stas4000

AI Operator Kit — AI skill for Claude Code

AI community

Battle-tested patterns from running AI agents in production daily: the CLAUDE.md that finishes work, a 5-layer agent memory stack, overnight autoresearch loops, and LLM-judge alignment.

How to install AI Operator Kit

This entry records only its repository, not the path inside it, so there is no exact command to give. Open stas4000/ai-operator-kit and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What AI Operator Kit does

Battle-tested patterns from running AI agents in production daily: the CLAUDE.md that finishes work, a 5-layer agent memory stack, overnight autoresearch loops, and LLM-judge alignment.

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README

AI Operator Kit

Battle-tested patterns from running AI agents in production, every day, for real businesses. Not theory. Everything here is distilled from systems that have been live for months: a personal AI operator on Telegram, autonomous sales and content pipelines, and overnight self-improvement loops.

Free to use, MIT licensed. Take what works.

What's inside

Asset What it does
claude-md/CLAUDE.md The agent instruction file that turns a coding agent from a suggestion machine into an operator that finishes work. Binary verification, complete-fix loops, ground-every-claim rules.
memory/MEMORY-STACK.md A five-layer memory architecture for long-running assistants that stays coherent after months of daily use. Each layer fails independently.
autoresearch/AUTORESEARCH-LOOP.md The overnight self-improvement loop: one asset, one honest number, one change per round. Keep winners, revert losers.
autoresearch/JUDGE-ALIGNMENT.md How to catch a lying LLM judge before it sends your optimization loop up a fake hill. Golden sets, consistency checks, ranking accuracy.

Who this is for

Anyone running AI agents on real work: builders, operators, small teams. You do not need to be deeply technical. Every doc explains the idea in plain language first, then gives you the exact artifact to copy.

Follow along

I post what we learn running these systems daily: [@stas_sorokin_](https://x.com/stas_sorokin_) on X.

Built by [Bles Software](https://bles-software.com).