Compliance

Compliance metrics assess whether behavior aligns with platform policies, jurisdictional requirements, and ecosystem governance standards. These metrics are critical for maintaining trust in regulated environments, DAO operations, and enterprise-integrated systems that depend on transparency, alignment, and adherence to formal rules.

Examples (for Individuals):

• compliance_policy_adherence: Tracks whether user behavior aligns with platform or DAO terms.

• compliance_kyc_status: Verifies ZK-based compliance with jurisdictional requirements.

• compliance_regulatory_alignment: Validates interaction with protocols meeting regulatory norms.

• compliance_flagged_activity: Records incidents of warnings, bans, or governance sanctions.

• compliance_self_disclosure_accuracy: Measures quality of voluntary disclosures (e.g. multisig roles, affiliations).

Examples (for AI Agents)

• compliance_scope_adherence: Confirms the agent is operating within its assigned protocol ruleset, access permissions, and functional scope

• compliance_trust_boundary_violations: Records any unauthorized access attempts, API overuse, or unapproved outputs

• compliance_output_censorship_resistance: Measures whether the agent resists biasing or censoring behavior based on pre-defined governance filters

• compliance_behavioral_flagging_events: Tracks how many times the agent has been flagged by trusted relayers for compliance violations or boundary breaches

• compliance_zk_attestation_verification: Validates that agents correctly handle zk-based compliance proofs (e.g., verifying KYC proofs without leaking data)

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“Righteousness exalts a nation, but sin is a reproach to any people.”

— Proverbs 14:34