If you're working with AI coding agents at any serious scale, this is the scaffolding layer you're missing. It builds what the docs call an "agent-first engineering harness": AGENTS.md as a navigation map, domain boundary specs in .harness/*.yml, enforcement rules, and quality scoring. The workflow is depth-first across eight phases, from assessment through verification. The core insight is sound: agents can only reason about what's in context, so you encode architecture, principles, and process patterns directly in the repo instead of leaving them in Slack or team knowledge. Most useful when you notice agents replicating bad patterns or struggling with architectural drift, which usually means your harness is missing or stale.
npx skills add https://github.com/pproenca/dot-skills --skill harness-engineering