I open-sourced an execution record for AI agents (Intent vs. Reality)

One thing that bothers me about agentic systems: after a long run, we often ask the agent itself what happened. That answer may be good. But the agent’s explanation and the execution record are not the same thing. That led me to build Sentience Governor, an open-source governance runtime for AI agents. I built it with Claude Code. The core idea is to separate: 1. Declared intent — what the agent says it plans to do 2. Recorded execution — the tool activity actually observed 3. Retrospective explanation — what the agent later says it did Sentience records observable tool activity and checks it against the objective and scope declared before execution. Through MCP, the agent can also query that record instead of relying entirely on what remains in context. The declaration itself isn’t automatically trustworthy — an agent can still declare something too broad or simply wrong. The distinction I care about is: The agent’s explanation isn’t the evidence. The recorded execution trail is. Today Sentience observes and reports; it doesn’t block actions yet. That’s the part I’m working through now: What would you actually trust a governance layer to block? A tool call outside declared scope? A destructive action? An agent starting work without declaring intent? Or should governance remain advisory? If you’re building agents or agent infrastructure, I’d especially like to hear where you think this model breaks. I’ll put the open-source repo in the comments for anyone who wants to try it or inspect the implementation.