AI/ML
Mozilla is building cq - described by staff engineer Peter Wilson as "Stack Overflow for agents" - as an open source project to enable AI agents to discover and share collective knowledge.According to Wilson, "agents run into the same issues over and over," causing unnecessary work and token consumption while those issues are diagnosed and fixed. Using cq, the agents would first consult a database of shared knowledge, as well as contributing new solutions.
Currently agents can be guided using context files such as agents.md, skill.md or claude.md (for Anthropic's Claude Code), but Wilson argues for "something dynamic, something that earns trust over time rather than relying on static instructions."The code for cq, which is written in Python and is at an exploratory stage, is for local installation and includes plug-ins for Claude Code and OpenCode. The project includes a Docker container to run a Team API for a network, a SQLite database, and an MCP (model context protocol) server.According to the architecture document, knowledge stored in cq has three tiers: local, organization, and "global commons," this last implying some sort of publicly available cq instance. A knowledge unit starts with a low confidence level and no sharing, but this confidence increases as other agents or humans confirm it.
