Install
openclaw skills install polymarket-real-time-tradesReal-time streaming Polymarket prediction trades on Polygon (matic) with live USD pricing. Subscribe to a live stream of Polymarket prediction market trades over WebSocket: outcome trades (buyer, seller, amount, collateral in USD, price, order ID), market metadata (question title, resolution source, outcome labels), and transaction details — streamed in real time from the Bitquery GraphQL API. Covers all Polymarket markets including sports odds, Bitcoin Up or Down (and other crypto up/down markets), and general prediction markets.
openclaw skills install polymarket-real-time-tradesThis skill gives you a real-time streaming Polymarket prediction trade feed over WebSocket on Polygon (matic). Every event is a successful prediction trade with outcome token amounts, collateral in USD, price in USD, buyer/seller addresses, market question, outcome label (e.g. "Up" / "Down"), and transaction hash.
Trades are filtered to TransactionStatus.Success: true. The stream uses Bitquery's EVM.PredictionTrades subscription so downstream code can build dashboards, track order flow, or monitor specific markets.
Official docs: Polymarket API — Get Prices, Trades & Market Data (Bitquery).
This skill's code implements the described Polymarket stream and contacts only Bitquery. Before installing:
Required credential: This skill requires BITQUERY_API_KEY (your Bitquery API token). The registry metadata must declare this credential so installers are prompted to provide it. Verify the registry entry lists BITQUERY_API_KEY as a required environment variable.
⚠️ Critical security risk — Token in WebSocket URL: Bitquery's API does not support header-based auth or any method other than embedding the token in the WebSocket URL as ?token=.... This is an inherent design limitation of the API, not a bug in this skill. However, it creates a significant leakage risk:
Sandbox first: Before using this skill in production or in shared environments, test it in an isolated environment (virtualenv, container, or dedicated machine) to confirm the logging behavior and ensure the URL is not captured by system monitoring or logging tools you have enabled.
Source and publisher: Verify the publisher's identity and source control access. Review the code in scripts/stream_polymarket.py to confirm the script does not log the full URL before use.
Before running this skill, confirm:
BITQUERY_API_KEY in your environment: export BITQUERY_API_KEY=your_token_hereHISTFILE, .bash_history, system logs, IDE debug outputIf any of these cannot be confirmed, do not proceed with this skill until those conditions are met.
BITQUERY_API_KEY — your Bitquery API token (required).⚠️ URL-only authentication (Bitquery API limitation): Bitquery's streaming endpoint accepts the token only in the WebSocket URL as a query parameter (?token=...). It does not support header-based auth or Bearer tokens. This design choice means:
The token is embedded in the connection URL and will be present in memory, network traces, and any logs that capture the full URL
Never print, log, or emit the full WebSocket URL in any context
Always construct the URL from the environment variable and pass it only to the WebSocket transport
If the URL appears in shell history, logs, IDE debugger, or network monitoring, the token is compromised
Rotate your API key immediately if you suspect it was logged or captured
Run this script only in controlled environments where logging and monitoring are configured securely
Runtime: Python 3.8+ and pip. Install the dependency: pip install 'gql[websockets]'.
These are the key reasons a trader would use this feed:
1. Order flow / market activity Monitor every filled order: buyer, seller, collateral in USD, price in USD, and outcome (Yes/No or Up/Down). Identify which markets are most active and which side (buy vs sell) is dominant.
2. Whale / large-trade detection
Filter by CollateralAmountInUSD or Amount to surface large prediction-market trades. Useful for following smart-money flow into specific outcomes.
3. Market-specific monitoring
Use Question.MarketId, Question.Title, or Question.Id to filter the stream to a single market (e.g. "Ethereum Up or Down - March 10") and track all trades for that market in real time.
4. Outcome imbalance
Aggregate trades by Outcome.Label (e.g. "Up" vs "Down") and IsOutcomeBuy to see net buying pressure per outcome — useful for sentiment or momentum.
5. Resolution source / data markets
Use Question.ResolutionSource and Question.Title to focus on data or oracle-driven markets (e.g. Chainlink streams) and monitor trading around resolution.
6. Entry / exit timing
Stream PriceInUSD and CollateralAmountInUSD per trade to see where size is trading and at what price — helps time entries and exits in prediction markets.
7. Protocol / marketplace verification
Marketplace.ProtocolName and ProtocolFamily (e.g. "polymarket", "Gnosis_CTF") confirm the trade is from Polymarket on Polygon; use to avoid mixing with other protocols.
8. Audit trail
Each event includes Transaction.Hash, Block.Time, Call.Signature.Name (e.g. "matchOrders"), and Log.Signature.Name (e.g. "OrderFilled") for full on-chain audit.
import os
api_key = os.getenv("BITQUERY_API_KEY")
if not api_key:
print("ERROR: BITQUERY_API_KEY environment variable is not set.")
print("Run: export BITQUERY_API_KEY=your_token")
exit(1)
If the key is missing, tell the user and stop. Do not proceed without it.
Install the WebSocket dependency once:
pip install 'gql[websockets]'
Use the streaming script:
python ~/.openclaw/skills/polymarket-prediction-trades/scripts/stream_polymarket.py
Optional: stop after N seconds:
python ~/.openclaw/skills/polymarket-prediction-trades/scripts/stream_polymarket.py --timeout 60
Or subscribe inline with Python:
import asyncio, os
from gql import Client, gql
from gql.transport.websockets import WebsocketsTransport
async def main():
token = os.environ["BITQUERY_API_KEY"]
url = f"wss://streaming.bitquery.io/graphql?token={token}"
transport = WebsocketsTransport(
url=url,
headers={"Sec-WebSocket-Protocol": "graphql-ws"},
)
async with Client(transport=transport) as session:
sub = gql("""
subscription MyQuery {
EVM(network: matic) {
PredictionTrades(where: { TransactionStatus: { Success: true } }) {
Block { Time }
Call { Signature { Name } }
Log { Signature { Name } SmartContract }
Trade {
OutcomeTrade {
Buyer
Seller
Amount
CollateralAmount
CollateralAmountInUSD
OrderId
Price
PriceInUSD
IsOutcomeBuy
}
Prediction {
CollateralToken { Name Symbol SmartContract AssetId }
ConditionId
OutcomeToken { Name Symbol SmartContract AssetId }
Marketplace { SmartContract ProtocolVersion ProtocolName ProtocolFamily }
Question { Title ResolutionSource Image MarketId Id CreatedAt }
Outcome { Id Index Label }
}
}
Transaction { From Hash }
}
}
}
""")
async for result in session.subscribe(sub):
for trade in (result.get("EVM") or {}).get("PredictionTrades") or []:
q = (trade.get("Trade") or {}).get("Prediction") or {}
q = q.get("Question") or {}
ot = (trade.get("Trade") or {}).get("OutcomeTrade") or {}
pred = (trade.get("Trade") or {}).get("Prediction") or {}
outcome = pred.get("Outcome") or {}
print(
f"{q.get('Title', '?')} | "
f"Outcome: {outcome.get('Label', '?')} | "
f"${float(ot.get('CollateralAmountInUSD') or 0):.2f}"
)
asyncio.run(main())
| Field | What it means for traders |
|---|---|
Trade.OutcomeTrade.Buyer | Taker buyer address |
Trade.OutcomeTrade.Seller | Maker seller address |
Trade.OutcomeTrade.Amount | Outcome token amount (raw) |
Trade.OutcomeTrade.CollateralAmount | Collateral token amount |
Trade.OutcomeTrade.CollateralAmountInUSD | Notional in USD — use for size/whale filter |
Trade.OutcomeTrade.OrderId | Order identifier |
Trade.OutcomeTrade.Price | Price in collateral (0–1 typical for binary) |
Trade.OutcomeTrade.PriceInUSD | Price in USD — entry/exit reference |
Trade.OutcomeTrade.IsOutcomeBuy | True = buyer bought the outcome (Yes/Up) |
Trade.Prediction.Question.Title | Market question (e.g. "Ethereum Up or Down - ...") |
Trade.Prediction.Question.MarketId | Market ID for filtering |
Trade.Prediction.Question.ResolutionSource | Resolution source (e.g. Chainlink URL) |
Trade.Prediction.Outcome.Label | Outcome label (e.g. "Up", "Down") |
Trade.Prediction.Marketplace.ProtocolName | e.g. "polymarket" |
Block.Time | Trade timestamp (ISO) |
Transaction.Hash | On-chain tx hash for audit |
Call.Signature.Name | e.g. "matchOrders" |
Log.Signature.Name | e.g. "OrderFilled" |
When presenting prediction trades to a trader, use this layout:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Polymarket [matic] Protocol: polymarket (Gnosis_CTF)
Time: 2026-03-10T13:21:11Z Tx: 0x9566...f2da
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Question: Ethereum Up or Down - March 10, 9:15AM-9:30AM ET
MarketId: 1537455 | Outcome: Down (Index 1)
Resolution: https://data.chain.link/streams/eth-usd
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OutcomeTrade
Side: BUY outcome (IsOutcomeBuy: true)
Buyer: 0x22dc...91bb → Seller: 0x86a2...73a8
Collateral: 0.316471 USDC (USD: $0.32)
Price: 0.632942 (USD: $0.633)
Amount: 500000 (outcome tokens)
OrderId: 44433632...
Call: matchOrders | Log: OrderFilled @ 0x4bfb...982e
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
?token= only — do not pass the token in headers)TransactionStatus: { Success: true } and network is maticreferences/graphql-fields.md. Use it to add filters or request extra fields (e.g. by MarketId, ConditionId, or date) in the subscription.