Aerodrome

Aerodrome Trading

Overview

Use this skill only for Aerodrome trading on Base through Superior Trade. Aerodrome is spot-only AMM swap execution: no futures, no margin, no shorting, no leverage, no sub-accounts, and no order book.

Production Defaults

• Superior Trade API base URL: https://api.superior.trade
• Auth header: x-api-key: $SUPERIOR_TRADE_API_KEY
• Base RPC URL: https://mainnet.base.org
• Keep setup simple: one pair, one numeric stake amount, static pairlist, market orders, and no orderbook pricing.

Source Of Truth

When behavior is unclear, inspect these local sources before answering:

• Production API: https://api.superior.trade

Non-Negotiables

• Use exchange.name: "aerodrome".
• Use only the supported spot pairs: AERO/USDC and CHECK/USDC. Never use :USDC.
• Omit trading_mode, or set it to "spot" only.
• Never set margin_mode, leverage, short entries, or futures fields.
• Set entry_pricing.use_order_book: false and exit_pricing.use_order_book: false.
• Do not call self.dp.orderbook(), fetch_order_book, fetch_l2_order_book, or order-book depth checks in strategy code.
• Use market orders. Aerodrome's CCXT adapter supports AMM market swaps, not limit-order-book execution.
• Use explicit numeric stake_amount. Avoid "unlimited" unless the user explicitly accepts balance exhaustion risk.
• Never include wallet private keys or platform-injected exchange credentials in config.
• Use https://mainnet.base.org for exchange.ccxt_config.options.rpcUrl unless the user explicitly provides another Base RPC.
• Always backtest before suggesting live deployment.
• Never start live trading without explicit user confirmation.

Wallet And Balance Rules

Aerodrome live trading depends heavily on the Base wallet balances because every order is an on-chain swap.

Before live deployment or when troubleshooting zero trades:

1. Verify the wallet has enough quote token for buys, usually USDC.
2. Verify it has enough base token for sells, such as AERO for AERO/USDC.
3. Verify it has Base ETH for gas. A small ETH balance is required even when trading USDC pairs.
4. Size stake_amount * max_open_trades below free quote balance and leave room for AMM slippage, token fees, and gas. Prefer 70-90% of available quote balance, lower for small wallets.
5. If the wallet balance cannot be checked in the current turn, say it has not been checked. Do not infer or fabricate balances.

Important distinction: Aerodrome uses Base wallet balances directly for on-chain swaps. Do not apply external exchange account rules here.

Supported Markets

Hard-code these Aerodrome/Base market definitions when configuring exchange.ccxt_config.options.markets:

Symbol	Base address	Base decimals	Quote address	Quote decimals	Pool address	Stable
AERO/USDC	0x940181a94A35A4569E4529A3CDfB74e38FD98631	18	0x833589fcd6edb6e08f4c7c32d4f71b54bda02913	6	0x6cdcb1c4a4d1c3c6d054b27ac5b77e89eafb971d	false
CHECK/USDC	0x9126236476eFBA9Ad8aB77855c60eB5BF37586Eb	18	0x833589fcd6edb6e08f4c7c32d4f71b54bda02913	6	0x6a4BeFa1337865071E27c62dc9d7E3bCa253cE0f	false

Backtesting data is available for both supported pairs on 5m, 15m, 1h, 4h, and 1d.

Minimum Config

Start from this shape and only change pair_whitelist, timeframe, stake, and strategy parameters. Keep the hard-coded supported markets and no-orderbook fields.

{
  "exchange": {
    "name": "aerodrome",
    "pair_whitelist": ["AERO/USDC"],
    "ccxt_config": {
      "options": {
        "rpcUrl": "https://mainnet.base.org",
        "markets": [
          {
            "symbol": "AERO/USDC",
            "baseAddress": "0x940181a94A35A4569E4529A3CDfB74e38FD98631",
            "baseDecimals": 18,
            "quoteAddress": "0x833589fcd6edb6e08f4c7c32d4f71b54bda02913",
            "quoteDecimals": 6,
            "poolAddress": "0x6cdcb1c4a4d1c3c6d054b27ac5b77e89eafb971d",
            "stable": false
          },
          {
            "symbol": "CHECK/USDC",
            "baseAddress": "0x9126236476eFBA9Ad8aB77855c60eB5BF37586Eb",
            "baseDecimals": 18,
            "quoteAddress": "0x833589fcd6edb6e08f4c7c32d4f71b54bda02913",
            "quoteDecimals": 6,
            "poolAddress": "0x6a4BeFa1337865071E27c62dc9d7E3bCa253cE0f",
            "stable": false
          }
        ]
      }
    }
  },
  "stake_currency": "USDC",
  "stake_amount": 10,
  "max_open_trades": 1,
  "timeframe": "5m",
  "stoploss": -0.1,
  "minimal_roi": { "0": 0.05 },
  "order_types": {
    "entry": "market",
    "exit": "market",
    "force_entry": "market",
    "force_exit": "market",
    "emergency_exit": "market",
    "stoploss": "market",
    "stoploss_on_exchange": false
  },
  "entry_pricing": { "price_side": "other", "use_order_book": false },
  "exit_pricing": { "price_side": "other", "use_order_book": false },
  "pairlists": [{ "method": "StaticPairList" }]
}

Notes:

• stake_currency must appear in the configured markets. For AERO/USDC, use USDC.
• Use trading_min_order_amount only when the strategy needs an explicit minimum; the API pads Aerodrome configs to 1 when omitted.
• Do not include dry_run, initial_state, api_server, walletAddress, privateKey, wallet_address, or private_key.
• ccxt_async_config is usually unnecessary for Aerodrome authoring unless current API tests show otherwise.

Strategy Template

from freqtrade.strategy import IStrategy
import pandas as pd
import talib.abstract as ta


class AerodromeRsiStrategy(IStrategy):
    timeframe = "5m"
    process_only_new_candles = True
    startup_candle_count = 50
    minimal_roi = {"0": 0.05}
    stoploss = -0.10
    can_short = False

    def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
        dataframe["ema_50"] = ta.EMA(dataframe, timeperiod=50)
        return dataframe

    def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        dataframe.loc[
            (dataframe["volume"] > 0)
            & (dataframe["rsi"] < 35)
            & (dataframe["close"] > dataframe["ema_50"]),
            "enter_long",
        ] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        dataframe.loc[
            (dataframe["rsi"] > 65),
            "exit_long",
        ] = 1
        return dataframe

Rules for generated strategy code:

• Implement populate_indicators, populate_entry_trend, and populate_exit_trend.
• Use enter_long and exit_long only. Do not use enter_short.
• Do not do custom network calls from strategy hot paths.
• Do not rely on bid/ask spread, order-book imbalance, depth, or maker/taker limit placement.
• If using multi-output TA-Lib functions such as BBANDS, MACD, or STOCH, assign their returned columns explicitly.

Backtest Workflow

1. Build Aerodrome config and Freqtrade strategy code.
2. Check data availability with GET https://api.superior.trade/v2/backtesting-data/aerodrome?pair=AERO/USDC&timeframe=5m.
3. Create a backtest with POST https://api.superior.trade/v2/backtesting using { "config": {}, "code": "...", "timerange": { "start": "YYYY-MM-DD", "end": "YYYY-MM-DD" } }.
4. Start it with PUT https://api.superior.trade/v2/backtesting/{id}/status and { "action": "start" }.
5. Poll GET https://api.superior.trade/v2/backtesting/{id}/status until completed or failed.
6. Fetch GET https://api.superior.trade/v2/backtesting/{id} and inspect result_url for full metrics.
7. Present total trades, win rate, profit, drawdown, and whether results justify live testing.

Do not offer live deployment after a zero-trade backtest unless the user explicitly wants to debug live behavior.

Aerodrome API Quick Reference

Use SUPERIOR_TRADE_API_KEY from the environment. Do not paste API keys into commands, files, or logs.

Check data availability:

curl -sS --get "https://api.superior.trade/v2/backtesting-data/aerodrome" \
  --data-urlencode "pair=AERO/USDC" \
  --data-urlencode "timeframe=5m"

Expected success shape:

{
  "available": true,
  "pair": "AERO/USDC",
  "timeframe": "5m",
  "from": "ISO8601 when cataloged",
  "to": "ISO8601 when cataloged",
  "candles": 1234
}

If available is false or the response says data will be fetched live from Bitquery, it is still acceptable to create the backtest unless the user requested only pre-downloaded data.

Create the backtest:

curl -sS -X POST "https://api.superior.trade/v2/backtesting" \
  -H "content-type: application/json" \
  -H "x-api-key: ${SUPERIOR_TRADE_API_KEY}" \
  --data @aero-backtest.json

Create response:

{
  "id": "string",
  "status": "pending",
  "message": "Backtest created. Call PUT /:id/status with action \"start\" to begin."
}

Start the backtest:

curl -sS -X PUT "https://api.superior.trade/v2/backtesting/${BACKTEST_ID}/status" \
  -H "content-type: application/json" \
  -H "x-api-key: ${SUPERIOR_TRADE_API_KEY}" \
  --data '{"action":"start"}'

Poll status every 10 seconds until completed or failed:

curl -sS "https://api.superior.trade/v2/backtesting/${BACKTEST_ID}/status" \
  -H "x-api-key: ${SUPERIOR_TRADE_API_KEY}"

Fetch full details after completion:

curl -sS "https://api.superior.trade/v2/backtesting/${BACKTEST_ID}" \
  -H "x-api-key: ${SUPERIOR_TRADE_API_KEY}"

If failed, fetch logs:

curl -sS "https://api.superior.trade/v2/backtesting/${BACKTEST_ID}/logs?pageSize=100" \
  -H "x-api-key: ${SUPERIOR_TRADE_API_KEY}"

Cancel or delete a backtest:

curl -sS -X DELETE "https://api.superior.trade/v2/backtesting/${BACKTEST_ID}" \
  -H "x-api-key: ${SUPERIOR_TRADE_API_KEY}"

Status responses may include parsed results. Full details may include a signed resultUrl; download it for full Freqtrade metrics when present. Present at least total trades, win rate, total profit, max drawdown, and Sharpe ratio. If a backtest fails, summarize the relevant log lines and the likely fix.

AERO/USDC Backtest Payload

Use this as the default aero-backtest.json for a simple AERO strategy unless the user requested different risk, timeframe, timerange, or indicators.

{
  "config": {
    "exchange": {
      "name": "aerodrome",
      "pair_whitelist": ["AERO/USDC"],
      "ccxt_config": {
        "options": {
          "rpcUrl": "https://mainnet.base.org",
          "markets": [
            {
              "symbol": "AERO/USDC",
              "baseAddress": "0x940181a94A35A4569E4529A3CDfB74e38FD98631",
              "baseDecimals": 18,
              "quoteAddress": "0x833589fcd6edb6e08f4c7c32d4f71b54bda02913",
              "quoteDecimals": 6,
              "poolAddress": "0x6cdcb1c4a4d1c3c6d054b27ac5b77e89eafb971d",
              "stable": false
            },
            {
              "symbol": "CHECK/USDC",
              "baseAddress": "0x9126236476eFBA9Ad8aB77855c60eB5BF37586Eb",
              "baseDecimals": 18,
              "quoteAddress": "0x833589fcd6edb6e08f4c7c32d4f71b54bda02913",
              "quoteDecimals": 6,
              "poolAddress": "0x6a4BeFa1337865071E27c62dc9d7E3bCa253cE0f",
              "stable": false
            }
          ]
        }
      }
    },
    "stake_currency": "USDC",
    "stake_amount": 10,
    "max_open_trades": 1,
    "timeframe": "5m",
    "stoploss": -0.1,
    "minimal_roi": { "0": 0.05 },
    "order_types": {
      "entry": "market",
      "exit": "market",
      "force_entry": "market",
      "force_exit": "market",
      "emergency_exit": "market",
      "stoploss": "market",
      "stoploss_on_exchange": false
    },
    "entry_pricing": { "price_side": "other", "use_order_book": false },
    "exit_pricing": { "price_side": "other", "use_order_book": false },
    "pairlists": [{ "method": "StaticPairList" }]
  },
  "code": "from freqtrade.strategy import IStrategy\nimport pandas as pd\nimport talib.abstract as ta\n\n\nclass AeroRsiEmaStrategy(IStrategy):\n    timeframe = \"5m\"\n    process_only_new_candles = True\n    startup_candle_count = 50\n    minimal_roi = {\"0\": 0.05}\n    stoploss = -0.10\n    can_short = False\n\n    def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:\n        dataframe[\"rsi\"] = ta.RSI(dataframe, timeperiod=14)\n        dataframe[\"ema_50\"] = ta.EMA(dataframe, timeperiod=50)\n        return dataframe\n\n    def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:\n        dataframe.loc[\n            (dataframe[\"volume\"] > 0)\n            & (dataframe[\"rsi\"] < 35)\n            & (dataframe[\"close\"] > dataframe[\"ema_50\"]),\n            \"enter_long\",\n        ] = 1\n        return dataframe\n\n    def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:\n        dataframe.loc[\n            (dataframe[\"rsi\"] > 65),\n            \"exit_long\",\n        ] = 1\n        return dataframe\n",
  "timerange": {
    "start": "2026-03-01",
    "end": "2026-04-01"
  }
}

Before submitting a modified payload, re-check it against the non-negotiables: spot-only, no :USDC pair suffix, no private keys, no orderbook pricing, market order types, numeric stake amount, and supported Aerodrome market metadata.

Live Deployment Workflow

1. Create deployment with POST https://api.superior.trade/v2/deployment using Aerodrome config and strategy code.
2. Store or confirm credentials using the current API behavior:
   • Prefer the documented v2 flow when supported: POST https://api.superior.trade/v2/deployment/{id}/credentials with {"exchange":"aerodrome"}.
   • If the current API rejects Aerodrome on the v2 credentials route, inspect the local api/src/routes/credentials-v2.ts, api/src/routes/deployment.ts, and OpenAPI before proceeding. Do not ask the user for private keys unless the live API explicitly requires that legacy flow.
3. Run the pre-deployment checklist below.
4. Show a concise live trading summary and wait for explicit confirmation.
5. Start with PATCH https://api.superior.trade/v2/deployment/{id}/status and { "action": "start" }.
6. Monitor status and logs with GET https://api.superior.trade/v2/deployment/{id}/status and GET https://api.superior.trade/v2/deployment/{id}/logs.
7. Stop with PATCH https://api.superior.trade/v2/deployment/{id}/status and { "action": "stop" }.

Pre-Deployment Checklist

• Backtest completed and was reviewed.
• Config is Aerodrome spot-only and has no margin_mode, leverage, shorting, or :USDC pair suffix.
• entry_pricing.use_order_book and exit_pricing.use_order_book are false.
• stake_amount is numeric and fits wallet balances with gas/slippage buffer.
• Wallet has Base ETH for gas and enough relevant token balance for intended buys/sells.
• Strategy has no custom orderbook or RPC polling.
• User explicitly confirmed live trading.

Use this confirmation format:

Deployment Summary:
- Exchange: aerodrome on Base
- Trading mode: spot only
- Pair: [pair]
- Stake amount: [amount] [stake_currency] per trade
- Max open trades: [n]
- Stoploss: [percentage]
- Order execution: AMM market swaps, no orderbook
- Wallet balance checked: [yes/no, source]
- Base ETH gas checked: [yes/no, source]

This will trade with real funds. Proceed? (yes/no)

Troubleshooting

• Validation says Aerodrome only supports spot: remove trading_mode: "futures", trading_mode: "margin", and margin_mode.
• Validation says stake currency is not present in markets: align stake_currency with the quote or base token in exchange.ccxt_config.options.markets.
• Orderbook errors: remove use_order_book, order_book_top, depth checks, and strategy calls to self.dp.orderbook().
• Zero trades: check wallet token balance, ETH gas, numeric stake_amount, data availability, and overly restrictive entry conditions.
• Market buy requires price: keep Freqtrade market order config and avoid hand-calling CCXT without price; Aerodrome market buys need price context for cost calculation.
• Aerodrome swaps are atomic, so stopping the bot does not need a position-close cleanup routine.