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How to hold risky agent tool calls for review with Awesome Jev

Let Jev score tool calls, then have your own policy approve, deny, or send them to a person.

  • Research
  • Advanced
  • 90 minutes
  • From the README
  • Any agent

Credentials. The gate calls a paid, key-based API, so keep the key server-side and scope it to the gating service only.

Who it is forA platform engineer running an agent that calls external tools and needs a review step for uncertain or high-risk actions.

The problemAn agent may call a tool with side effects, and a model-only check is not a permission system.

The outcomeA tool-call gate where Jev gives an advisory signal and application code, not Jev, makes the final approve, deny, or escalate decision.

What you need first

  • A TypeSafe AI API key from the official docs, if you call the API directly
  • Python or Node.js, if you use the SDKs or framework adapters
  • A labeled set of example inputs to test Jev decisions before relying on them

Steps

  1. Read the 'Jev 在 Agent Loop 中的位置' section and the 'Jev 不是什么' list to confirm Jev is a decision layer, not a security boundary.
  2. Open the Vercel eve evaluation guide linked in the 接入方式速查 table and review its auto and evaluate policy options.
  3. Set a policy that sends uncertain or high-risk tool calls to a human, and enforces permissions in your own code.
  4. Test the gate with blocked, allowed, and borderline tool calls, and confirm that tool execution never depends on Jev output alone.

Prompt for your agent

Using the Promethe-us/awesome-jev README, outline a tool-call gate for <my agent> that uses Jev only as an advisory signal and keeps permission checks in application code. Return the policy steps and one test case per outcome, then verify that no tool runs without your own permission check.

Caveat. The README states Jev is not a security boundary and not a physical robot safety controller, so permissions must live in your application code.

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