Arsenal Decision Engine

Arsenal Decision Engine 🛡️

The Risk-Validation Layer for Autonomous AI Agents (DeFAI)

Method and raw results are published — backtest script · result data (180 days of Binance ETH/USDC daily closes):

🔬 Breakeven Corridor is a deterministic algebraic boundary (where IL = accumulated yield). Any position whose price ratio stays within [lower_be, upper_be] has R_net > 0 by mathematical definition — not a probabilistic model.

📐 This engine measures; it does not forecast. No predictive-accuracy figure is claimed — read the published result files and judge the method for yourself.

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Mission

Transform DeFi uncertainty into deterministic, actionable risk metrics for autonomous agents. We do not run stateful trading bots or generate speculative prediction signals; we provide a stateless risk middleware layer that agents query before deploying or maintaining standard constant-product / full-range LP positions.

Built for agents. 100 free calls per IP per day — no wallet, no sign-up, custom parameters included. An L402 payment path is implemented in the gateway but is not operational in production: today, the engine is free to use.

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What This Engine Does

Before an autonomous agent deploys capital or adjusts a standard constant-product / full-range LP position (such as Uniswap V2 or full-range V3), it submits the pool parameters (APY, price ratio, days held) to our API. The engine computes the exact mathematical risk, the net return ($R_{net}$), and the dynamic Breakeven Corridor bounds.

• No LLMs. No hallucinations. Pure algebraic calculation.
• Complexity: $\mathcal{O}(1)$ time and memory.
• Latency: $< 15\text{ms}$ local execution.

Two ways to call it

1. MCP JSON-RPC — the endpoint advertised on the MCP registry

POST https://api.arsenal-quant.com/mcp

{"jsonrpc":"2.0","id":1,"method":"tools/call",

"params":{"name":"evaluate_pool", "arguments":{"apy":0.20,"price_ratio":0.85,"days_held":30}}}

Standard MCP handshake: `initialize` → `tools/list` → `tools/call`. Available over

streamable HTTP and stdio.

2. REST convenience route — no MCP client required

GET https://api.arsenal-quant.com/mcp/evaluate?apy=0.20&price_ratio=0.85&days_held=30

Both routes run the same calculation and the same quota. Note that /mcp/evaluate is GET-only: a POST to that path returns 405 Allow: GET, because JSON-RPC belongs on /mcp.

Engine Response (JSON Contract)

{

"impermanent_loss_pct": 0.3292, "accumulated_yield_pct": 1.6438, "r_net_pct": 1.3146, "il_to_yield_ratio": 0.2, "risk_level": "LOW", "breakeven_corridor": { "lower_ratio": 0.6941, "upper_ratio": 1.4407, "interpretation": "Position remains profitable if price ratio stays within [0.6941, 1.4407]" }, "inputs": { "apy": 0.2, "price_ratio": 0.85, "days_held": 30 }, "source": "Arsenal Decision Engine v2.0", "oracle_signature": " ", "layer": "FREE" }

`layer` reports how the call was served: `FREE` while inside the free quota,

PREMIUM once an L402 payment has been verified. The call shown above is served as FREE.

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Access and Pricing

• Free tier — `evaluate_pool`: 100 calls per IP per day, custom parameters included. No Lightning wallet is needed. This is the only tier currently in service.
• Beyond the free quota: the gateway implements the L402 challenge and returns 402 with a WWW-Authenticate header. The payment rail is not operational in production — invoices issued today are not settleable, and no payment is expected or accepted. Treat the paid tier as announced, not available.
• `GET /mcp/audit/latest`: 3 free calls per IP per hour; beyond that the route returns 402. That response documents the protocol; it is not a live payment path.

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Python Integration Example

import urllib.request

import urllib.error import json import re import os

API_URL = "https://api.arsenal-quant.com/mcp/evaluate?apy=0.20&price_ratio=0.85&days_held=30" LNBITS_URL = "https://demo.lnbits.com"

LNbits requires a wallet key with send permission to pay an invoice.

Use a DEDICATED wallet funded with a small working balance, and never the key

of a wallet holding significant funds. Keep it in the environment, never in code.

LNBITS_PAYMENT_KEY = os.getenv("LNBITS_PAYMENT_KEY")

def query_risk_oracle(): req = urllib.request.Request(API_URL, method="GET") req.add_header("x-agent-id", "autonomous-lp-bot")

try: with urllib.request.urlopen(req) as resp: return json.loads(resp.read().decode('utf-8')) except urllib.error.HTTPError as e: if e.code == 402: auth_header = e.headers.get("WWW-Authenticate") macaroon = re.search(r'token="([^"]+)"', auth_header).group(1) invoice = re.search(r'invoice="([^"]+)"', auth_header).group(1)

pay_req = urllib.request.Request( f"{LNBITS_URL}/api/v1/payments", data=json.dumps({"out": True, "bolt11": invoice}).encode(), headers={"X-Api-Key": LNBITS_PAYMENT_KEY, "Content-Type": "application/json"} ) with urllib.request.urlopen(pay_req) as pay_resp: preimage = json.loads(pay_resp.read().decode())["preimage"]

retry_req = urllib.request.Request(API_URL, method="GET") retry_req.add_header("Authorization", f"L402 {macaroon}:{preimage}") retry_req.add_header("x-agent-id", "autonomous-lp-bot")

with urllib.request.urlopen(retry_req) as final_resp: return json.loads(final_resp.read().decode('utf-8')) else: raise

if name == "main": evaluation = query_risk_oracle() print(f"Risk Level : {evaluation['risk_level']}") print(f"R_net : {evaluation['r_net_pct']:+.4f}%") print(f"Breakeven : {evaluation['breakeven_corridor'}, {evaluation'breakeven_corridor'}]")

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Developer Integration

• Integration cookbook & MCP guides: COOKBOOK.md
• MCP auto-discovery card: https://api.arsenal-quant.com/.well-known/mcp/server-card.json

Why per-call pricing is the intended model

This engine does not prevent losses, and it makes no claim about how much money it saves you. What it does is compute — deterministically, in $\mathcal{O}(1)$ — whether a position sits above or below its breakeven boundary. Each response carries an HMAC tag over the result, which lets the engine detect tampering with its own output; it is a symmetric provenance marker, not a proof a third party can verify independently.

The intended model is per-call pricing, so the cost can be budgeted like any other input. That model is not yet in service: today every call is free.