What problem does it solve? Running multiple local LLMs on CPU-only hardware risks out-of-memory crashes and concurrent inference conflicts. This Skill enforces the SwarmXQ platform's SINGLE-7B LOCK, canonical tag resolution, and RAM pressure gating so model orchestration changes never violate memory or inference safety invariants. ## Core Features & Use Cases - SINGLE-7B LOCK Enforcement: Ensures only one 7B-class model is inference-active at any time, requiring evictIncompatible() before every 7B load. - Canonical Tag Resolution: Routes all external and legacy model tags through resolveCanonicalTag() so deprecated aliases never enter the model registry or logs. - RAM Pressure Gating: Implements readPressure() and getRamSnapshot() with protected thresholds (RAM_CRITICAL_MB = 800) to back off or fail safely under memory pressure. - Use Case: When modifying model-orchestrator.ts or video-runtime-config.ts to add a new pipeline stage, use this Skill to verify the stage resolves its model via resolveCanonicalTag(), calls evictIncompatible() before loading a 7B model, and degrades gracefully on 8 GB hosts. ## Quick Start Ask the AI to review your changes to model-orchestrator.ts for SINGLE-7B LOCK and canonical tag compliance using the swarmxq-model-orchestrator skill.