Proposal: Add Formal Responsibility Tracking System

[qizwiz]

Building on the tool execution authenticity verification work (PR #3378) and workflow transparency improvements, I'd like to propose adding a formal responsibility tracking system to CrewAI.

This would provide mathematical guarantees for agent behavior rather than empirical validation:

Key Features

1. Capability-Based Agent Hierarchy: Agents organized in competence-based hierarchies where higher-capability agents supervise lower-capability ones

2. Mathematical Responsibility Assignment: Provable assignment of responsibility based on hierarchy distance and decision outcomes

3. Accountability Logging: Complete audit trails with formal verification of decision paths

4. Performance-Based Capability Adjustment: Automatic capability updates based on proven performance metrics

Benefits

• Mathematical Proofs: Decision routing correctness, responsibility bounds, system stability
• Enterprise Readiness: Formal compliance and audit trails for regulated environments
• Safety Guarantees: Provable safety properties rather than testing-based assurance
• Scalability: Formal methods that scale with system complexity

I have a working implementation based on formal verification principles and would love to hear thoughts from maintainers on this direction.

[qizwiz]

@joaomdmoura @maintainers

Updating this proposal to better reflect the distributed systems foundations:

This isn't just "formal responsibility tracking" - it's implementing Byzantine Fault Tolerant consensus protocols for multi-agent AI systems using established distributed systems principles.

The mathematical framework provides the same safety guarantees as PBFT, but adapted for AI agent hierarchies with formal verification instead of empirical validation.

This addresses real enterprise needs for provable AI safety and regulatory compliance.