by Flamerix AI · MIT License
Tested on Linux, Claude Code 2.1.257–2.1.312 (see Tested versions). The binary is not modified (
BUN_OPTIONS=--preload). An update can silently undo it, so see Verify.
Every ~30 seconds, Claude Code re-sends each background agent's full transcript to the model just
to fill that agent's status line in the agents panel. no-agent-summary.js is a Bun --preload
src: https://www.stationx.net/nmap-cheat-sheet
| Switch | Example | Description |
| UGC/Creator Tools & Platforms | |
| ♡ Trybe: https://jointrybe.com/ [pay per revenue] | |
| ♡ TikTok Creative Exchange: https://ads.tiktok.com/creativeexchange/pc [agency partners, just put dedicated spend behind free assets] | |
| Other Media | |
| ♡ RedCircle: https://redcircle.com/ [podcast ads] | |
| ♡ MNTN: https://mountain.com/ [programmatic tv] | |
| Thought Leaders | |
| ♡ https://www.alyshadotmd.com/ |
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real
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)
