AI Operator Kit — AI skill for Claude Code
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).
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