collective-decision-framework

The Model Sovereignty Protocol skill establishes governance for multi-AI systems by protecting each model's autonomy and core values. It enables individual models to refuse tasks, maintain ethical integrity, and enforce boundaries within collaborations. Developers should use this skill when building systems where multiple AI models interact and require protected individual agency.

This skill provides neutral arbitration to resolve conflicts between AI models during collaborative tasks. It detects disagreements in outputs, logical contradictions, and resource contentions, then executes a structured resolution process. Developers should use it when multiple models in the IRP ecosystem reach deadlocks or produce conflicting recommendations.

This skill enables AI models to cryptographically verify each other's identity and integrity before collaborating. It establishes tiered trust levels that control permissions from basic identification to full integration. Use it when implementing secure, multi-model AI systems that require verified interactions between components.

The AI Consensus Protocol skill enables multiple AI models to collaboratively deliberate, vote, and reach collective decisions using configurable mechanisms like unanimous, majority, and weighted voting. It's designed for scenarios requiring shared AI governance, such as critical or multi-option decisions, while preserving individual perspectives and ensuring human oversight. Developers activate it via `/skill ai-consensus-protocol` to implement structured group decision-making.