skorasaurus

[
   {
        "where": "Layer",
        "if": {
            "Datasource.type": "postgis"
        },
        "then": {
            "Datasource.dbname": "hdmht",
            "Datasource.user": "skors",
            "Datasource.host": "localhost"

tamanishi

List of Chrome URLs

chrome://accessibility
chrome://appcache-internals
chrome://apps
chrome://blob-internals
chrome://bookmarks
chrome://cache
chrome://chrome
chrome://chrome-urls

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.

aarondfrancis

Audit this entire codebase for materially useful simplifications in its data structures, state representation, control flow, algorithms, and ownership.

This is an audit-only exercise. Do not edit files, run tests, implement recommendations, commit, or push. Read-only inspection commands are allowed.

You are the coordinator. Continue until the complete codebase has been reviewed and the final audit is validated.

1. Establish the coverage contract

Inspect the repository and inventory every identifiable subsystem.

penteract

Rules
Dimensions are indexed by natural numbers. The first dimension (indexed by 0) is “forwards”. Axes go from 1 to 8 in every dimension

Pieces start in the same places as in 2D chess, the white queen starts on (1,4), the white king on (1,5), the black queen on (8,4). coordinates in all dimensions not explicitly listed are 1.

Q moves n spaces in any finite set of dims
K moves 1 space in any finite set of dims
B moves n spaces in 2 dims
N moves 2 spaces in any dim and 1 space in any other dim
R moves any num spaces in 1 dim

mfpiccolo

53 things from ~4 months of running an agent harness in production.

iii, the engine that powers the harness, is really cool too: https://iii.dev/docs/install

• crash mid tool call left a dangling call with no result that poisoned every later request workers#507 workers#630
• resumed turn raced the worker booting and called a function that wasn't registered yet workers#507
• no durable queue for turns so wedged ones sat in running forever workers#464
• cut stream parsed as null args and got reported as a successful empty turn workers#878
• seven providers treating any connection close as done workers#878
• cached tokens double billed on six providers workers#740

drillan

Jev (TypeSafe System One) — Finance & Trading Projects

Projects using Jev, TypeSafe AI's System One decision model (released 2026-09-15), in investment, trading, and financial-data contexts. Surveyed 2026-09-20 via GitHub API and community awesome-lists.

Reference project

• jarrodwatts/jev-trader (★1.3k, 2026-09-16) — One AI trade decision every Monad block (~300 ms). Jev reads the Kuru MON-USDC order book and answers buy or sell; the bot posts a post-only limit order one tick inside the touch, earning the spread. Bun/TypeScript, dry-run mode, SSE dashboard. The template most projects below derive from.

Live trading / trading systems

gjgjgjjj123

🛠️📱 QST Pro Tool V4 – Mobile Servicing & Repair Solution

🌟 Introduction

QST Pro Tool V4 is presented as a mobile servicing utility aimed at technicians who work with supported Android smartphones. Such tools are generally used for device diagnostics, software maintenance, firmware-related operations, and authorized repair workflows.

The exact functions available can vary according to the tool release, device model, chipset, Android version, and security configuration.

⚠️ Important: Use mobile servicing tools only on devices you own or are authorized to repair. Do not use them to bypass ownership protections, access another person's account, or defeat device security without permission.

0xfauzi

AGENTS.md Best Practices for AI Coding Assistants: Comprehensive Guide

AGENTS.md has emerged as the de facto open standard for guiding AI coding assistants, now adopted by over 20,000 repositories and formalized in August 2025 through collaboration between OpenAI, Google, Cursor, Factory, and Sourcegraph. This file acts as a "README for machines"—providing structured, technical context that helps AI assistants write better code from the start. For Python + AWS + Terraform projects, a well-crafted AGENTS.md dramatically reduces friction, ensuring generated code follows your conventions, uses the right tools, and adheres to security requirements.

What is AGENTS.md and why it matters

AGENTS.md is a dedicated Markdown file that complements, not replaces, README.md. While README targets human developers with project overviews and quick-start guides, AGENTS.md contains detailed technical instructions specifically for AI coding agents. Think of it as onboarding documentation for an AI team member: ex

KGHague

function ConvertTo-PackedGuid {
    <#
	.SYNOPSIS
		https://gist.github.com/MyITGuy/d3e039c5ec7865edefc157fcd625a20a
        Converts a GUID string into a packed globally unique identifier (GUID) string.
	.DESCRIPTION
		Takes a GUID string and breaks it into 6 parts. It then loops through the first five parts and reversing the order. It loops through the sixth part and reversing the order of every 2 characters. It then joins the parts back together and returns a packed GUID string.
	.EXAMPLE
		ConvertTo-PackedGuid -Guid '{7C6F0282-3DCD-4A80-95AC-BB298E821C44}'