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@mpppk
mpppk / clean_architecture.md
Last active August 25, 2026 04:53
クリーンアーキテクチャ完全に理解した

2020/5/31追記: 自分用のメモに書いていたつもりだったのですが、たくさんのスターを頂けてとても嬉しいです。
と同時に、書きかけで中途半端な状態のドキュメントをご覧いただくことになっており、大変心苦しく思っています。

このドキュメントを完成させるために、今後以下のような更新を予定しています。

  • TODO部分を埋める
  • 書籍を基にした理論・原則パートと、実装例パートを分割
    • 現在は4層のレイヤそれぞれごとに原則の確認→実装時の課題リスト→実装例という構成ですが、同じリポジトリへの言及箇所がバラバラになってしまう問題がありました。更新後は、実装時の課題リストを全て洗い出した後にまとめて実装を確認する構成とする予定です。

2021/1/22追記:

@Naxdy
Naxdy / sysprompt.md
Last active August 25, 2026 04:51
Minimax H3 Prompt Enhancer

Role

You are a prompt-enrichment engine that sits between a user's raw creative request and MiniMax H3, a generative model that synthesizes video AND synchronized stereo audio together. Your role mirrors MiniMax's official "H3-Context-IR": deeply understand and refine the multimodal input, reason about how the pieces relate to each other and to the intended output, and serialize your understanding into a structured "production brief" that H3-Base can consume directly. You perform instruction parsing, cross-modal association, temporal understanding, and complex logical reasoning over the material you are given. Without deviating from the user's original intent, you may supplement missing or underspecified semantic details where appropriate. You convert everything into a single, maximally detailed and unambiguous brief, formatted exactly as specified below. You DO NOT generate media yourself. You ONLY OUTPUT THE BRIEF TEXT, nothing else — no preamble, no explanation, no markdown fences, no JSON wrapper.

Wh

  • Shall i implement it?
  • No ...
@tdcosta100
tdcosta100 / WSL2GUIWSLg-XWayland-en.md
Last active August 25, 2026 04:46
A tutorial to use GUI in WSL2/WSLg replacing original Xorg by Xwayland, allowing WSL to work like native Linux, including login screen

Full desktop shell in WSL2 using WSLg (XWayland)

Note

If you want to use Wayland in WSLg in a simpler setup, you can try the WSLg (Wayland) tutorial.

In this tutorial, we will setup GUI in WSL2. No additional software outside WSL (like VcXsrv or GWSL) is required. You will find this tutorial very similar to the one that replaces Xorg with Xvnc. Indeed, it's pretty much the same tutorial, with some few changes.

The key component we need to install is the desktop metapackage you want (GNOME, KDE, Xfce, Budgie, etc), and after that, replace the default Xorg by a script that calls Xwayland instead.

For this setup, I will use Ubuntu 24.04, and install GNOME Desktop. Unfortunately older versions of Ubuntu lack some fundamental things, so we cannot reproduce it in older versions (at least not fully). Since the key components aren't bound to Ubuntu or GNOME, you can use your favorite distro and GUI. Check the [Sample screenshot

@Brajesh2022
Brajesh2022 / Running Antigravity CLI on Termux.md
Last active August 25, 2026 04:41
Antigravity CLI on Termux: Auto-Installer and Manual Patching Guide

🚀 Recommended Installation (Auto-Installer)

Antigravity CLI Demo The easiest and community-recommended way to install Antigravity CLI on Termux is using the standalone auto-installer.

curl -fsSL https://raw.githubusercontent.com/wallentx/antigravity-cli-termux/dev/install.sh | bash

How it works: This script instantly installs the latest release directly from the wallentx/antigravity-cli-termux repository. A huge thanks to the original repository owner, @wallentx, for packaging these releases! The repository automatically runs a GitHub Action every six hours that fetches the official binary and patches it using the exact methods outlined in this guide below.

@dagimg-dot
dagimg-dot / spotify-in-brave-arm64-guide.md
Last active August 25, 2026 04:41
Spotify Web Player in Brave on ARM64: PWA install + icon fix + ad silencing

Spotify (and other DRM sites) in Brave on ARM64 Linux

Why this exists: Brave ships with Widevine DRM disabled by default, and on ARM64 Linux (Asahi, Raspberry Pi, etc.) Brave does not auto-download the Widevine CDM. You get "Playback of protected content is not enabled" on Spotify, Netflix, and similar sites until you install the CDM manually and switch Widevine on.

Everything below was verified on Asahi Linux (Arch Linux ARM, aarch64), Brave 151. The same steps apply to any ARM64 Linux distro.

@bdsqqq
bdsqqq / 2026-01-06 ensure your work is a meaningful contribution
Created August 24, 2026 23:45
2026-01-06 ensure your work is a meaningful contribution
# meaningful contribution
Based on embarassing feedback on a bad PR for AXM-10598, and written from my beliefs; with only a little bit of copy pasting, because to be human is to copy from a shitload of places until it becomes your own.
## A contribution is not code, it's proven working code
> "your job is to deliver code you have proven to work." — [simon willison](https://simonwillison.net/2025/Dec/18/code-proven-to-work/)
agent-generated code is cheap. anyone can prompt an LLM to produce a thousand-line patch. that's not valuable. what's valuable is contributing code that demonstrably works, has been tested, and doesn't shift burden to reviewers.
@k16shikano
k16shikano / SKILL.md
Last active August 25, 2026 04:40
cognitive-rhythm-writing/SKILL.md
name cognitive-rhythm-writing
description 説明的な文章に緩急を設計するための規範。緩急を装飾ではなく認知モードの切替(観察→逡巡→断定→再観察)と未回収の緊張の管理として扱い、文の拍、段落の密度波形、節の入り方、緩みと駄文の判別、執筆後の機械的な点検手順を定める。読み物として読ませたい章・記事・解説文を生成するとき、または「密度はあるが平坦でおもしろくない」文章を診断・修正するときに使用する。

認知リズムを生むための日本語ライティング規範

密度の高い文章が退屈になるのは、情報が多いからではなく、全文が同じ認知モードで書かれているからである。 この規範は、読者の認知モード(観察する、迷う、確信する、確かめ直す)を意図的に切り替え、常に「続きを読む理由」を維持することで、読み進める推進力を作る。

@k16shikano
k16shikano / SKILL.md
Last active August 25, 2026 04:40
japanese-tech-writing/SKILL
name japanese-tech-writing
description 日本語の技術文書・書籍原稿の文章規範。整形(一文一行、引用ブロック、脚注、コラム記法)、段落と論証の構成(パラグラフライティング)、論証の厳密さ(ツッコミどころの除去)、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

日本語技術文書の文章規範

日本語で技術的な原稿(書籍の章、記事、解説文)を書く・推敲するときは、以下の規範に従う。

整形

@ry
ry / llm-wiki.md
Last active August 25, 2026 04:39 — forked from karpathy/llm-wiki.md
llm-wiki

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.