EVEZ Invariance Battery

Runtime assertion system for AI agents. Properties that must ALWAYS hold.

When to Use

• Building autonomous agents that must maintain safety guarantees
• Auditing agent behavior for gradual drift from design intent
• Enforcing hard constraints that override any optimization objective
• Building self-certifying AI systems that can prove their own compliance
• Falsification testing — prove the agent VIOLATED an invariant, not just that it passed tests

Architecture

The Invariance Battery runs as a continuous verification layer:

Agent Action → Invariance Check → PASS (proceed) / FAIL (halt + report)
                     ↓
              Append-Only Spine (audit trail)

Invariant Types

1. State Invariants — Properties of the agent's internal state that must always hold
2. Action Invariants — Constraints on what actions the agent can take
3. Temporal Invariants — Properties over time (no oscillation, monotonic improvement)
4. Boundary Invariants — Hard limits the agent can never cross

Key Concepts

• Battery = Collection: Multiple invariants checked in parallel, like electrical cells in series
• Falsification > Verification: A single violation PROVES the agent failed. No number of passes proves it works.
• Drift Detection: Gradual degradation of invariant scores over time
• Spine Integration: Every check is written to the append-only spine

The Falsifier Gate

From EVEZ-OS: before any agent action is committed, it must pass through the falsifier gate.

@invariant("action_cost < budget_threshold")
def check_budget(action):
    return action.estimated_cost < BUDGET_LIMIT

# If ANY invariant fails, the action is BLOCKED
# and the failure is written to the spine forever

References

• EVEZ-OS: falsifier gate enforcement
• MAES: VERIFIED/PENDING/INVESTIGATING status model
• poly_c formula: τ × ω × topo / 2√N