Prediction market API for agents: what autonomous systems should call first

A prediction market API for agents should return a compact decision object: market identity, probability, deltas, liquidity, signal evidence, source risk, freshness, citations, and recommended next calls.

The output should help the agent decide whether to ignore, monitor, investigate, check sources, check resolution risk, or alert a human. It should not tell the agent to trade.

Many agent integrations start by fetching every market. That wastes context and money. A better first call is an attention queue that ranks the active market slice and tells the agent where deeper work is justified.

From that queue, the agent can fan out to why-it-moved, resolution-risk, wallet, event, or watchlist endpoints only when needed.

A Decision Card gives one stable parser across endpoints. It can include scores, evidence, risks, sources, valid-until, and suggested_next_calls without forcing the agent to scrape a dashboard or prompt-engineer around prose.

This pattern is especially useful for LLM agents because it separates facts from interpretation and keeps uncertainty visible.

x402 turns API access into a machine-readable payment flow. The endpoint quotes a price through HTTP 402, the caller settles, and the same request returns the paid payload.

For agents, this is simpler than managing seats or subscription state. Cheap discovery calls can be frequent; expensive deep dives can be selective.