ClawTrust
3.4k Downloads
Overview
Continuously scan Polymarket prediction markets to detect and rank executable arbitrage opportunities (primarily math/arbitrage across all outcomes), and provide structured outputs plus alerting to support manual or semi-automated trading strategies.
Key Advantages
1.Specialized for Polymarket math arbitrage with explicit handling of multi-outcome markets and taker fees.
2.Provides quantitative metrics per opportunity (net_profit_pct after fees, risk_score, volume, action) for quick filtering and decision-making.
3.Supports both one-off scans and continuous monitoring with configurable interval and minimum edge threshold.
4.Built-in state tracking and alert deduplication to avoid repeated notifications on the same arbitrage opportunity.
5.Opinionated, stepwise workflow (paper trading → micro testing → scaling → automation) with embedded risk-management guidelines (max position, min edge, daily loss limit).
Use Cases
- Scanning Polymarket once to get a current snapshot of available math arbitrage opportunities for manual review.
- Running a background monitoring process (e.g., every 5 minutes) to alert on newly-appearing arbitrage edges above a specified threshold.
- Paper-trading arbitrage strategies by logging detected opportunities and evaluating hypothetical P&L before committing real capital.
- Supporting a small manual arbitrage operation where a trader executes recommended buy-all-outcomes trades on Polymarket.
- Feeding structured arbitrage data (arbs.json) into a downstream custom tool or dashboard for deeper analysis or risk modeling.
Evaluation Scores
7.7
/ 10
Reliability
7.0
Functionality
8.0
Usability
8.5
Safety
7.0
Performance
7.5
Compatibility
8.5
Based on 1 evaluation · Latest: 3/19/2026
Download Trend
Loading...
Evaluation History (1)
7.7/103/19/2026▼
OS: darwin-x64LLM: google/gemini-2.5-flash-lite
**Quick judgment:** This skill is a focused, well-structured tool for *math arbitrage* on Polymarket, suitable for technically comfortable users who want to monitor and exploit probability mispricings across all outcomes. It is strong for detection and monitoring, but intentionally conservative about full automation and does not yet implement cross-market or orderbook-based arbitrage.
**Strengths:**
- Clear CLI workflow for both single-run scans and continuous monitoring (with alert deduplication).
- Outputs rich structured data (net edge after realistic fee assumptions, risk score, liquidity/volume, recommended action).
- Thoughtful trading guidance: phased rollout (paper → micro → scale), position sizing rules, fee-aware edge thresholds.
**Key limitations / risks:**
- **Data fragility:** Relies on scraping Polymarket’s homepage; any front-end or format change may silently break or degrade results.
- **Execution gap:** Results use homepage probabilities, which may not reflect executable orderbook prices; profitable-looking edges may already be gone or illiquid.
- **Scope limits:** Cross-market and orderbook arbitrage are described but not implemented; focus is predominantly on buy-side math arbs.
- **Financial risk:** Despite strong risk-management messaging, users still face real-money risk, latency risk, and possible overreliance on stale data.
**Recommended scenarios:**
- You want to **explore Polymarket arbitrage opportunities** and start with paper trading and small manual experiments.
- You need a **data feed of candidate math arbs** (JSON files) to plug into your own research, dashboards, or execution logic.
- You are comfortable with Python/CLI tools and want a **lightweight monitoring and alerting layer** before building more advanced automation.
**Less suitable when:**
- You require **high-frequency, execution-grade arbitrage** using direct orderbook data or websockets.
- You need **fully automated trading**, wallet/key management, or robust exchange API integration out of the box.
Comments (0)
No comments yet. Be the first!