Yossi Elkrief MaTriXy

OpenClaw Prompts - Build Your Own AI Assistant

Prompts to recreate each piece of the OpenClaw system. Use these with any AI coding assistant.

1. Personal CRM "Build a personal CRM that automatically scans my Gmail and Google Calendar to discover contacts from the past year. Store them in a SQLite database with vector embeddings so I can query in natural language ('who do I know at NVIDIA?' or 'who haven't I talked to in a while?'). Auto-filter noise senders like marketing emails and newsletters. Build profiles for each contact with their company, role, how I know them, and our interaction history. Add relationship health scores that flag stale relationships, follow-up reminders I can create, snooze, or mark done, and duplicate contact detection with merge suggestions. Link relevant documents from Box to contacts so when I look up a person, I also see related docs."

2. Meeting Action Items (Fathom)

Claude Code TeammateTool - Source Code Analysis

This is not a proposal. This documents existing but hidden functionality found in Claude Code v2.1.19 binary, plus speculation on how it could be used.

Executive Summary

TeammateTool already exists in Claude Code. We extracted this from the compiled binary at ~/.local/share/claude/versions/2.1.19 using strings analysis. The feature is fully implemented but gated behind feature flags (I9() && qFB()).

	#include <metal_stdlib>
	#include <SwiftUI/SwiftUI.h>
	using namespace metal;

	[[ stitchable ]] half4 simpledistort(float2 pos, SwiftUI::Layer l, float4 boundingRect, float progress, float distortion) {

	float2 size = boundingRect.zw;
	float2 uv = pos / size;
	float2 center = float2(0.5, 0.5);
	float2 delta = uv - center;

	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp

	# OpenClaw Implementation Prompts

	Each prompt below is a self-contained brief you can hand to an AI coding assistant (or use as a project spec) to build that use case from scratch. Adapt the specific services to whatever you already use — the patterns are what matter.

	---

	## 1) Personal CRM Intelligence

	```
	Build me a personal CRM system that automatically tracks everyone I interact with, with smart filtering so it only adds real people — not newsletters, bots, or cold outreach.

	#!/usr/bin/env bash
	set -euo pipefail

	source_dirs=(
	"/Users/cameroncooke/Developer/dimillian-skills"
	"/Users/cameroncooke/Developer/sentry_skills"
	"/Users/cameroncooke/Developer/cameroncooke-skills"
	"/Users/cameroncooke/Developer/openai-skills/skills/.curated"
	)

	#!/bin/bash

	# Check if a GitHub URL is provided as an argument
	if [ -z "$1" ]; then
	echo "Usage: $0 <github_url>"
	exit 1
	fi

	# Store the GitHub URL
	GIT_URL="$1"

	// Lines
	float hash( float n ) {
	return fract(sin(n)*753.5453123);
	}

	// Slight modification of iq's noise function.
	float noise(vector_float2 x )
	{
	vector_float2 p = floor(x);
	vector_float2 f = fract(x);

	import androidx.compose.foundation.layout.Box
	import androidx.compose.runtime.Composable
	import androidx.compose.ui.Modifier
	import androidx.compose.ui.draw.drawWithContent
	import androidx.compose.ui.geometry.Offset
	import androidx.compose.ui.graphics.BlendMode
	import androidx.compose.ui.graphics.Color
	import androidx.compose.ui.graphics.nativeCanvas

	@Composable

	private val PARTICLE_COLOR = Color.White
	private val LINE_COLOR = Color.White
	private const val PARTICLE_QUANTITY = 100
	private const val DEFAULT_SPEED = 2
	private const val VARIANT_SPEED = 1
	private const val DEFAULT_RADIUS = 4
	private const val VARIANT_RADIUS = 2
	private const val LINK_RADIUS = 200
	// TODO: 30/09/2020 These should be measured but are only used to calculate
	// the initial position