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A map of the eleven open-source repos behind the way I work with coding agents now — grouped into the three things they actually fix: how the agent works, what it knows, and how much of the loop you have to crank yourself.
Most people still use coding agents like a chat box — prompt, wait, copy, fix, repeat. The next step is to stop prompting and design the loop that prompts the agent for you. Here's the shift, the repo that names it, and two tools that make a loop worth running.
A coding agent fails in two quiet, expensive ways: it forgets what it learned last session, and it re-reads your whole codebase to answer a small question. Four open-source tools attack both — memory, knowledge graphs, and context compression — and they map cleanly onto ideas any data engineer already trusts.
A skill is a reusable instruction file that teaches your coding agent how to do a task the way a senior engineer would. Four engineers put theirs on GitHub — here's what's inside, when to reach for each, and the trap to avoid before you copy them in.