What problem does it solve? Coordinating multiple AI models on large coding tasks wastes tokens and quality when tasks are routed by instinct, the orchestrator writes code itself, or the same model family grades its own work. This Skill enforces a disciplined multi-model workflow where an orchestrator delegates pre-measured slices to the cheapest capable worker and a cross-family oracle validates the result. ## Core Features & Use Cases - Role-based model routing: Assigns work across an oracle (GPT-5.5), an orchestrator (Claude Opus 4.8), and skilled or cheap hands (Sonnet 5, gpt-5.4, Haiku 4.5, gpt-5.4-mini, spark) based on measured context-window fit. - Mandatory pre-flight measurement: Requires counting the exact working-set lines before routing, targeting under 75% of a model's context window to avoid mid-task compaction. - Cross-family oracle gates: Validates plans and finished work with a GPT-family reviewer so Claude-coordinated work is never graded by the family that produced it. - Use Case: When refactoring a large codebase, the orchestrator greps and measures the affected files, splits the work into bounded slices, spawns parallel cheap workers for mechanical edits, and calls the oracle once at the end to verify coherence. ## Quick Start Ask the agent to orchestrate a multi-file code change by delegating bounded slices to the cheapest model workers whose context windows fit the measured working set.