polymarket-user-analyzer_skill

This skill analyzes Polymarket user strategies by username or wallet, generating comprehensive reports on trades, patterns, and profitability for actionable

Python

2.6k

GitHub Stars

3

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill polymarket-user-analyzer

_meta.json304 B
README.md2.4 KB
SKILL.md4.2 KB

Overview

This skill analyzes Polymarket user trading strategies from a username or wallet address and produces a structured performance report. It extracts the on-chain wallet, fetches trading history from the Polymarket Data API, and summarizes behavior with actionable metrics. Reports include win rate, market preferences, position sizing, entry price patterns, and profitability metrics.

How this skill works

Given a username or wallet address, the analyzer scrapes the public profile to resolve the wallet then queries Polymarket Data API for activity records. It normalizes trade and redeem events, computes statistics (P&L, ROI, win rate, average entry, time-of-day patterns), and classifies strategy types (momentum, value, scalper, etc.). The tool outputs a clear, shareable report and highlightable insights based solely on public on-chain data.

When to use it

Assess a trader's historical performance before following or copying their trades
Research market participant behavior and sentiment across market categories
Validate claimed trading results for due diligence or reporting
Identify recurring entry/exit patterns for strategy development
Monitor a specific wallet's activity for research or competitive analysis

Best practices

Provide either the exact username or the wallet address for faster resolution
Interpret win rate and redeems cautiously; redeems do not always mean profitable outcomes
Combine this analysis with on-market context (resolutions, liquidity, news) for stronger insights
Limit expectations: historical on-chain trades exclude off-chain signals, gas, and slippage
Request multiple time windows (recent vs full history) to understand regime changes

Example use cases

Generate a report on a public trader to decide whether to mirror their strategy
Compare market focus across traders to spot underexploited niches (crypto vs politics)
Extract position sizing habits to help build a risk management template
Audit a claimed performance by checking on-chain trades and computed ROI
Aggregate time-of-day and entry price distributions to discover momentum patterns

FAQ

No. It only uses publicly available on-chain activity and does not require authentication.

Can it guarantee a trader's future performance?

No. It analyzes historical behavior and metrics but cannot predict future results or off-chain decisions.

Are gas fees and slippage included in profitability?

No. Profitability metrics are based on on-chain trade values and do not account for gas or slippage unless explicitly provided.