Bounty Engineer Agent Commerce Plan is a paid API for AI agents from bounty-engineer-x402-prod.onrender.com, paid per call via x402, $0.025/call, status unknown (last checked 2026-10-12).
Routes autonomous agent API spend across candidate providers by optimizing for policy, budget, trust, and latency, returning a ranked plan with affordability checks and fallback ordering.
Machine-buyable infrastructure for autonomous agents: API cost routing, margin optimization, funding-rate data, webpage extraction, result verification, spend controls, retry planning, state, tender search and GitHub bounty intelligence.
Returns a JSON object with a top-level decision ('ready' or otherwise), the selected best-fit provider including its price, trust score, success rate, balanced score, and latency, plus an affordability array for all candidates showing projected spend and max calls within budget, a full route plan with fallback ordering, and any limitations or caveats about the computation.
POSThttps://bounty-engineer-x402-prod.onrender.com/v1/agent-commerce-plan?utm_source=zero.xyzUse this endpoint when an autonomous agent needs to deterministically select among multiple API providers given a fixed budget and call volume, especially when policy-driven trade-offs between cost, reliability, trust, and latency are required. Prefer this over manual routing logic when you need a structured fallback order and affordability projection in a single call.
| Field | Type | Description |
|---|---|---|
| policy | string | |
| budget_usd | number | |
| candidates | array | |
| constraints | object | |
| expected_calls | integer |
{
"type": "json",
"example": {
"ok": true,
"mode": "agent_commerce_plan",
"decision": "ready",
"selected": {
"price_usd": 0.01,
"fits_budget": true,
"provider_id": "alpha",
"expected_calls": 100,
"projected_spend_usd": 1,
"max_calls_with_budget": 200
},
"budget_usd": 2,
"route_plan": {
"ok": true,
"mode": "provider_route_plan",
"policy": "balanced",
"decision": "route",
"rejected": [],
"selected": {
"id": "alpha",
"price_usd": 0.01,
"trust_score": 0.9,
"success_rate": 0.99,
"balanced_score": 0.8255,
"p95_latency_ms": 500,
"freshness_seconds": null
},
"limitations": [
"Balanced scoring uses fixed transparent weights: reliability 45%, trust 20%, latency 20%, cost 15%. Inputs are supplied by the caller and are not independently verified."
],
"fallback_order": [
{
"id": "alpha",
"price_usd": 0.01,
"trust_score": 0.9,
"success_rate": 0.99,
"balanced_score": 0.8255,
"p95_latency_ms": 500,
"freshness_seconds": null
},
{
"id": "beta",
"price_usd": 0.005,
"trust_score": 0.8,
"success_rate": 0.95,
"balanced_score": 0.7375,
"p95_latency_ms": 800,
"freshness_seconds": null
}
]
},
"limitations": [
"Combines caller-supplied provider measurements with a deterministic budget check. It does not make payments or guarantee service quality."
],
"affordability": [
{
"price_usd": 0.01,
"fits_budget": true,
"provider_id": "alpha",
"expected_calls": 100,
"projected_spend_usd": 1,
"max_calls_with_budget": 200
},
{
"price_usd": 0.005,
"fits_budget": true,
"provider_id": "beta",
"expected_calls": 100,
"projected_spend_usd": 0.5,
"max_calls_with_budget": 400
}
],
"expected_calls": 100
}
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