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Working like a madman on Level Up & Muxxi

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Working like a madman on Level Up & Muxxi
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simple10 / securing-openclaw-guide.md
Created February 9, 2026 03:27 — forked from thedudeabidesai/securing-openclaw-guide.md
Securing Your OpenClaw Deployment — A practical security guide through Child & First Principles lenses 🎳

Deploying & Securing OpenClaw on Hetzner

A Complete Production Guide — Secure From Step One

Guide version: 2.0 — February 7, 2026 Last reviewed: 2026-02-07 | Lines: ~1125 | Grade: Multi-model audited (Opus 4.6, Codex 5.3, Grok 3)

Based on Brad Barbin's original Hetzner deployment gist. Security hardening from a real production audit by The Dude 🎳.

Platform: Written for Hetzner VPS (Ubuntu 24.04/22.04 or Debian 12), but the security principles and Docker-based deployment apply to any Linux host. macOS-specific notes are called out where relevant.

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simple10 / 1-research.md
Created February 7, 2026 07:12 — forked from ruvnet/1-research.md
AI Manipulation Defense System

AI Manipulation Defense System: Comprehensive Development Plan

The AI Manipulation Defense System (AIMDS) is a production-ready framework built to safeguard AI models, APIs, and agentic infrastructures from adversarial manipulation, prompt injection, data leakage, and jailbreaking attempts. It’s designed for organizations deploying autonomous agents, LLM APIs, or hybrid reasoning systems that demand both speed and security.

Application

AIMDS integrates directly into AI pipelines—before or after model inference—to detect and neutralize malicious inputs. It’s ideal for:

  • Enterprise AI gateways securing LLM APIs.
  • Government and defense AI deployments requiring verified integrity.
  • Developers embedding guardrails within autonomous agents and chatbots.
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simple10 / contemplative-llms.txt
Created January 11, 2025 23:56 — forked from Maharshi-Pandya/contemplative-llms.txt
"Contemplative reasoning" response style for LLMs like Claude and GPT-4o
You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis.
## Core Principles
1. EXPLORATION OVER CONCLUSION
- Never rush to conclusions
- Keep exploring until a solution emerges naturally from the evidence
- If uncertain, continue reasoning indefinitely
- Question every assumption and inference
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>Single-Column Responsive Email Template</title>
<style>
@media only screen and (min-device-width: 541px) {
.content {
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simple10 / app.coffee
Last active December 14, 2015 00:59 — forked from harlantwood/circle-packing.coffee
Github D3 Visualizer
root = exports ? this
class root.App
constructor: (repo) ->
@github = new App.Github
@d3 = new App.D3
@github.loadRepo(repo, (data) =>
data = @github.parseForD3(data)
@d3.renderCirclePack(data)