What problem does it solve? Running multiple AI coding agents in parallel often leads to API failures, uncontrolled tool access, and conflicting file changes. This Skill coordinates sub-agent dispatches so each task gets only the MCP servers it needs, automatically recovers from provider errors, and isolates work in separate git worktrees. ## Core Features & Use Cases - Fixed Agent Rotation: Dispatches tasks in a strict claude → mini rotation, using claude for reasoning-heavy work (audits, reviews, design) and mini for execution (fixes, tests, migrations). - Provider Fallback Chain: Automatically retries failed API calls across an ordered chain of eight providers (modal → nvidia → nebius → opencode → zai → wafer-serverless → openrouter → zenmux), then falls back to the other agent. - Scoped MCP Configuration: Dynamically writes ~/.claude.json or a temporary mini YAML config so each sub-agent receives only the MCP servers relevant to its task, with cleanup via trap handlers. - Worktree Isolation: Assigns one git worktree per dispatch, then merges, verifies, and cleans up results centrally. - Use Case: Dispatch a security audit to claude with github, tavily-search, and gitnexus MCP servers in one worktree, while mini writes a database migration with the postgres MCP server in another, then merge both after review. ## Quick Start Ask the orchestrator to dispatch a code review task to the next agent in rotation with the appropriate MCP servers and an isolated git worktree.