I got tired of agents that could do anything, so I built the layer that stops them

Everyone's building AI agents. Nobody's building what governs them. MCP standardized how agents talk to tools. A2A standardized how they talk to each other. Neither says anything about what an agent is actually *allowed to do* once it's talking. So I built that layer. Today it ships as a runtime enforcer. ```python from scyvera import ContractEnforcer enforcer = ContractEnforcer.load("contract.yaml") enforcer.gate("push_to_main", "side_effect") def deploy(): ... # Not in the contract → ContractViolationError before execution ``` Every agent declares its permissions, side effects, and approval boundaries upfront. The enforcer holds it to that declaration at runtime. Every decision - allowed, denied, pending approval - goes to an immutable audit log. It's MIT licensed, 20+ stars, and the spec is framework-agnostic (n8n, LangGraph, or whatever you're running). What it honestly doesn't do: it can't stop a developer from calling an ungated function directly. That's a known limitation and it's documented. Curious if anyone's hit the governance problem in production - how are you handling it today?