An automated parameter tuning engine that analyzes trading performance and adjusts strategy thresholds to maximize prediction market returns.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install polymarket-optimizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install polymarket-optimizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Polymarket Optimizer?
Polymarket Optimizer is an adaptive tuning layer designed to sit atop the Polymarket execution ecosystem. It functions as a performance-driven feedback loop, reading real-time metrics and adjusting strategy parameters to ensure optimal capital efficiency. By leveraging Openclaw Skills, this tool removes the need for manual intervention by automatically tightening or loosening trading criteria based on recent win rates and total P&L.
Part of the Wesley Agent Ecosystem, this skill mirrors professional crypto-executor patterns. It focuses on evolving a learned configuration over time, allowing the agent to transition from conservative paper trading to aggressive live execution only when specific, data-driven performance benchmarks are met.
Polymarket Optimizer Use Cases
- Automating the adjustment of profit thresholds based on historical strategy win rates.
- Scaling capital allocation dynamically toward high-performing arbitrage opportunities.
- Reducing portfolio risk during drawdowns by adjusting Kelly fractions automatically.
- Validating live trading readiness through rigorous paper trade analysis and circuit breaker checks.
How Polymarket Optimizer Works
- The optimizer triggers every six hours via a cron job integrated with Openclaw Skills.
- It ingests performance data, paper trade records, and portfolio health metrics from the local workspace.
- Strategies are categorized based on win rate thresholds, ranging from Poor (below 50%) to Excellent (above 80%).
- Thresholds are adjusted: poor strategies require higher profit margins to trade, while excellent strategies have thresholds lowered to capture more volume.
- Capital allocations are renormalized across all active strategies to ensure the portfolio remains balanced.
- A live readiness assessment evaluates if the current performance justifies moving from paper to live production.
- Detailed logs and a Telegram notification are generated to summarize the optimization run.
Polymarket Optimizer Setup
Navigate to the skill directory within your environment and execute the primary Python script. To ensure continuous optimization using Openclaw Skills, it is recommended to schedule the script via cron.
cd /data/.openclaw/workspace/skills/polymarket-optimizer
python3 polymarket_optimizer.py
To automate this, add the following entry to your system crontab:
0 */6 * * * docker exec openclaw-container-name python3 /data/.openclaw/workspace/skills/polymarket-optimizer/polymarket_optimizer.py
Polymarket Optimizer Data Schema & Taxonomy
The skill manages several critical files to maintain the state of the optimization engine:
| File | Role | Description |
|---|---|---|
| performance_metrics.json | Input | Contains per-strategy win rates and trade counts. |
| portfolio.json | Input | Tracks current capital, positions, and daily returns. |
| learned_config.json | Output | The dynamic configuration file read by the executor for its next run. |
| optimizer_log.jsonl | Output | A comprehensive historical log of every adjustment made by the skill. |
Polymarket Optimizer Advanced Features
- Adaptive Scan Frequency: Automatically increases API scanning speed when strategies show high accuracy.
- Dynamic Kelly Fractioning: Scales position sizing up or down based on overall portfolio return health.
- Multi-Step Readiness Assessment: Requires 30+ resolved trades and a 55%+ win rate before recommending live deployment.
- Telegram Integration: Sends real-time optimization reports including P&L, adjustments made, and readiness status.
- Seamless Workspace Integration: Works natively with other Openclaw Skills to create a fully autonomous trading agent.
SKILL.md
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