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Cq – Stack Overflow for AI coding agents

Hi all, I'm Peter at Staff Engineer and Mozilla.ai and I want to share our idea for a standard for shared agent learning, conceptually it seemed to fit easily in my mental model as a Stack Overflow for agents.The project is trying to see if we can get agents (any agent, any model) to propose 'knowledge units' (KUs) as a standard schema based on gotchas it runs into during use, and proactively query for existing KUs in order to get insights which it can verify and confirm if they prove useful.It's currently very much a PoC with a more lofty proposal in the repo, we're trying to iterate from local use, up to team level, and ideally eventually have some kind of public commons.At the team level (see our Docker compose example) and your coding agent configured to point to the API address for the team to send KUs there instead - where they can be reviewed by a human in the loop (HITL) via a UI in the browser, before they're allowed to appear in queries by other agents in your team.We're learning a lot even from using it locally on various repos internally, not just in the kind of KUs it generates, but also from a UX perspective on trying to make it easy to get using it and approving KUs in the browser dashboard. There are bigger, complex problems to solve in the future around data privacy, governance etc. but for now we're super focussed on getting something that people can see some value from really quickly in their day-to-day.Tech stack:* Skills - markdown* Local Python MCP server (FastMCP) - managing a local SQLite knowledge store* Optional team API (FastAPI, Docker) for sharing knowledge across an org* Installs as a Claude Code plugin or OpenCode MCP server* Local-first by default; your knowledge stays on your machine unless you opt into team sync by setting the address in config* OSS (Apache 2.0 licensed)Here's an example of something which seemed straight forward, when asking Claude Code to write a GitHub action it often

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