A professional-grade market analysis tool that identifies structural inefficiencies in Polymarket order books to generate high-alpha trading signals.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dolph-clob-microstructure
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 dolph-clob-microstructure 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 CLOB Microstructure Scanner?
The CLOB Microstructure Scanner is a specialized automaton designed to extract structural alpha from Polymarket order book data. By interfacing directly with the CLOB API, it performs a granular analysis of liquidity gaps and order book imbalances that are often invisible to the average trader. As a key entry in the Openclaw Skills ecosystem, it provides a sophisticated framework for identifying market manipulation and organic price movements.
This skill is engineered for developers and quantitative traders who require deep insights into market depth. It systematically scores markets based on physical logic and liquidity constraints, allowing for a data-driven approach to prediction market trading. By focusing on microstructure rather than just price action, it offers a distinct edge in detecting fake breakouts and whale activity.
CLOB Microstructure Scanner Use Cases
- Detecting fake breakouts on thin volume to execute mean-reversion strategies.
- Monitoring order book imbalances to predict short-term price direction.
- Identifying liquidity gaps where price slippage is likely to occur.
- Quantifying whale activity relative to total book depth for risk assessment.
How CLOB Microstructure Scanner Works
- The skill connects to the Polymarket CLOB API to pull real-time, raw order book data.
- It processes the data through four specific microstructure dimensions: Liquidity Gaps, Imbalance, Whale Activity, and Breakout Detection.
- Each dimension is assigned a score from 0-25, aggregating into a total market inefficiency score of 0-100.
- Based on the aggregate score, the engine generates one of four actionable signals (ENTRY_OK, REDUCE_SIZE, SKIP, or MEAN_REVERT).
- If a MEAN_REVERT signal is triggered and live mode is active, the bot executes a trade via SimmerClient to fade the move.
CLOB Microstructure Scanner Setup
To integrate this into your local environment, ensure you have your credentials configured.
# Export your Simmer API Key
export SIMMER_API_KEY='your_api_key_here'
# Run a dry run to verify scoring logic
python clob_microstructure.py
# Execute with live trading enabled
python clob_microstructure.py --live
CLOB Microstructure Scanner Data Schema & Taxonomy
The skill organizes microstructure data into a weighted scoring matrix to ensure consistent evaluation across different markets.
| Dimension | Metric | Score Range |
|---|---|---|
| Liquidity Gaps | Thin price zones | 0-25 |
| Order Imbalance | Bid/Ask weight asymmetry | 0-25 |
| Whale Activity | Large order relative to depth | 0-25 |
| Fake Breakout | Volume vs. Price delta | 0-25 |
All signals and scores are outputted to the console, and execution logs are maintained for auditability within the Openclaw Skills framework.
CLOB Microstructure Scanner Advanced Features
- Modular scoring system: Easily fork the skill to adjust weights or inject custom technical indicators.
- Dry-run safety gate: Test complex strategies without risking capital by default.
- Cron-ready CLI: Built-in quiet mode for seamless integration into automated DevOps pipelines.
- SimmerClient Integration: Native support for fading moves via high-fidelity execution protocols.
SKILL.md
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