| // ==UserScript== | |
| // @name Desmos godmode with lists | |
| // @namespace github.com/jared-hughes | |
| // @match *://www.desmos.com/calculator* | |
| // @description Increase the limits on list length and "nested too deeply" error | |
| // @grant none | |
| // @version 1.4 | |
| // @run-at document-start | |
| // @author jared-hughes | |
| // ==/UserScript== |
This guide covers the minimum and recommended hardware specifications for hosting OpenClaw across different deployment scenarios. OpenClaw is designed to be lightweight—the Gateway itself is a Node.js process that proxies messages to cloud-hosted LLMs—but resource needs scale with enabled features, concurrent sessions, and sandboxing configuration.
| Scenario | CPU | RAM | Storage | Network |
|---|---|---|---|---|
| Minimal (headless gateway) | 1 vCPU | 512MB | 1GB | 1 Mbps |
| Standard (gateway + channels) | 1-2 vCPU | 1-2GB | 5GB | 5 Mbps |
| #!/usr/bin/env bash | |
| set -euo pipefail | |
| DOMAIN="${1:-example.com}" | |
| RELEASE="${CC_RELEASE:-cc-main-2026-jan-feb-mar}" | |
| CACHE="${HOME}/.cache/cc-backlinks/${RELEASE}" | |
| BASE="https://data.commoncrawl.org/projects/hyperlinkgraph/${RELEASE}/domain" | |
| VERTICES="${CACHE}/domain-vertices.txt.gz" | |
| EDGES="${CACHE}/domain-edges.txt.gz" |
| Right about now, Free Software court is in full effect | |
| Judge Whax presiding | |
| In the case of Free Software vs. the GNOME Foundation; | |
| prosecuting attorneys are: Satoshi, YYY, and ZZ-motherfucking-Z | |
| Order, order, order | |
| Satoshi, take the motherfucking stand | |
| Do you swear to tell the truth, the whole truth | |
| and nothing but the truth so help your nerd ass? |
Si alguna vez abren la consola de python y escriben import this verán que les aparecerán las líneas con el famoso Zen de Python:
| # Script to generate a new block every minute | |
| # Put this script at the root of your unpacked folder | |
| #!/bin/bash | |
| echo "Generating a block every minute. Press [CTRL+C] to stop.." | |
| address=`./bin/bitcoin-cli getnewaddress` | |
| while : | |
| do |
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.