# Bounty Engineer Mission Digital Twin Planner

> Bounty Engineer Mission Digital Twin Planner is a paid API for AI agents from bounty-engineer-x402-prod.onrender.com, paid per call via x402, $39.9/call, status unknown (last checked 2026-10-12).

Simulates an agentic mission DAG to compute execution order, expected spend, failure costs, fragility hotspots, and success probability before committing real budget.

## Facts

- Endpoint: POST https://bounty-engineer-x402-prod.onrender.com/v1/mission-digital-twin?utm_source=zero.xyz
- Price: $39.9/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-mission-digital-twin-planner-b537a83a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kGMkK-w0-cHsOLrBMGwf9

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-mission-digital-twin-planner-b537a83a -d '<json body>'
```

Example prompt: Before I actually run my 3-step data-collection and verification pipeline, simulate it for me — the nodes are 'collect' (98% success, $4 cost, $2 failure cost, 1000ms) and 'verify' (96% success, $8 cost, $20 failure cost, 1800ms, depends on collect) — I want to stay under a $50 budget, at least 90% mission success probability, and no more than $5 expected failure cost.

## When to prefer this

Use this endpoint when you need a deterministic, pre-execution simulation of a multi-step agentic pipeline to avoid unexpected overspend or mission failure. It is specifically designed for agent-to-agent infrastructure planning with cost routing and failure-cost awareness, making it ideal before committing to expensive or irreversible API call chains. Prefer it over generic DAG schedulers when you need financial exposure analysis (expected failure cost, worst-case spend) and fragility hotspot ranking alongside execution ordering.

## Known failure modes

- Invalid node DAG (cycles or missing dependencies) returns a 4xx error
- Budget or probability thresholds not satisfiable — decision field returns 'blocked' with blocker list
- Fewer than 1 or more than 60 nodes causes schema validation failure
- Malformed success_rate or cost values outside valid ranges rejected
- Service unavailable on Render.com cold-start returning 502/503

## 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 object with the computed execution order (topological sort of the DAG), per-node details (reach probability, expected spend, failure probability, expected failure cost), mission-level aggregates (total expected spend, worst-case exposure, serial latency, overall success probability), a list of fragility hotspots ranked by risk, any blockers preventing execution, a decision field ('ready' or 'blocked'), and a model SHA256 for reproducibility.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "nodes": {
   "type": "array",
   "maxItems": 60,
   "minItems": 1
  },
  "budget_usd": {
   "type": "number"
  },
  "min_success_probability": {
   "type": "number",
   "maximum": 1,
   "minimum": 0
  },
  "max_expected_failure_cost_usd": {
   "type": "number"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "ok": true,
  "mode": "mission_digital_twin",
  "order": [
   "collect",
   "verify"
  ],
  "details": [
   {
    "id": "collect",
    "required": true,
    "latency_ms": 1000,
    "dependencies": [],
    "success_rate": 0.98,
    "declared_cost_usd": 4,
    "reach_probability": 1,
    "expected_spend_usd": 4,
    "failure_probability": 0.02,
    "declared_failure_cost_usd": 2,
    "expected_failure_cost_usd": 0.04
   },
   {
    "id": "verify",
    "required": true,
    "latency_ms": 1800,
    "dependencies": [
     "collect"
    ],
    "success_rate": 0.96,
    "declared_cost_usd": 8,
    "reach_probability": 0.98,
    "expected_spend_usd": 7.84,
    "failure_probability": 0.0392,
    "declared_failure_cost_usd": 20,
    "expected_failure_cost_usd": 0.784
   }
  ],
  "blockers": [],
  "decision": "ready",
  "assumptions": [
   "Declared node success rates are treated as independent for mission-level probability.",
   "Costs, failure costs and latencies are caller supplied.",
   "This is a deterministic planning model, not a guarantee of real-world execution."
  ],
  "model_sha256": "9ef1bcb97d905fd56657e11bc9057034027150dbea5abdc48a2bc7e3c7ae9abb",
  "expected_spend_usd": 11.84,
  "fragility_hotspots": [
   {
    "id": "verify",
    "required": true,
    "latency_ms": 1800,
    "dependencies": [
     "collect"
    ],
    "success_rate": 0.96,
    "declared_cost_usd": 8,
    "reach_probability": 0.98,
    "expected_spend_usd": 7.84,
    "failure_probability": 0.0392,
    "declared_failure_cost_usd": 20,
    "expected_failure_cost_usd": 0.784
   },
   {
    "id": "collect",
    "required": true,
    "latency_ms": 1000,
    "dependencies": [],
    "success_rate": 0.98,
    "declared_cost_usd": 4,
    "reach_probability": 1,
    "expected_spend_usd": 4,
    "failure_probability": 0.02,
    "declared_failure_cost_usd": 2,
    "expected_failure_cost_usd": 0.04
   }
  ],
  "worst_case_exposure_usd": 34,
  "expected_failure_cost_usd": 0.824,
  "declared_serial_latency_ms": 2800,
  "mission_success_probability": 0.9408
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/bounty-engineer-mission-digital-twin-planner-b537a83a/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)