| # 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. |
Terminals should generate the 256-color palette from the user's base16 theme.
If you've spent much time in the terminal, you've probably set a custom base16 theme. They work well. You define a handful of colors in one place and all your programs use them.
The drawback is that 16 colors is limiting. Complex and color-heavy programs struggle with such a small palette.
| """ | |
| 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 |
| @ECHO OFF | |
| SETLOCAL | |
| FOR /F "tokens=4-5 delims=. " %%i IN ('ver') DO SET VERSION=%%i.%%j | |
| IF "%VERSION%" == "10.0" GOTO :NOUPDATE | |
| IF "%VERSION%" == "6.3" GOTO :NOUPDATE | |
| IF "%VERSION%" == "6.2" GOTO :NOUPDATE | |
| IF "%VERSION%" == "6.1" GOTO :UPDATETry | |
| ENDLOCAL | |
| :NOUPDATE |
app.asar file from https://drive.google.com/drive/folders/1gbhjOEYH1NPZNB_uMDDNr34sMsgGw8kf?usp=sharingapp.asar file download in step 2 (Override app.asar file)
C:\Program Files\StarUML\resources/Applications/StarUML.app/Contents/Resources//opt/StartUML/resourcesPrompts 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)