Eugene-Fed

Оглавление

• Начальный уровень
• Продвинутый уровень
• Экспертный уровень
• Найти ошибку в коде -- начальный
• Найти ошибку в коде -- продвинутый
• Найти ошибку в коде -- экспертный

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Начальный уровень

devinschumacher

source_url	https://github.com/serpapps/canva-downloader/blob/main/README.md

Canva Downloader

Export Canva designs without watermarks in high resolution with all elements intact

pazteddy

Laravel: AI, REST, JWT, Repository Pattern

Para empezar el curso, les dejo una lista de las instalaciones generales que les recomiendo.

Herramientas base

kamronbatman

# CW RMM Uninstaller Script
# This script forcefully removes the ConnectWise RMM agent and its components.
# Run with administrative privileges.

$TranscriptPath = "$env:SystemDrive\CWRMM-Removal\CWRMM-Uninstall-$(Get-Date -Format yyyyMMdd-HHmmss).log"
New-Item -Path $TranscriptPath -ItemType Directory -Force | Out-Null
Start-Transcript -Path $TranscriptPath -Append | Out-Null

Write-Output ""
Write-Output "Beginning CW RMM Uninstall"

mattezell

Antigravity / Antigravity IDE — Linux tarball installer

Antigravity 2.0 and the Antigravity IDE currently ship for Linux as raw .tar.gz archives — no .deb, no .AppImage, no Flatpak, no installer. This gist is a small set of shell scripts that turn one of those extracted tarballs into a proper user-local install: a desktop launcher in your app menu, a CLI symlink on your $PATH, an icon, and (on Ubuntu 24.04+) a working Chromium sandbox via an AppArmor profile.

Status: community workaround. Replace with whatever Google ships

karpathy

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

mnabila

In some cases, only these lines will work

for product in IntelliJIdea WebStorm DataGrip PhpStorm CLion PyCharm GoLand RubyMine; do
    rm -rf ~/.config/$product*/eval 2> /dev/null
    rm -rf ~/.config/JetBrains/$product*/eval 2> /dev/null
done

But if not, try these

rvrsh3ll

NOTE

These are NOT product / license keys that are valid for Windows activation.
These keys only select the edition of Windows to install during setup, but they do not activate or license the installation.

Index

• Windows 11
• RTM Generic Keys

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

mamamoz

video-eyes — научи Claude смотреть видео

Скилл для Claude Code / Claude Cowork: разбор видео (YouTube, Reels, TikTok, Shorts) кадр за кадром с синхронизацией картинки и речи. Заточен под русскоязычный контент.

Что умеет:

• скачивает видео по ссылке
• расшифровывает речь с таймкодами (русский — из коробки)
• для YouTube берёт готовые субтитры — быстрее и точнее