Author: Changan I Biteye Content Team
When was the last time you watched the market closely until what time?
The longest I've done so was from the opening of the U.S. stock market until the Asian market closed, and I slept for two hours in between, only to wake up and realize I missed a perfect entry point.
I started to ponder: why does this have to be done by a person?
After OpenClaw integrated with Hyperliquid and Polymarket, I tested the answer to this question. Some things went more smoothly than expected, while some pitfalls were deeper than anticipated. This article covers it all.
Because I had been caught in the rain before, Biteye also wants to hold an umbrella for you.
1. Installation Steps
If you want AI to trade for you, simply installing OpenClaw is not enough. Its main function is to coordinate; the actual trading is executed by skills, and for skills to run, you need to provide them with the corresponding trading permissions.
This chapter clarifies three tasks: installation, configuration, and push notifications. Once configured, you can directly enter the practical part in the next chapter.
1.1 Install Skill: Find the Abilities You Need
You can search for and install the required skill keywords at ClawHub for any tasks you want to complete, for example:
hyperliquid skill
polymarket skill
After installation, confirm that the skill has been loaded by accessing the local console page: Left proxy bar → Click skill
If you can see the skill you just installed, it indicates that the installation was successful.
At this time, some skills may display "Save key," indicating that further configuration of the API or private key is needed, which is normal; the next step requires filling in the corresponding permission information.
1.2 Configure Trading API: Grant AI Order Permission
To allow AI to place orders, you must give it trading permissions.
Do not use the main account directly; it is recommended to create a separate new account for testing with a small amount of funds.
The method for acquiring permissions varies by exchange. Here are two examples.
1️⃣Hyperliquid
Open Hyperliquid → More → API
Here you can generate an API wallet that has trading permission but no withdrawal permission.
Enter wallet name → Click Generate to obtain the API key, and you can customize the authorization duration.
After generating the API wallet, from bitter experience, I can tell you: do not transfer any funds to the API wallet address; keep the funds in the main account. (Funds transferred to the API wallet will be lost)
During configuration, you need to fill in two pieces of information: the wallet address of the main account (API Key) and the private key displayed when generating the API wallet (API Secret). AI operates with the funds in the main account, signed through the API wallet.
Testing method: let OpenClaw query the account balance, and enter in the dialog: "Check my current balance in Hyperliquid."
If a specific number can be returned, the API configuration is normal.
2️⃣Polymarket
Open Polymarket settings page:
Settings → Relayer API Keys → API key → Click Create New
After creation, you will obtain:
RELAYER_API_KEY
RELAYER_API_KEY_ADDRESS
Signer Address
If you need to trade, you also need to export the signer corresponding wallet's private key and fill it into the configuration.
Here, I will demonstrate using the OKX wallet: Click the profile icon in the upper left corner of the wallet → Manage Wallet → View Private Key
Then fill the private key and API key together into OpenClaw's openclaw.json file. Next, open openclaw.json (the path is usually C:\Users\YourUsername\.openclaw\), and fill in three pieces of data in the env field.
⚠️ The private key is the highest permission credential; do not screenshot it, do not share it with anyone, and do not store it in chat records.
After configuring the API, you also need to complete an on-chain authorization. The simplest method is to make a manual trade on Polymarket, for example, buying a 1 USDC position.
1.3 Integrate with Telegram: Use It While On the Go
After configuring the API, the little lobster can already trade, but you can't just keep staring at your computer screen, can you?
Once integrated with Telegram, whether it's trade notifications, error messages, or temporarily wanting to place an order, you can simply pull out your phone and handle it. You can go out to eat, lie in bed before sleep, and the little lobster will do what it needs to do while you know exactly what it's doing.
Create Telegram bot:
Open Telegram
Search for BotFather
Create a Telegram bot: Send /start → /newbot → Follow the prompts to create the bot → After creation, you will receive the BOT Token
Obtain Chat ID: Send a message to the bot, then open: https://api.telegram.org/bot (your token, replace this part)/getUpdates
In the returned JSON, find chat → id; that string of numbers is your Chat ID.
Then fill in the two parameters in the configuration:
TELEGRAM_BOT_TOKEN
TELEGRAM_CHAT_ID
Then test: send me a test message
If Telegram can receive it, the push was successful.
If you cannot receive it, common reasons include proxy or network issues; you need to fill in the HTTPS proxy port in the configuration.
Open the openclaw.json file and add:
{
"HTTPS_PROXY": "http://127.0.0.1:your port",
"HTTP_PROXY": "http://127.0.0.1:your port"
}
Fill in the port based on your own proxy software.
2. Execute Orders: Turning Judgments into Action (More Detail)
Since AlphaGo's battle against the Korean Go player Lee Sedol, humanity has been particularly keen on competing with AI.
Last October, an AI research organization called Nof1 held a competition called Alpha Arena. The rules were simple: give models on the market $10,000 in funds and let them trade perpetual contracts autonomously on Hyperliquid, whoever has the highest account balance at the end wins.
Recently, Aster also held two live trading competitions of "Human vs AI," and unexpectedly, both competitions ended with AI victories.
After watching this, I began to think: can I also set up a similar pathway to run OpenClaw on Hyperliquid?
Thus, the following two skills were created.
2.1 Hyperliquid: Let AI Open Contracts
I searched in ClawHub and found the corresponding skill; the installation method can be referred to in the previous deployment tutorial.
After configuration, you can directly place orders using natural language: "Long ETH on Hyperliquid, 10x leverage, position 30%."
But in practice, it wasn't that smooth.
The first problem was leverage. When I instructed it to open 10x, it opened 20x instead, and it couldn't get it right even after repeated adjustments. The phrase "10x leverage" is ambiguous for AI; it adjusts based on its own judgment of "reasonable leverage." Later, I changed to a clearer command, prompting it to display specific parameters before placing an order, confirm, and then execute, which stabilized the process.
The second problem was position proportion: when I said "use 30% of the balance," it either ended up with a full position or opened an absurdly small position. Eventually, I directly instructed it with a specific amount, like "open a position of 200 USDC," which resolved the issue.
My initial goal was to replicate the Alpha Arena model: let OpenClaw run fully automatically like those AI models, 24 hours a day, without needing to monitor it.
In theory, this is feasible, but first, I need to articulate the strategy in natural language to share with OpenClaw: what asset, under what conditions to enter, how much position, where to set stop loss, and under what circumstances to close the position. After understanding this, it will continuously monitor and execute based on this logic, eliminating the need for you to trigger each action manually.
However, at this stage, the immaturity of the skill ecosystem presents a real challenge. No matter how good the strategy you feed in, if execution has issues, the result will deviate, just like AI models in Arena running on the native environment of Hyperliquid versus indirectly calling through third-party skills; their stability is not in the same league.
This section will be revisited once the skill ecosystem matures.
2.2 Polymarket: Transfer the Same Logic to the Prediction Market
After spending some time navigating Hyperliquid, I became curious: how would OpenClaw perform in the prediction market?
The underlying logic of the two markets is quite similar; both are pricing the "probability of something happening." The information sources are the same, and the judgment frameworks are roughly similar, only the execution locations differ.
In the previous article, I used PolyClaw to analyze the market but didn't actually place orders. There is a psychological barrier between analysis and placing orders; when analysis is wrong, there is no loss, but making a wrong order means real money is at stake. However, this time I want to take a step forward.
So, after filling out the three keys following the configuration process in the first chapter and completing the on-chain authorization, I asked OpenClaw to help find a worthy entry opportunity.
It suggested a market: "Will the Federal Reserve's interest rate remain unchanged after the March meeting?" The current YES price is $0.99, with a 24-hour trading volume of $2.4M, and market consensus indicates that 99% believe it will remain unchanged. The fundamentals support this judgment: inflation data is stable, economic growth is moderate, and the Federal Reserve's recent stance is dovish without urgency to cut interest rates.
Before placing an order, I usually ask: "What is the current order book depth in this market? What is the spread? How much is suitable to buy?"
OpenClaw will analyze the current buy-sell price difference; when the spread is too large, placing a limit order can save a lot of unnecessary loss.
After confirming that the depth is satisfactory, I simply instruct OpenClaw whether to buy and how much to buy to place the order: "Buy a position of 5 USDC in YES."
After the trade is completed, checking the position is also straightforward: "OpenClaw, what positions do I currently hold?"
From discovering the opportunity to completing the order, the entire process is carried out within OpenClaw, without the need to switch pages, nor putting up with the often sluggish front end of Polymarket.
3. Conclusion
The AI models in Alpha Arena run on Hyperliquid with $10,000, operating without sleep, without emotions, and not getting thrown off rhythm by losing a single trade.
In the past, this infrastructure was only accessible to professionals with technical backgrounds, but now OpenClaw has lowered the barrier to a level where ordinary people can enter. You don’t need to know how to write code, nor do you need to build a system yourself; a natural language directive is all it takes for AI to execute on your behalf.
The tools are already here.
The only remaining question is: when do you plan to start?
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