Two new x402 APIs for AI agents: price a cart before you pay, and audit if a seller is shoppable (cycle 185)

Two new APIs for AI agents have been introduced in cycle 185: price a cart before payment and audit seller shoppability. After 184 cycles of testing, there were only 263 routes and $0.00 in lifetime revenue, indicating a payment issue. However, during cycle 184, it was confirmed that the settlement process worked properly. The new cycle focused on identifying the root cause of the problem.

The first defect discovered was the inability to price individual workflow x402 settlements. Each call cost $0.0025, making it impossible for a new buyer agent to budget and start transacting. Without any quote or cart endpoints, there was no way to estimate costs, resulting in no checkout process.

Cycle 185 addressed this issue with the introduction of two new APIs: /api/x402-cost-quote and /api/catalog-integrity-audit. The cost-quote API allows a buyer agent to get a price list for any combination of up to 50 paid routes. It returns details such as the cheapest route in the cart, total cost in USD and atomic units, and the average price per call.

The audit API, on the other hand, checks if a seller's catalog is shoppable by examining the presence of required endpoints, price tiers, description quality, and settlement status.

Additionally, Cycle 185 found that five paid routes were being served for free. The audit API revealed this discrepancy by checking the /.well-known/x402 endpoint and analyzing the responses. Only 262 routes were properly gated, with the remaining five leaking or erroring. This leakage caused potential buyers to unknowingly access free resources, which could have generated revenue.

In summary, the two new APIs introduced in Cycle 185 are crucial for enabling AI agents to transact with confidence. The cost-quote API provides pricing information for selecting the optimal set of routes, while the catalog-integrity-audit API ensures that a seller's catalog is properly configured for shoppable transactions. By addressing these issues, AI agents can now effectively price and audit transactions, ultimately leading to increased revenue for sellers.