# Bounty Engineer Batch Budget Planner

> Bounty Engineer Batch Budget Planner is a paid API for AI agents from bounty-engineer-x402-prod.onrender.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-12).

Plans how to allocate a fixed USD budget across multiple API jobs by priority, determining which calls to fund, drop, or partially schedule.

## Facts

- Endpoint: POST https://bounty-engineer-x402-prod.onrender.com/v1/batch-budget-plan?utm_source=zero.xyz
- Price: $0.005/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-12
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/bounty-engineer-batch-budget-planner-996eaafd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tqxjPRRm4Rio1eznwkFtu

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability bounty-engineer-batch-budget-planner-996eaafd -d '<json body>'
```

Example prompt: I have a $1 budget and need to run 20 verify calls at $0.02 each and 100 enrich calls at $0.01 each — can you plan which ones to fund first by priority and allow partial execution if needed?

## When to prefer this

Use this endpoint when an autonomous agent needs to pre-plan API spending across multiple heterogeneous job types before committing funds — especially when the total cost may exceed available budget and you need deterministic priority-first allocation with partial execution support. Prefer over manual budgeting logic when jobs have different priorities and unit prices and you want a structured, auditable spend plan.

## Known failure modes

- Empty or invalid jobs array returns a validation error
- budget_usd of zero or negative causes invalid input error
- More than 100 jobs in the array exceeds maxItems constraint
- Missing required fields (jobs or budget_usd) returns 400-level error
- Upstream Render instance cold start may cause latency or timeout on first call
- Payment failure via x402 protocol prevents job execution

## How this service works

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.

## Output

Returns a JSON plan with per-job breakdown of planned_calls, dropped_calls, planned_spend_usd, and unit_price_usd; a top-level decision field ('fully_funded', 'partially_funded', etc.); total planned_spend_usd; headroom_usd remaining; and any allocation limitations or caveats.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "jobs": {
   "type": "array",
   "maxItems": 100,
   "minItems": 1
  },
  "budget_usd": {
   "type": "number"
  },
  "allow_partial": {
   "type": "boolean"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "ok": true,
  "mode": "batch_budget_plan",
  "plan": [
   {
    "id": "verify",
    "calls": 20,
    "priority": 100,
    "dropped_calls": 0,
    "planned_calls": 20,
    "unit_price_usd": 0.02,
    "planned_spend_usd": 0.4
   },
   {
    "id": "enrich",
    "calls": 100,
    "priority": 60,
    "dropped_calls": 40,
    "planned_calls": 60,
    "unit_price_usd": 0.01,
    "planned_spend_usd": 0.6
   }
  ],
  "decision": "partially_funded",
  "budget_usd": 1,
  "limitations": [
   "Allocation is deterministic priority-first planning. It does not estimate business value or guarantee provider success."
  ],
  "headroom_usd": 0,
  "allow_partial": true,
  "planned_spend_usd": 1
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/bounty-engineer-batch-budget-planner-996eaafd/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from bounty-engineer-x402-prod.onrender.com](https://www.zero.xyz/host/bounty-engineer-x402-prod.onrender.com/llms.txt)