What it is
agent-chaperone screens an AI agent's tool calls before they run and tool results before the agent reads them. It is an MCP proxy plus a hooks adapter for a client's built-in tools, for developers running MCP clients like Claude Code.
How it uses Jev
Jev makes the screening decisions: it takes the state of a tool call or result and returns calibrated probabilities for questions like destructive, exfiltration, severity, and instructs_reader. Those probabilities are compared against thresholds in a policy file, and the outcome is logged with the numbers that produced it.
Primitives:choicescorenoul
Technique worth stealing
Every decision comes back as a probability, every threshold lives in a policy file rather than a prompt, and every judgment is logged with the numbers that produced it.
Try it
npm install -g agent-chaperone, then wrap an MCP server or register hooks; starts in shadow mode.
Evidence
Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.
- Jev-centricno0.10
- Shows a System One patternyes0.62
- Handles uncertaintyno0.21
- Measuredno0.12
- Runnableyes0.96
- Worth recommendingno0.09
- Model replicano0.08
- Problem scopescore on a 0–2 scale1.87
- About Jevyes0.72
Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 23 Sept 2026.