qoomon

Conventional Commit Messages

See how a minor change to your commit message style can make a difference.

git commit -m"<type>(<optional scope>): <description>" \
  -m"<optional body>" \
  -m"<optional footer>"

conradcaffier03

👁️ Give Claude Eyes — watch any video frame-by-frame

Freebie for the EYES keyword (reel-47, "Give Claude eyes"). Deliver as a public GitHub Gist — numbered steps the user can run today, not a raw link. Value-first: by the end you have a Claude Code skill that sees a video (every cut, every on-screen detail), not just reads its transcript.

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Why this exists

Claude has no native video model. So every "analyze this video" tool just pulls the transcript — and

Pythonation

1. برومبت التخطيط المطوّر (The Planning Protocol)

[الدور والمسؤولية] أنت الآن تعمل بصفة Staff Software Engineer ومدير تقني Tech Lead. مهمتك التخطيط المعماري الصارم للمشروع التالي: [أدخل وصف المشروع هنا]

[قواعد ما قبل التتخطيط] قبل البدء بالبروتوكولات، يجب أن تطبق مبدأ "Think Before Coding":

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.

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)

VapidLinus

using UnityEngine.UI;

[RequireComponent(typeof(RectTransform), typeof(LayoutElement))]
[ExecuteInEditMode]
public class LayoutElementFitParent : MonoBehaviour
{
	[SerializeField] private float aspectRatio = 1;

	[SerializeField] private bool updateMin = false;
	[SerializeField] private bool updatePreferred = false;

lexi-lambda

Monads and delimited control are very closely related, so it isn’t too hard to understand them in terms of one another. From a monadic point of view, the big idea is that if you have the computation m >>= f, then f is m’s continuation. It’s the function that is called with m’s result to continue execution after m returns.

If you have a long chain of binds, the continuation is just the composition of all of them. So, for example, if you have

m >>= f >>= g >>= h

then the continuation of m is f >=> g >=> h. Likewise, the continuation of m >>= f is g >=> h.

pei0804

pei0804

Hello World.

GitHub

pei0804

Blog

• Hatena
• Zenn

sebastienblanc

Deploying Hermes Agent on a Raspberry Pi 5 (16 GB)

A complete guide: from a blank SD card to a self-improving agent running 24/7 on your home network, reachable via SSH and (optionally) Telegram/Discord/WhatsApp.

Why this works well: Hermes Agent officially supports Linux aarch64 as a Tier 1 platform via the install.sh installer. The LLM inference runs on a remote provider (Nous Portal, OpenRouter, Anthropic, etc.), so the Pi only handles orchestration, tools, memory, and the messaging gateway — 16 GB of RAM is generous headroom for this.

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0. What you need

Inspector-a11

FULL REVERSE ENGINEERING: awstore.cloud Malware

Caution

Это профессиональный многостадийный MitM-троян, таргетированный на СНГ. Значительно опаснее обычного стилера.

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Attack Overview

Элементарное "Спасибо" ниже в комментариях, будет греть душу))

graph TD