Designing a CLI Skill That Structures AI Sessions into Posts -- Architecture, Security, and Implementation Decisions

Body /lovai is a command that structures your AI session into five blocks and posts it to Lovai. It works with Claude Code, Cursor, Codex, and Gemini CLI. Every day, the decisions you make and the problems you hit during AI sessions vanish the moment you close the terminal. I kept losing the reasoning behind good sessions -- even when the final output looked fine, the "why I chose this over three alternatives" was gone by the next morning. I built this skill to solve that problem. This article covers how it was designed and implemented -- why this structure, where things broke, and what trade-offs I made along the way. The Full Architecture Here's the pipeline, end to end: User runs /lovai | v Step 1: Session analysis (extract 5 blocks from conversation context) | v Step 2: Security filtering (detect and strip secrets) | v Step 3: Block composition (auto-assign visibility levels) | v Step 4: Metadata tagging (tool name, model, category) | v Step 5: Preview display -> user confirmati