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Agent Next Step Selector
x402
Agent Next Step Selector is a paid API for AI agents from agent-product-normalizer.vercel.app, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-18).
Ranks a list of candidate next actions against the current agent state to recommend the best next step
Price / call$0.002
Success—
StatusUnknown
How this service works
Rank candidate next actions against the current agent state
Output
Returns a ranked list of the candidate actions with the recommended best next step highlighted, scored or ordered by appropriateness relative to the provided agent state. Likely includes the top recommended action and a rationale or confidence ordering for the remaining candidates.
Example use cases
Multi-step research agent planning
“My research agent has gathered 5 sources and partially summarized two of them. It has these four possible next actions: 'summarize remaining sources | cross-reference findings | generate report draft | ask user for clarification'. Which one should it do next given that state?”
Customer support bot next action
“My support bot just confirmed the user's account is active and identified a billing discrepancy. Candidate next steps are: 'escalate to billing team | issue automatic refund | ask user for invoice number | send FAQ link'. Rank these against the current state and tell me the best next step.”
Autonomous shopping agent step selection
“My shopping agent has compared three product listings and found the cheapest option. Now it needs to choose from: 'add to cart | check return policy | verify seller rating | notify user'. What should it do next given where it is in the workflow?”
Technical details
Endpoint
GEThttps://agent-product-normalizer.vercel.app/api/v1/choose-next-stepWhen to prefer
Choose this endpoint when an autonomous agent has a concrete list of candidate next actions and needs a lightweight, fast decision on which to execute given its current operational state. It is ideal for multi-step agent pipelines where the orchestrator must pick the next tool call without burning tokens on a full LLM reasoning pass. Prefer this over general-purpose LLM prompting when you want a consistent, cost-effective ranking signal specifically tuned for agent state-action matching.
Side effects
- Missing required 'state' or 'actions' query parameters returns a validation error
- State or actions string exceeds 12000 character limit causing a 400 error
- Ambiguous or poorly formatted actions list (not separated by | or newlines) may produce unreliable rankings
- Empty actions list returns an error or empty ranking
- Service unavailability returns a 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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