polymarket-openclaw-trader
Reusable Polymarket + OpenClaw trading operations skill for any workspace. Use when the user needs to set up, run, tune, monitor, and deploy an automated Polymarket trading project (paper/live), including env configuration, risk controls, reporting, and dashboard operations.
About this skill
This skill provides a comprehensive framework for deploying and managing an automated trading bot on Polymarket, powered by OpenClaw. It guides the AI agent through the entire lifecycle, from initial environment setup and sensitive configuration management (e.g., private keys in `.env`) to launching the trading process, monitoring its activity, and deploying web-based control panels. Users can leverage this skill for paper trading to test strategies or for live trading after careful consideration of risk. The skill emphasizes robust operational practices, including secure handling of credentials, clear instructions for process initiation and health checks, and the ability to dynamically adjust strategy parameters. It also outlines critical reporting guidelines, ensuring that financial data is presented accurately, distinguishing between actual wallet balances and bot-specific ledger entries. Furthermore, it incorporates strict execution safeguards, such as pre-order checks for private keys, market validity, and risk thresholds, while explicitly handling geographical restrictions. This makes the `polymarket-openclaw-trader` skill invaluable for individuals or organizations looking to institutionalize their speculative or hedging operations on Polymarket. By abstracting away the complex setup and operational overhead, it allows users to focus on strategy development and performance, while ensuring that the underlying trading infrastructure adheres to best practices for security, reliability, and compliance.
Best use case
The primary use case is to establish and operate an automated trading system for Polymarket, enabling users to execute predefined strategies in a systematic and controlled manner. It specifically benefits users who wish to automate their market participation, whether for testing new trading ideas in a paper environment or for deploying live trading bots with integrated risk management and performance monitoring.
Reusable Polymarket + OpenClaw trading operations skill for any workspace. Use when the user needs to set up, run, tune, monitor, and deploy an automated Polymarket trading project (paper/live), including env configuration, risk controls, reporting, and dashboard operations.
A fully configured and actively running automated Polymarket trading bot, capable of executing strategies with defined risk controls, accessible via monitoring logs and an optional web dashboard.
Practical example
Example input
I want to deploy my Polymarket OpenClaw trading bot. Please configure it for paper trading, set my private key from a variable, and start the `cli_bot.py` process, then show me the logs.
Example output
Acknowledged. The Polymarket OpenClaw trading bot has been configured for paper mode and launched successfully. `nohup env PYTHONUNBUFFERED=1 python3 cli_bot.py loop > logs/runner_v2.log 2>&1 < /dev/null &` Process ID: 12345. Here are the last 10 lines from `logs/runner_v2.log`: ... (log output) ...
When to use this skill
- When you need to automate trading strategies on Polymarket, either for testing (paper mode) or live execution.
- To set up a robust, monitored, and risk-controlled trading bot environment with OpenClaw.
- If you require a structured way to configure sensitive trading parameters and deploy a web-based control panel.
- When an existing Polymarket project with `cli_bot.py` or `web_app.py` needs to be operated and managed.
When not to use this skill
- If you are not interested in automated trading or do not use Polymarket.
- For general-purpose programming tasks unrelated to trading or blockchain.
- When manual, discretionary trading is preferred over automated execution.
- If you are subject to geographical restrictions that prevent legal access to Polymarket.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/polymarket-openclaw-trader/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How polymarket-openclaw-trader Compares
| Feature / Agent | polymarket-openclaw-trader | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | medium | N/A |
Frequently Asked Questions
What does this skill do?
Reusable Polymarket + OpenClaw trading operations skill for any workspace. Use when the user needs to set up, run, tune, monitor, and deploy an automated Polymarket trading project (paper/live), including env configuration, risk controls, reporting, and dashboard operations.
How difficult is it to install?
The installation complexity is rated as medium. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Polymarket + OpenClaw 自动化交易(可发布通用版) ## 0) 前置条件(先检查) - Python 3.10+ - 可用的 Polymarket 项目目录(包含 `cli_bot.py` / `web_app.py`) - 具备合法可交易区域(否则会触发 geoblock) - 仅在用户明确授权时写入私钥 先确认项目路径(不要写死绝对路径): ```bash pwd ls -la ``` 如果用户没有给路径,询问并约定:`<PROJECT_DIR>`。 后续命令都基于: ```bash cd <PROJECT_DIR> ``` --- ## 1) 初始化配置(敏感信息只进 .env) 必须项: - `POLYMARKET_PRIVATE_KEY` - `POLYMARKET_WALLET_ADDRESS` - `EXECUTION_MODE=paper|live` - `AUTO_TRADE=true|false` - `LIVE_MAX_ORDERS_PER_DAY=<int>` 可选: - `POLYMARKET_FUNDER` - `DISCORD_WEBHOOK_URL` - `POLYMARKET_HOST` - `POLYMARKET_CHAIN_ID` - `POLYMARKET_SIGNATURE_TYPE` 要求: - 禁止把私钥写进代码或日志 - 对外回复时私钥只可显示“已配置/未配置”,不可回显原文 --- ## 2) 启停与巡检 启动: ```bash nohup env PYTHONUNBUFFERED=1 python3 cli_bot.py loop > logs/runner_v2.log 2>&1 < /dev/null & ``` 巡检: ```bash ps -ef | grep 'python3 cli_bot.py loop' | grep -v grep tail -n 120 logs/runner_v2.log ``` 若进程不在:自动重启并再次验证。 --- ## 3) 策略参数(非敏感,建议面板/运行时可调) 优先写入 `runtime/settings.json`: - `price_move_threshold_pct` - `volume_spike_multiple` - `signal_score_threshold` - `poll_interval_sec` - `status_every_minutes` 修改后重启策略进程。 --- ## 4) 汇报口径(必须真实) 汇报优先使用真实来源: - 真实持仓、持仓价值、浮动盈亏(钱包查询) - 机器人账本字段(如 `dailyPnlUsd/openMarkets`)要明确标注为“机器人账本” 禁止将估算余额伪装成真实账户余额。 --- ## 5) 下单执行规范 执行前依次检查: 1. 私钥已配置 2. 市场与 token id 可解析 3. 风控阈值通过 4. 执行下单 5. 返回完整结果(成功回执或失败原因) 若返回 geoblock / region restriction: - 立即停止交易尝试 - 明确告知合规限制 - 不提供绕过区域限制的方法 --- ## 6) Web 控制台与部署 本地: ```bash python3 web_app.py ``` Vercel: ```bash vercel --prod --yes ``` 若 Flask 入口报错,检查是否存在 `app.py` 且内容为: ```python from web_app import app ``` --- ## 7) 持久化与交付 每次关键变更后: 1. 更新项目记忆文件(若工作区有 MEMORY 体系) 2. `git add/commit` 提交 3. 若用户要求,打包 skill: ```bash python3 <skill_creator_scripts>/package_skill.py <skill_dir> <out_dir> ``` --- ## 8) 给最终用户的最小启动指令模板 ```bash cd <PROJECT_DIR> python3 -m venv .venv . .venv/bin/activate pip install -r requirements.txt cp .env.example .env # 填写必要环境变量后 nohup env PYTHONUNBUFFERED=1 python3 cli_bot.py loop > logs/runner_v2.log 2>&1 < /dev/null & ```
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