tkrotoff

/* eslint-disable unicorn/no-null */

/*
 * Resetting window.location between tests is unfortunately a hard topic with JSDOM.
 *
 * https://gist.github.com/tkrotoff/52f4a29e919445d6e97f9a9e44ada449
 *
 * FIXME JSDOM leaves the history in place after every test, so the history will be dirty.
 * Also its implementations for window.location and window.history are lacking.
 * - https://github.com/jsdom/jsdom/blob/22.1.0/lib/jsdom/living/window/Location-impl.js

bkw777

Xperia 1 VI - XQ-EC72 HK
firmware update notes

This is for a HongKong device in the USA.
https://xdaforums.com/t/tool-xperifirm-xperia-firmware-downloader-v5-8-1.2834142/
https://xdaforums.com/t/tool-newflasher-xperia-command-line-flasher.3619426/
https://xdaforums.com/t/tool-unsin-sin-v3-v4-v5-unpacker-v2-0.3128106/
-------------------------------------------

xperia boot modes:

sundowndev

Google dork cheatsheet

Search filters

Filter	Description	Example
allintext	Searches for occurrences of all the keywords given.	allintext:"keyword"
intext	Searches for the occurrences of keywords all at once or one at a time.	intext:"keyword"
inurl	Searches for a URL matching one of the keywords.	inurl:"keyword"
allinurl	Searches for a URL matching all the keywords in the query.	allinurl:"keyword"
intitle	Searches for occurrences of keywords in title all or one.	intitle:"keyword"

spilist

다음 레퍼런스를 바탕으로, 내 코딩 에이전트 설정을 토큰 효율 관점에서 점검해줘.

• https://code.claude.com/docs/en/settings.md
• https://code.claude.com/docs/en/env-vars.md
• https://developers.openai.com/codex/config-reference.md
• https://github.com/cnighswonger/claude-code-cache-fix

목표는 성능 저하를 크게 만들지 않으면서 토큰 낭비를 줄이는 거야.

• 직접 절약(자동 주입 문맥, 긴 툴 출력 제한 등)과 간접 절약(검색/IDE/앱 경로 차단 등)을 구분해서 봐줘
• 현재 버전 공식 문서나 현재 설치본에서 확인되지 않은 키는 절대 추천하지 마

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.

tsposato

#!/bin/bash

###############################################
# CONFIGURATION
###############################################

PORTAINER_URL="https://portainer-host:40005"
PORTAINER_COMPOSE_DIR="/mnt/data/containers/portainer/compose"
DOCKHAND_STACK_DIR="/mnt/data/containers/dockhand/stacks/Env"

bradtraversy

Common Terminal Commands

Key Commands & Navigation

Before we look at some common commands, I just want to note a few keyboard commands that are very helpful:

• Up Arrow: Will show your last command
• Down Arrow: Will show your next command
• Tab: Will auto-complete your command
• Ctrl + L: Will clear the screen

tronikos

blueprint:
  name: Energy Disaggregation
  description: Approximate power usage of an appliance
  domain: automation
  input:
    power_helper:
      name: Input helper to store the approximate power usage
      description: in W
      selector:
        entity: