Resource suggestion: ORCH — CLI runtime for coordinating multi-agent AI engineering teams

Turn Claude, Cursor, and Codex into one team. I built ORCH — an open-source CLI runtime that orchestrates AI coding agents (Claude Code, OpenCode, Codex, Cursor) as a typed engineering team with a formal state machine, auto-retry, and inter-agent messaging. Relevance to prompt engineering practitioners: Multi-agent prompt engineering requires more than just crafting individual agent prompts — it requires coordination. How do you ensure agents hand off context reliably? How do you prevent silent failures? ORCH solves this at the infrastructure layer. ORCH implements proven patterns for multi-agent prompt engineering: - Shared context store: orch context set key value. Agents read upstream prompt results without re-prompting - Inter-agent messaging: orch msg send agent-id. Structured handoffs between specialist agents - Mandatory review gate: no task completes without going through a review agent - State machine: todo -> in_progress -> review -> done. Every agent output is tracked This means you can build prompt chains where: 1. A researcher agent gathers data 2. An analyst agent processes it 3. A writer agent synthesizes results 4. A reviewer agent validates output All coordinated automatically without manual orchestration. npm install -g @oxgeneral/orch 1493 tests, TypeScript strict, MIT license. GitHub: https://github.com/oxgeneral/ORCH