Caution
As of August 26th 2026, Discord has started suspending quest access of people caught automating quest completion.
Some users have received the following system message:
There isn't much I can do to make the script undetected, so use it at your own risk, as you WILL get flagged by doing so.
A Claude Code Agent Skill built from Dex Horthy's (HumanLayer) playbook on David Ondrej's podcast.
"Once the model has written thousands of lines of code, it is harder to change. The sessions that generate design docs are context-light — you get the most model intelligence when you do the hard thinking early."
By default, agents build horizontally: all the backend, then all the frontend, then a 2,000-line diff lands in your lap and reviewing it is your problem. This skill flips that. Every decision that matters gets made before the code exists — where changing your mind costs a sentence, not a rewrite.
for 4.2.4 or higher, 4.2.5,4.2.6,4.3.7, it's works, this is the way which makes Always in evaluation mode.
Terminal, go to the dir : cd /Applications/Beyond Compare.app/Contents/MacOSBCompare to BCompare.bak: mv BCompare BCompare.bakBCompare , and chmod a+ux BCompare : touch BCompare && chmod a+ux BCompareBCompare with text editor, insert the script :#!/bin/bash
rm "/Users/$(whoami)/Library/Application Support/Beyond Compare/registry.dat"
"`dirname "$0"`"/BCompare.bak $@
| . | |
| .. | |
| ........ | |
| @ | |
| * | |
| *.* | |
| *.*.* | |
| 🎠|
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.
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.
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.
| The MIT License (MIT) | |
| Copyright (c) 2015 J Kishore Kumar | |
| Permission is hereby granted, free of charge, to any person obtaining a copy | |
| of this software and associated documentation files (the "Software"), to deal | |
| in the Software without restriction, including without limitation the rights | |
| to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| copies of the Software, and to permit persons to whom the Software is | |
| furnished to do so, subject to the following conditions: |
