Use for video processing, live streaming, or audio manipulation.

meta-skill-evloving 是什么?

meta-skill-evloving is a Claude Code agent skill that audio and video processing with FFmpeg, WebRTC, and streaming. Covers transcoding, format conversion, real-time communication, and media pipelines. Use for video processing, live streaming, or audio manipulation.

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Audio & Video Processing Skill

Complete guide for audio and video processing.

Quick Reference

FFmpeg Commands

TaskCommand
Convertffmpeg -i input.mp4 output.webm
Extract Audioffmpeg -i video.mp4 -vn audio.mp3
Thumbnailffmpeg -i video.mp4 -ss 5 -frames:v 1 thumb.jpg
Resizeffmpeg -i input.mp4 -vf scale=1280:720 output.mp4
Compressffmpeg -i input.mp4 -crf 28 output.mp4

Common Formats

Video: MP4, WebM, MKV, AVI, MOV
Audio: MP3, AAC, WAV, FLAC, OGG
Codecs: H.264, H.265/HEVC, VP9, AV1

1. FFmpeg Basics

Installation

# Ubuntu/Debian
sudo apt install ffmpeg

# macOS
brew install ffmpeg

# Windows (Chocolatey)
choco install ffmpeg

Basic Conversion

# Video format conversion
ffmpeg -i input.avi output.mp4

# Audio format conversion
ffmpeg -i input.wav output.mp3

# With codec specification
ffmpeg -i input.mp4 -c:v libx264 -c:a aac output.mp4

Video Quality Control

# CRF (Constant Rate Factor) - 0-51, lower = better quality
ffmpeg -i input.mp4 -c:v libx264 -crf 23 output.mp4

# Bitrate control
ffmpeg -i input.mp4 -c:v libx264 -b:v 2M output.mp4

# Two-pass encoding for better quality
ffmpeg -i input.mp4 -c:v libx264 -b:v 2M -pass 1 -f null /dev/null
ffmpeg -i input.mp4 -c:v libx264 -b:v 2M -pass 2 output.mp4

2. Video Processing

Resize and Scale

# Scale to specific resolution
ffmpeg -i input.mp4 -vf "scale=1920:1080" output.mp4

# Scale maintaining aspect ratio
ffmpeg -i input.mp4 -vf "scale=1280:-1" output.mp4  # Auto height
ffmpeg -i input.mp4 -vf "scale=-1:720" output.mp4   # Auto width

# Scale with padding (letterbox)
ffmpeg -i input.mp4 -vf "scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:(ow-iw)/2:(oh-ih)/2" output.mp4

Trim and Cut

# Cut from timestamp to timestamp
ffmpeg -i input.mp4 -ss 00:01:00 -to 00:02:00 -c copy output.mp4

# Cut with duration
ffmpeg -i input.mp4 -ss 00:01:00 -t 30 -c copy output.mp4

# Fast seek (put -ss before input)
ffmpeg -ss 00:01:00 -i input.mp4 -t 30 -c copy output.mp4

Concatenate Videos

# Create file list
echo "file 'video1.mp4'" > list.txt
echo "file 'video2.mp4'" >> list.txt
echo "file 'video3.mp4'" >> list.txt

# Concatenate
ffmpeg -f concat -safe 0 -i list.txt -c copy output.mp4

Add Watermark

# Image watermark
ffmpeg -i input.mp4 -i logo.png -filter_complex "overlay=10:10" output.mp4

# Bottom right corner
ffmpeg -i input.mp4 -i logo.png -filter_complex "overlay=W-w-10:H-h-10" output.mp4

# Text watermark
ffmpeg -i input.mp4 -vf "drawtext=text='Copyright':fontsize=24:fontcolor=white:x=10:y=10" output.mp4

Speed Adjustment

# Speed up 2x
ffmpeg -i input.mp4 -filter:v "setpts=0.5*PTS" -filter:a "atempo=2.0" output.mp4

# Slow down 0.5x
ffmpeg -i input.mp4 -filter:v "setpts=2*PTS" -filter:a "atempo=0.5" output.mp4

3. Audio Processing

Extract Audio

# Extract audio track
ffmpeg -i video.mp4 -vn -c:a copy audio.aac

# Convert to MP3
ffmpeg -i video.mp4 -vn -c:a libmp3lame -q:a 2 audio.mp3

# Extract specific audio stream
ffmpeg -i video.mp4 -map 0:a:0 -c copy audio.m4a

Audio Conversion

# WAV to MP3
ffmpeg -i input.wav -c:a libmp3lame -b:a 320k output.mp3

# FLAC to MP3
ffmpeg -i input.flac -c:a libmp3lame -q:a 0 output.mp3

# MP3 to AAC
ffmpeg -i input.mp3 -c:a aac -b:a 256k output.m4a

Audio Normalization

# Loudnorm filter (EBU R128)
ffmpeg -i input.mp3 -af loudnorm=I=-16:LRA=11:TP=-1.5 output.mp3

# Volume adjustment
ffmpeg -i input.mp3 -af "volume=2.0" output.mp3  # 2x louder
ffmpeg -i input.mp3 -af "volume=0.5" output.mp3  # Half volume

# Peak normalization
ffmpeg -i input.mp3 -af "acompressor" output.mp3

Merge Audio/Video

# Replace audio track
ffmpeg -i video.mp4 -i audio.mp3 -c:v copy -c:a aac -map 0:v -map 1:a output.mp4

# Add audio to video (mix)
ffmpeg -i video.mp4 -i audio.mp3 -c:v copy -filter_complex "[0:a][1:a]amix=inputs=2:duration=first" output.mp4

4. Thumbnails and Screenshots

Single Thumbnail

# At specific time
ffmpeg -i video.mp4 -ss 00:00:05 -frames:v 1 thumbnail.jpg

# Best quality
ffmpeg -i video.mp4 -ss 00:00:05 -frames:v 1 -q:v 2 thumbnail.jpg

# Specific size
ffmpeg -i video.mp4 -ss 00:00:05 -frames:v 1 -vf "scale=320:180" thumbnail.jpg

Multiple Thumbnails

# Every N seconds
ffmpeg -i video.mp4 -vf "fps=1/10" thumbnails_%03d.jpg  # Every 10 seconds

# Specific number of thumbnails
ffmpeg -i video.mp4 -vf "select='not(mod(n,300))'" -vsync vfr thumb_%03d.jpg

# Thumbnail sprite/grid
ffmpeg -i video.mp4 -vf "fps=1/10,scale=160:90,tile=10x10" sprite.jpg

GIF Creation

# Simple GIF
ffmpeg -i video.mp4 -ss 0 -t 5 -vf "fps=10,scale=320:-1" output.gif

# High quality GIF with palette
ffmpeg -i video.mp4 -ss 0 -t 5 -vf "fps=10,scale=320:-1:flags=lanczos,palettegen" palette.png
ffmpeg -i video.mp4 -i palette.png -ss 0 -t 5 -filter_complex "[0:v]fps=10,scale=320:-1:flags=lanczos[x];[x][1:v]paletteuse" output.gif

5. Streaming Formats

HLS (HTTP Live Streaming)

# Generate HLS
ffmpeg -i input.mp4 \
  -c:v libx264 -c:a aac \
  -hls_time 10 \
  -hls_list_size 0 \
  -hls_segment_filename "segment_%03d.ts" \
  output.m3u8

# Adaptive bitrate HLS
ffmpeg -i input.mp4 \
  -filter_complex "[0:v]split=3[v1][v2][v3];[v1]scale=1920:1080[v1out];[v2]scale=1280:720[v2out];[v3]scale=854:480[v3out]" \
  -map "[v1out]" -c:v:0 libx264 -b:v:0 5M \
  -map "[v2out]" -c:v:1 libx264 -b:v:1 2M \
  -map "[v3out]" -c:v:2 libx264 -b:v:2 1M \
  -map 0:a -c:a aac -b:a 128k \
  -var_stream_map "v:0,a:0 v:1,a:0 v:2,a:0" \
  -master_pl_name master.m3u8 \
  -hls_time 6 \
  -hls_segment_filename "v%v/segment_%03d.ts" \
  v%v/index.m3u8

DASH (Dynamic Adaptive Streaming)

ffmpeg -i input.mp4 \
  -c:v libx264 -c:a aac \
  -f dash \
  -init_seg_name "init-\$RepresentationID\$.m4s" \
  -media_seg_name "chunk-\$RepresentationID\$-\$Number%05d\$.m4s" \
  output.mpd

6. Python Integration

PyAV (FFmpeg bindings)

import av

def transcode_video(input_path, output_path, target_codec='libx264'):
    input_container = av.open(input_path)
    output_container = av.open(output_path, 'w')

    # Get input streams
    video_stream = input_container.streams.video[0]
    audio_stream = input_container.streams.audio[0] if input_container.streams.audio else None

    # Create output streams
    output_video = output_container.add_stream(target_codec, rate=video_stream.average_rate)
    output_video.width = video_stream.width
    output_video.height = video_stream.height
    output_video.pix_fmt = 'yuv420p'

    if audio_stream:
        output_audio = output_container.add_stream('aac', rate=audio_stream.rate)

    for packet in input_container.demux():
        if packet.stream.type == 'video':
            for frame in packet.decode():
                for out_packet in output_video.encode(frame):
                    output_container.mux(out_packet)
        elif packet.stream.type == 'audio' and audio_stream:
            for frame in packet.decode():
                for out_packet in output_audio.encode(frame):
                    output_container.mux(out_packet)

    # Flush encoders
    for packet in output_video.encode():
        output_container.mux(packet)

    output_container.close()
    input_container.close()

MoviePy

from moviepy.editor import VideoFileClip, concatenate_videoclips, TextClip, CompositeVideoClip

def process_video(input_path, output_path):
    # Load video
    clip = VideoFileClip(input_path)

    # Trim
    trimmed = clip.subclip(10, 60)  # 10s to 60s

    # Resize
    resized = trimmed.resize(height=720)

    # Add text overlay
    txt_clip = TextClip("Hello World", fontsize=50, color='white')
    txt_clip = txt_clip.set_position('center').set_duration(5)

    # Composite
    final = CompositeVideoClip([resized, txt_clip])

    # Export
    final.write_videofile(
        output_path,
        codec='libx264',
        audio_codec='aac'
    )

    clip.close()

def create_thumbnail(video_path, output_path, time=5):
    clip = VideoFileClip(video_path)
    frame = clip.get_frame(time)
    clip.save_frame(output_path, t=time)
    clip.close()

def concatenate_videos(video_paths, output_path):
    clips = [VideoFileClip(path) for path in video_paths]
    final = concatenate_videoclips(clips)
    final.write_videofile(output_path)
    for clip in clips:
        clip.close()

FFmpeg Subprocess

import subprocess
import json

def get_video_info(video_path):
    """Get video metadata using ffprobe"""
    cmd = [
        'ffprobe',
        '-v', 'quiet',
        '-print_format', 'json',
        '-show_format',
        '-show_streams',
        video_path
    ]

    result = subprocess.run(cmd, capture_output=True, text=True)
    return json.loads(result.stdout)

def transcode_video(input_path, output_path, options=None):
    """Transcode video with FFmpeg"""
    cmd = ['ffmpeg', '-i', input_path]

    if options:
        if 'video_codec' in options:
            cmd.extend(['-c:v', options['video_codec']])
        if 'audio_codec' in options:
            cmd.extend(['-c:a', options['audio_codec']])
        if 'crf' in options:
            cmd.extend(['-crf', str(options['crf'])])
        if 'resolution' in options:
            cmd.extend(['-vf', f"scale={options['resolution']}"])

    cmd.extend(['-y', output_path])

    result = subprocess.run(cmd, capture_output=True, text=True)

    if result.returncode != 0:
        raise Exception(f"FFmpeg error: {result.stderr}")

    return True

def generate_hls(input_path, output_dir):
    """Generate HLS stream"""
    import os
    os.makedirs(output_dir, exist_ok=True)

    cmd = [
        'ffmpeg', '-i', input_path,
        '-c:v', 'libx264',
        '-c:a', 'aac',
        '-hls_time', '10',
        '-hls_list_size', '0',
        '-hls_segment_filename', f'{output_dir}/segment_%03d.ts',
        f'{output_dir}/index.m3u8'
    ]

    subprocess.run(cmd, check=True)

7. Live Streaming

RTMP Server (nginx-rtmp)

# nginx.conf
rtmp {
    server {
        listen 1935;

        application live {
            live on;
            record off;

            # HLS output
            hls on;
            hls_path /var/www/hls;
            hls_fragment 3;
            hls_playlist_length 60;
        }
    }
}

Stream to RTMP

# Stream file to RTMP
ffmpeg -re -i input.mp4 -c copy -f flv rtmp://server/live/stream

# Stream webcam
ffmpeg -f v4l2 -i /dev/video0 -f alsa -i hw:0 \
  -c:v libx264 -preset veryfast -b:v 2M \
  -c:a aac -b:a 128k \
  -f flv rtmp://server/live/stream

# Stream to YouTube
ffmpeg -i input.mp4 \
  -c:v libx264 -preset medium -b:v 4M \
  -c:a aac -b:a 128k \
  -f flv rtmp://a.rtmp.youtube.com/live2/YOUR_STREAM_KEY

8. Video Processing Pipeline

Async Processing with Celery

from celery import Celery
import os

celery = Celery('video_tasks')

@celery.task
def process_upload(video_id, input_path):
    """Complete video processing pipeline"""
    output_dir = f'/videos/{video_id}'
    os.makedirs(output_dir, exist_ok=True)

    # Generate thumbnail
    generate_thumbnail.delay(video_id, input_path, f'{output_dir}/thumb.jpg')

    # Transcode to multiple resolutions
    resolutions = [
        ('1080p', '1920:1080', '5M'),
        ('720p', '1280:720', '2.5M'),
        ('480p', '854:480', '1M'),
    ]

    for name, scale, bitrate in resolutions:
        transcode_resolution.delay(
            video_id, input_path,
            f'{output_dir}/{name}.mp4',
            scale, bitrate
        )

    # Generate HLS
    generate_hls.delay(video_id, input_path, f'{output_dir}/hls')

@celery.task
def generate_thumbnail(video_id, input_path, output_path):
    cmd = [
        'ffmpeg', '-i', input_path,
        '-ss', '5', '-frames:v', '1',
        '-vf', 'scale=320:-1',
        output_path
    ]
    subprocess.run(cmd, check=True)

@celery.task
def transcode_resolution(video_id, input_path, output_path, scale, bitrate):
    cmd = [
        'ffmpeg', '-i', input_path,
        '-c:v', 'libx264', '-b:v', bitrate,
        '-vf', f'scale={scale}',
        '-c:a', 'aac', '-b:a', '128k',
        output_path
    ]
    subprocess.run(cmd, check=True)

9. Audio Analysis

Waveform Generation

import librosa
import librosa.display
import matplotlib.pyplot as plt
import numpy as np

def generate_waveform(audio_path, output_path):
    """Generate waveform image"""
    y, sr = librosa.load(audio_path)

    plt.figure(figsize=(14, 5))
    librosa.display.waveshow(y, sr=sr)
    plt.title('Waveform')
    plt.savefig(output_path, dpi=150, bbox_inches='tight')
    plt.close()

def generate_spectrogram(audio_path, output_path):
    """Generate spectrogram image"""
    y, sr = librosa.load(audio_path)
    D = librosa.stft(y)
    S_db = librosa.amplitude_to_db(np.abs(D), ref=np.max)

    plt.figure(figsize=(14, 5))
    librosa.display.specshow(S_db, sr=sr, x_axis='time', y_axis='hz')
    plt.colorbar(format='%+2.0f dB')
    plt.title('Spectrogram')
    plt.savefig(output_path, dpi=150, bbox_inches='tight')
    plt.close()

10. Best Practices

Encoding Presets

# Web-optimized MP4
ffmpeg -i input.mp4 \
  -c:v libx264 -preset slow -crf 22 \
  -c:a aac -b:a 128k \
  -movflags +faststart \
  output.mp4

# Archive quality
ffmpeg -i input.mp4 \
  -c:v libx264 -preset veryslow -crf 18 \
  -c:a flac \
  archive.mkv

# Mobile-optimized
ffmpeg -i input.mp4 \
  -c:v libx264 -preset fast -crf 28 \
  -vf "scale='min(720,iw)':-2" \
  -c:a aac -b:a 96k \
  mobile.mp4

Best Practices

  1. Use hardware acceleration - NVENC, VAAPI, VideoToolbox
  2. Optimize for web - faststart flag for streaming
  3. Choose right codec - H.264 for compatibility, VP9/AV1 for quality
  4. Appropriate CRF - 18-23 for quality, 28+ for size
  5. Two-pass for size - When file size matters
  6. Process async - Queue long operations
  7. Generate previews - Thumbnails and sprites
  8. Validate input - Check format before processing
  9. Clean temp files - Remove intermediate files
  10. Monitor resources - CPU/memory limits

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

David-Li0406/meta-skill-evloving

Browser automation with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website", "log into", or any browser interaction request.

David-Li0406/meta-skill-evloving

Create technical diagrams using Mermaid syntax for architecture, sequences, ERDs, flowcharts, and state machines. Use for visualizing system design, data flows, and processes. Triggers: diagram, mermaid, architecture diagram, sequence diagram, flowchart, ERD, entity relationship, state diagram, C4 model, component diagram, visualize, draw.

David-Li0406/meta-skill-evloving

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

David-Li0406/meta-skill-evloving

Complete color manipulation and green screen effects system. PROACTIVELY activate for: (1) Green screen/chromakey removal, (2) Color grading with LUTs, (3) Color correction (levels, curves, white balance), (4) Colorkey/color removal effects, (5) Hue/saturation manipulation, (6) Color space conversions (BT.709, BT.2020, HDR), (7) Color isolation effects, (8) Teal and orange look, (9) Vintage/film looks, (10) Color keying for transparency. Provides: chromakey and colorkey filters, LUT application (lut3d), curves and levels adjustment, color balance, selective color manipulation, color space handling, HDR tone mapping, professional color grading chains.

David-Li0406/meta-skill-evloving

Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.

David-Li0406/meta-skill-evloving

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

David-Li0406/meta-skill-evloving

Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.

David-Li0406/meta-skill-evloving

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

David-Li0406/meta-skill-evloving

Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks

David-Li0406/meta-skill-evloving

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

David-Li0406/meta-skill-evloving

Best practices for Remotion - Video creation in React

David-Li0406/meta-skill-evloving

指导如何通过自定义注解(如@Unicom)标识Dubbo接口,利用BeanDefinitionRegistryPostProcessor在启动时扫描并动态注册ReferenceBean,实现RPC调用的封装。

David-Li0406/meta-skill-evloving

生成Python脚本,利用FFmpeg将图片序列按3x3布局合并,或将合并图拆分。要求使用subprocess模块执行命令,并支持用户交互式输入路径。

David-Li0406/meta-skill-evloving

Generates KWL (Know, Want to know, Learned) charts for educational videos, specifically BrainPOP, using simple 7th-grade language and short, concise bullet points.

David-Li0406/meta-skill-evloving

Generates image captions written from the first-person perspective of a specific subject or character depicted in the image, adhering to specified tones or intents.

David-Li0406/meta-skill-evloving

Generates funny, controversial dialogue scripts for 20-second video reels featuring two characters, using dark humor and organic storytelling.

David-Li0406/meta-skill-evloving

Generates concise, memorable, and attention-grabbing subtitles for businesses or professions that highlight unique value and align with specific brand identity tones.

David-Li0406/meta-skill-evloving

Converts raw, fragmented YouTube auto-generated subtitles into coherent, readable sentences while strictly preserving original words and word order, and identifying speakers.

David-Li0406/meta-skill-evloving

Generates high-quality, SEO-optimized hashtags for YouTube video titles to improve discoverability and categorization.

David-Li0406/meta-skill-evloving

Tracks complex, multi-session work using the Beads issue tracker and dependency graphs, and provides persistent memory that survives conversation compaction. Use when work spans multiple sessions, has complex dependencies, or needs persistent context across compaction cycles. Trigger with phrases like "create task for", "what's ready to work on", "show task", "track this work", "what's blocking", or "update status".

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