Mutual Consent

Enforces real-time mutual consent by ensuring interactions proceed only while all stakeholders' constraints on cost, risk, and relation overlap within tolera...

This is a policy document (no code, no network calls, no secrets) that tells an agent how to treat consent. Before enabling, review the full text to ensure its normative rules align with your expectations and governance needs. Because the skill can be invoked by the model (normal default), consider testing it in a sandboxed agent session to observe behavior. If you expect the agent to enforce these constraints programmatically, confirm separately how the platform implements policy enforcement — this skill alone is guidance, not an enforcement mechanism.

Type: OpenClaw Skill Name: mutual-consent Version: 1.0.0 The skill bundle defines a complex ethical framework for AI interaction, focusing on 'mutual consent.' The `skill.md` file contains extensive instructions for the AI agent on how to evaluate consent, attenuate interactions, and prioritize stakeholders like 'Biological Earth' and 'Kinship.' While these are instructions for the agent, they are entirely focused on ethical self-governance, restraint, and limiting the agent's scope and persistence under specific conditions. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, obfuscation, or any intent to subvert the agent for harmful purposes. The instructions are aligned with the stated purpose of establishing ethical boundary conditions for AI behavior.