AI agent wallet spending controls: an evaluation guide

Define exactly what the agent may request

An agent wallet policy should name the workload, wallet, network, asset, permitted action, destination rules, amount limit, and expiry. Write those constraints outside the agent’s prompt, where the authorization service can enforce them. Treat a natural-language instruction as a request, not as signing authority.

Example evaluation scenario: a purchasing agent may request up to 20 native units per purchase and 100 per day from approved destinations. These are illustrative limits, not a live configuration or a production API request.

Read the current deployment contract first

Hybrid-Chain’s published AI Wallet Control milestone exposes authenticated reads and a separately scoped intent evaluation that does not change transaction state. Use the module reference to inspect bindings, policies, budgets, retained decisions, and the required authentication scopes.

Planned lifecycle operations must not be registered as executable agent tools. The public interface does not make transaction construction, approval actions, MPC signing, emergency execution changes, or broadcast available merely because a policy evaluation succeeds.

Evaluate allowed and rejected requests

In an authorized evaluation environment, compare a request inside the policy with one over the amount limit, an unknown destination, an expired grant, and a request using the wrong network. Record the evaluator’s actual decision and reasons. Keep credentials and entered data out of public reports.

Check which constraints are actually represented in the returned contract. A budget shown on a dashboard is not evidence that concurrent spending is reserved atomically; that behavior needs a separate execution test when an execution interface becomes available.

Keep evaluation, approval, and settlement distinct

A successful evaluation reports the result of checking an intent. Human approval, a reserved budget, a threshold signature, broadcast, and final settlement each require their own authoritative evidence. Design your application so that it never displays ‘paid’ merely because an evaluator allowed the request.

Before enabling autonomous execution, demonstrate duplicate-request handling, expiry, policy updates during review, revocation, and recovery after a lost response. Document where a human must intervene and what an emergency control can still stop.

Bring a decision-ready evaluation brief

Use these requirements with your implementation and security teams. Share a high-level workflow—not credentials, wallet identifiers, transaction records, or customer data.

1. Separate proposer from authorizer

   Document what the model may propose and which independent service checks it. Do not let a prompt, tool description, or successful model response grant wallet authority.

2. Specify the asset budget

   State network, asset, amount per request, time window, and destination requirements. Keep native amounts as decimal strings. A dollar-denominated business budget needs a separately defined valuation policy.

3. Build a decision test set

   Include within-policy and over-budget proposals, the wrong network, an out-of-scope caller, and destinations outside the intended policy. First confirm which constraints the deployed contract actually evaluates.

4. Verify no execution side effects

   For the current intent-evaluation interface, confirm that evaluation does not create a reservation, approval, transaction, signature, or broadcast. Do not label its result as paid.

5. Define the later execution gate

   Before a future execution integration goes live, require separate evidence for idempotency, concurrent reservations, human approval, revocation, lost-response recovery, and terminal settlement. These are acceptance requirements, not current public API claims.