OpenClaw agents move fast. That’s the point.
But the moment your agent can spend, a new requirement appears: a checkout flow that stays safe when the agent is wrong.
This post is the simplest production-friendly pattern we’ve found:
Intent → Card → Verify
It works for ecommerce, SaaS, and “buy API credits” style purchases, and it’s designed around one principle:
Don’t let an agent spend money unless you can explain the charge later.
If you’re starting from zero, also see: OpenClaw Payments and Signets MCP.
The 3-step flow
1) Intent (declare what will be bought)
The agent must declare the purchase before any credentials are released.
What you want in an intent:
- ▸Purpose (human readable)
- ▸Expected amount (or range)
- ▸Expected merchant (when possible)
- ▸Optional recurrence window for subscriptions
Example MCP call:
signets.intents.create(
purpose="Buy $50 of API credits for Example API",
expectedAmount=5000,
expectedMerchant="exampleapi.com"
)
Why this matters: intent is an audit primitive. It’s also your main policy hook (“approve/deny/escalate”).
2) Card (issue/unlock isolated credentials)
Once the intent is approved, the system issues a dedicated card or unlocks an existing locked card for a narrow window.
For sensitive card data, require:
- ▸
intentId(links the purchase) - ▸
reason(forces a natural-language justification)
signets.cards.get_sensitive(
cardId="card_xyz",
intentId="int_abc123",
reason="Checkout for API credits (approved intent)"
)
Rule of thumb: if an agent can call “get me raw credentials” without an intent, you don’t have a safe system. You have a password manager with a chatbot glued on.
3) Verify (confirm spend matched intent)
After checkout, verify the resulting transaction matches the intent.
signets.transactions.list_for_card(cardId="card_xyz")
At minimum, compare:
- ▸amount (exact or within tolerance)
- ▸merchant name / descriptor
- ▸time window
- ▸intent purpose tag
Then store an evidence record:
{
"intentId": "int_abc123",
"cardId": "card_xyz",
"merchant": "EXAMPLEAPI.COM",
"amount": 5000,
"currency": "USD",
"transactionId": "txn_123",
"decision": "approved",
"reason": "API credits",
"verifiedAt": "2026-02-05T18:22:10Z"
}
This is the single best “future-you” feature you can add.
A 5-minute ecommerce example
This is the flow you can copy into your OpenClaw “payments skill pack” README.
Step 0: Preconditions
- ▸Your Signets account is funded.
- ▸You can authenticate to MCP (OAuth or agent token).
Check status:
signets.kyc.status
signets.balance.get
Step 1: Create intent
signets.intents.create(
purpose="Buy a replacement USB-C hub",
expectedAmount=3500,
expectedMerchant="amazon.com"
)
If the purchase is above a threshold, your policy should require approval instead of auto-issuing a card.
Step 2: Checkout with isolated credentials
signets.cards.get_sensitive(
cardId="card_xyz",
intentId="int_abc123",
reason="E-commerce checkout for USB-C hub"
)
Step 3: Verify transaction
signets.transactions.list_for_card(cardId="card_xyz")
If it doesn’t match the intent, treat it like an incident:
- ▸re-lock card
- ▸alert a human
- ▸attach logs and page artifacts
Where safety breaks (and how to prevent it)
Failure mode: “The agent retried and double-charged”
Agents retry. Merchants can return ambiguous responses. Result: duplicate charges.
Control: add a “velocity check” in policy (“no more than 1 transaction per merchant per 60 seconds”) and/or enforce a “one intent → one successful transaction” constraint.
Failure mode: “Merchant drift”
The agent is allowed to buy in one domain but ends up spending elsewhere.
Control: merchant allowlists and category/MCC locks where possible.
See: Merchant Drift.
Failure mode: “The agent asked for bigger limits”
If the agent can request its own scope, it will eventually request too much—by bug, compromise, or misinterpretation.
Control: policies must be enforced by the system, not the agent.
See: Shared credentials are dangerous.
Recommended internal links for this post
If you’re building this as an acquisition wedge, every OpenClaw payment post should link to:
- ▸OpenClaw Payments (canonical)
- ▸MCP (setup)
- ▸Pricing (conversion)
- ▸AI Agent Overspend Postmortem (risk)
- ▸AI Agent Chargebacks (liability)
Bottom line
If you want OpenClaw momentum without lighting money on fire:
- ▸Make intent mandatory.
- ▸Keep credentials isolated and time-bounded.
- ▸Verify every transaction and store evidence.
That’s the checkout flow that scales.
Looking for agent spending controls? Start with MCP + skills, then choose a plan that fits your workload.