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Découvrez les skills Blockchain, comparez leurs dépôts et consultez leurs instructions.

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GitHub

ffmpeg-karaoke-animated-text

JosiahSiegel

Complete karaoke subtitle system and advanced animated text effects. PROACTIVELY activate for: (1) Karaoke-style highlighted lyrics, (2) ASS/SSA advanced subtitle styling, (3) Scrolling credits (horizontal/vert...

GitHub

python-testing

JosiahSiegel

Complete Python testing system. PROACTIVELY activate for: (1) pytest fundamentals, (2) Fixtures and scopes, (3) Parameterized tests, (4) Mocking with pytest-mock, (5) Async testing with pytest-asyncio, (6) Cove...

GitHub

viral-video-platform-specs

JosiahSiegel

Complete platform upload specifications for viral video creation across TikTok, YouTube Shorts, Instagram Reels, Facebook Reels, Snapchat Spotlight, and Twitter/X. PROACTIVELY activate for: (1) Platform-specifi...

GitHub

ffmpeg-color-grading-chromakey

JosiahSiegel

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)...

GitHub

viral-video-long-form

JosiahSiegel

Complete YouTube long-form video optimization for maximum watch time, SEO, and viral potential. PROACTIVELY activate for: (1) YouTube video strategy, (2) Long-form content planning, (3) Watch time optimization,...

GitHub

nextjs-modal-integration

JosiahSiegel

Modal.com integration patterns for Next.js applications. PROACTIVELY activate for: (1) Next.js + Modal backend setup, (2) AI inference from Next.js (LLMs, image generation), (3) Video/audio processing backends,...

GitHub

compose-patterns-2025

JosiahSiegel

Docker Compose production patterns 2025 including multi-environment strategies, health checks, and modern compose features

GitHub

ffmpeg-audio-processing

JosiahSiegel

Complete audio encoding and normalization system. PROACTIVELY activate for: (1) Audio codec selection (AAC, MP3, Opus, FLAC), (2) Loudness normalization (EBU R128, loudnorm), (3) Audio extraction from video, (4...

GitHub

git-security-2025

JosiahSiegel

Git security best practices for 2025 including signed commits, zero-trust workflows, secret scanning, and verification

GitHub

fal-serverless-guide

JosiahSiegel

Complete fal.ai serverless deployment system. PROACTIVELY activate for: (1) Creating fal.App class, (2) GPU machine selection (T4/A10G/A100/H100), (3) setup() for model loading, (4) @fal.endpoint decorators, (5...

GitHub

ffmpeg-deinterlacing-telecine

JosiahSiegel

Complete FFmpeg deinterlacing, field processing, and telecine removal for broadcast and professional video. PROACTIVELY activate for: (1) Deinterlacing interlaced video (yadif, bwdif, w3fdif), (2) Hardware-acce...

GitHub

query-optimization

JosiahSiegel

T-SQL query optimization techniques for SQL Server and Azure SQL Database. Use this skill when: (1) User needs to optimize slow queries, (2) User asks about SARGability or index seeks, (3) User needs help with...

GitHub

adf-master

JosiahSiegel

Comprehensive Azure Data Factory knowledge base with official documentation sources, CI/CD methods, deployment patterns, and troubleshooting resources

GitHub

python-cloudflare

JosiahSiegel

Complete Python Cloudflare deployment system. PROACTIVELY activate for: (1) Python Workers with Pyodide, (2) FastAPI on Workers, (3) Cloudflare Containers for heavy compute, (4) Service bindings (RPC), (5) Envi...

GitHub

fal-video-to-video

JosiahSiegel

Complete fal.ai video-to-video system. PROACTIVELY activate for: (1) Kling O1 video editing, (2) Sora Remix transformation, (3) Video upscaling, (4) Frame interpolation, (5) Style transfer (anime, painting), (6...

GitHub

ffmpeg-noise-reduction

JosiahSiegel

Complete FFmpeg noise reduction and denoising for video and audio. PROACTIVELY activate for: (1) Video denoising (nlmeans, hqdn3d, vaguedenoiser), (2) Hardware-accelerated denoising (nlmeans_opencl, nlmeans_vul...

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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