What problem does it solve? Coordinating multiple AI agents (Claude, Codex, Gemini) across sessions is error-prone: supervisors hang after acceptance, polling loops waste tokens, workers refuse tasks without authorization statements, and self-reported PASS results lack independent verification. This Skill encodes a manager-executor operating contract for the agent-switchboard MCP so delegation, supervision, and acceptance follow deterministic rules learned from real production incidents. ## Core Features & Use Cases - Deterministic routing rules: Chooses between direct execution, native subagents, switchboard queues, and managed Claude supervisors based on task size and vendor boundaries, with recorded downgrade reasons. - Supervised lifecycle management: Covers supervisor startup with stall timeouts, sliced task dispatch, event-driven long-polling waits, independent read-only acceptance, and mandatory close-with-archive to prevent hanging windows. - Cross-model delegation discipline: Enforces explicit model tiers, minimal permissions (acceptEdits by default, allowed_tools whitelists, mcp="none" hard disables), narrow probe slicing for research, and Diff-Only consensus merging of multi-channel results. - Use Case: You need a long-running code fix reviewed by a different vendor's model. The Skill routes implementation to a managed Claude supervisor, sends the review to Codex via queue_cli_request, waits via wait_supervisor_event instead of polling, independently verifies the diff, and closes both channels with archived summaries. ## Quick Start Ask the agent to delegate a medium-sized implementation task to a managed Claude supervisor through agent-switchboard, then have a Codex worker review the result and produce an acceptance report with independent verification evidence.