# Before you run a Polymarket bot, read this - URL: https://runtimenotes.com/blog/before-you-run-a-polymarket-bot/ - Published: 2026-02-03, updated 2026-02-17 - Tags: trading, prediction-markets, engineering - Summary: We reviewed hundreds of Polymarket bot repos, official SDKs and community tools. Most viral profit claims are fake or misleading. X is full of Polymarket bot success stories: - "I gave a bot $100 and it made $347 overnight." - "$900 per day exact formula." - "$75k in a month from market making." - "$500 to $800 daily from arbitrage alerts." We reviewed hundreds of Polymarket bot repositories (~860 on GitHub for "polymarket bot," ~3,500 Polymarket-related repos total), official SDKs, community tools and academic research. **Most of this is fake, misleading or affiliate marketing.** Most people who run automated bots on prediction markets lose money. --- ## The two biggest scams in Polymarket bot content ### 1. Viral profit claims Most viral bot posts are designed for engagement and referral fees, not profitability. If you see links with `?ref=` or `?via=` parameters, that's usually the real business model. > 70% of all Polymarket traders have realized losses. Only 0.04% of addresses captured over 70% of total profits. Survivorship bias makes this worse. The bots that survive have 85%+ win rates, but most attempts at running automated trading bots result in losses. The winners have custom infrastructure, significant capital and years of experience. Profitable traders usually have: - Years of market intuition - Significant starting capital - Custom infrastructure and low-latency execution - Ruthless risk management - Comfort with being wrong often There is no bot that reliably turns $100 into $347 overnight. Claims like these trace back to single unverified anecdotes, often involving general-purpose AI tools that aren't even trading bots. The [CFTC has explicitly warned](https://www.cftc.gov/LearnAndProtect/AdvisoriesAndArticles/AITradingBots.html) that claims of huge returns from AI trading bots are a hallmark of fraud. ### 2. Keyword-stuffed GitHub repos After reviewing hundreds of Polymarket repositories, the pattern is obvious. Many "popular" bots have descriptions like: > polymarket bot, polymarket trading bot, polymarket copy trading bot, polymarket arbitrage bot, polymarket trading bot… This is SEO spam, not documentation. Red flags: - Extremely high star counts - Almost no real explanation of strategy - Repeated keywords instead of real descriptions - Forks of forks with no meaningful changes Before running any third-party bot: 1. **Read every line of code** 2. **Check for hard-coded wallet addresses** 3. **Verify how API keys are used** 4. **Never give write access unless you fully understand it** If you can't explain what the code does, don't let it touch your money. --- ## How Polymarket actually works (and why this matters) Polymarket uses a central limit order book (CLOB). That means: - Limit orders, not just market orders - Visible bid/ask spreads - Order book depth is public - Markets resolve to $1.00 (YES) or $0.00 (NO) This matters because bots don't "predict outcomes." They: - Read order books - Manage inventory - React faster than humans - Execute predefined rules **Speed, execution quality and discipline matter more than "intelligence."** --- ## 5 bot strategies, from simple to dangerous ### 1. Copy trading **What it is:** Automatically mirrors trades from "smart money" wallets. **Why people like it:** It feels easy. Someone else does the thinking. **Why it fails:** - You enter later at worse prices - You don't know the trader's risk tolerance - Past performance doesn't persist - Position sizing rarely matches your bankroll **Reality:** Start with alerts. Don't auto-execute. ### 2. Arbitrage **What it is:** Buying mispriced YES/NO outcomes for guaranteed profit. **Example:** YES @ $0.48 + NO @ $0.49 = $0.97 cost → $1.00 payout. **Why people like it:** It seems "risk-free." **Why it fails:** - Opportunities last milliseconds - Fees and slippage erase gains - Liquidity is thin - Professionals get there first Claims of "$900/day arbitrage" for retail traders are not credible. ### 3. Market making **What it is:** Providing liquidity on both sides and earning the spread. **Why people like it:** It looks steady and systematic. **Why it fails:** - Informed traders trade against you - Inventory risk accumulates quickly - Requires constant rebalancing - Needs meaningful capital to matter This is hard even for professionals. ### 4. Sentiment-driven trading **What it is:** Using X (Twitter) sentiment to anticipate price movement. **How it works:** 1. Scan posts by keyword 2. Score sentiment 3. Compare against implied odds 4. Trade large divergences **Why it fails:** - Social media is noisy - Markets often price news faster than sentiment tools - Small sample sizes mislead Useful for alerts, not blind execution. ### 5. AI-assisted trading **What it actually is:** A self-hosted AI assistant, not a money printer. **What it can realistically do:** - Cross-market research - Sentiment divergence alerts - Liquidity monitoring - Trade journaling and post-mortems - Wallet tracking - Performance dashboards **What it cannot do:** - Guarantee profits - Replace judgment - Turn $100 into $347 overnight - Beat the market autonomously AI helps you think better. It doesn't think for you. --- ## The only path that doesn't end in a blow-up ### Step 1: Learn the API (no trading yet) Use the official SDK. Just read data. ```bash pip install py-clob-client ``` - Fetch market data, read order books, understand the data structures - Query historical trades and resolutions - Spend at least a week just reading data before writing any trading logic ### Step 2: Build analysis before execution Before placing a single trade: - Track your own manual trades with entry thesis and outcome - Monitor specific markets you're interested in - Set up alerts for price movements or unusual activity - Calculate your own calibration (how often your predictions are right) - Review this data weekly If you can't explain why you're winning or losing, automation will amplify mistakes. ### Step 3: Paper trade (minimum 4 weeks) - Log what you would have bought/sold - Track simulated P&L with realistic assumptions about slippage and fees - Run for a few days/weeks before using real money - Identify whether your strategy has an actual edge (>55% hit rate after costs) ### Step 4: Start small and conservative - Use an amount you're genuinely comfortable losing entirely - Set strict position sizing rules (e.g. never more than 2-5% of bankroll on one market) - Implement stop-losses or maximum loss limits in code - Log every trade with full reasoning - Review losses ### Step 5: Add automation gradually Don't go from 0 to fully autonomous overnight. 1. Manual trading with bot-generated alerts and analysis 2. Bot suggests trades, you approve each one manually 3. Bot executes within tight parameters (small size, high-confidence only) 4. Expand parameters slowly as you build confidence and data --- ## Risk rules every bot must have - Max position size - Daily loss limit - Liquidity thresholds - No leverage - Market time-to-resolution limits - Full audit logs - One-command kill switch - Weekly reviews (especially losses) **If your bot doesn't enforce discipline, it will enforce losses.** --- ## Official Polymarket repos If you're going to build, start from the source. These are maintained by Polymarket Engineering under [github.com/Polymarket](https://github.com/Polymarket). **CLOB clients:** | Language | Repository | |----------|-----------| | Python | [py-clob-client](https://github.com/Polymarket/py-clob-client) | | TypeScript | [clob-client](https://github.com/Polymarket/clob-client) | | Rust | [rs-clob-client](https://github.com/Polymarket/rs-clob-client) | **Order utilities:** | Language | Repository | |----------|-----------| | TypeScript | [clob-order-utils](https://github.com/Polymarket/clob-order-utils) | | Go | [go-order-utils](https://github.com/Polymarket/go-order-utils) | **Smart contracts:** - [ctf-exchange](https://github.com/Polymarket/ctf-exchange): core on-chain exchange contract - [neg-risk-ctf-adapter](https://github.com/Polymarket/neg-risk-ctf-adapter): negative risk adapter - [uma-ctf-adapter](https://github.com/Polymarket/uma-ctf-adapter): market resolution via UMA's Optimistic Oracle **Real-time data:** - [real-time-data-client](https://github.com/Polymarket/real-time-data-client): WebSocket feeds for live orderbook and trade updates **Examples:** - [examples](https://github.com/Polymarket/examples): runnable code for placing orders, fetching markets, etc. --- ## No shortcuts, just better tools Polymarket bots are tools, not cheat codes. The people making money from "bot strategies" on X are often selling referrals, farming engagement, or both. If you treat this as a learning project, you might build something useful. If you treat it as a get-rich-quick scheme, you will lose money. There are no shortcuts. Just better tools, slower decisions and honest accounting of what works.