What is user-activity?

This Claude skill enables the automated extraction and analysis of trading activity from Polymarket, a leading decentralized prediction market. By interfacing with the Polymarket Data API, it allows users to retrieve comprehensive transaction histories, calculate trading volumes, and identify strategic patterns for any specific wallet address or username, facilitating data-driven insights into market behavior.

When should I use user-activity?

user-activity is useful in the following scenarios: • Trader Strategy Analysis: Evaluate the historical performance, entry/exit points, and directional bias of top-performing traders to refine your own market approach. • Whale Tracking: Monitor high-volume accounts to detect significant capital shifts and sentiment changes in political, economic, or crypto-related prediction markets. • Financial Reporting and Auditing: Export detailed trading logs to CSV or JSON formats for personal portfolio tracking, tax compliance, or third-party auditing. • Market Sentiment Research: Analyze the distribution of 'Up' vs 'Down' positions across specific event slugs to gauge the conviction level of market participants.

name	user-activity
description	Pull trading activity from Polymarket for any user
when_to_use	When you need to analyze a Polymarket user's trading history, strategy, or patterns
script	scripts/polymarket-user-activity.py

Polymarket User Activity Scraper

Pull trading activity from Polymarket's Data API for any user by username or wallet address.

Quick Start

# Analyze gabagool22's last 7 days of trading
python scripts/polymarket-user-activity.py gabagool22 --analyze

# Save to CSV
python scripts/polymarket-user-activity.py gabagool22 --days 7 --output data/gabagool22-trades.csv

# Save as JSON
python scripts/polymarket-user-activity.py gabagool22 --days 7 --output data/gabagool22-trades.json

# Use wallet address directly
python scripts/polymarket-user-activity.py 0x6031b6eed1c97e853c6e0f03ad3ce3529351f96d --analyze

Options

Option	Description	Default
`user`	Username (e.g. gabagool22) or wallet address (0x...)	Required
`--days N`	Number of days of history to fetch	7
`--limit N`	Maximum number of trades to fetch	10000
`--output PATH`	Output file (CSV or JSON based on extension)	None
`--analyze`	Print analysis summary	False
`--json`	Output raw JSON to stdout	False

Output Fields (CSV)

Field	Description
datetime	ISO timestamp
timestamp	Unix timestamp
side	BUY or SELL
outcome	Up or Down
title	Market question
size	Number of shares
price	Price per share
value	size * price
slug	Market URL slug
eventSlug	Event identifier
conditionId	Market condition hash
transactionHash	On-chain tx hash
proxyWallet	Trader wallet

Analysis Summary

The --analyze flag prints:

Total trade count (BUY/SELL breakdown)
Total volume in USD
Date range covered
Up/Down position breakdown
Price statistics (avg/min/max)
Top 5 markets by trade count

Example Analysis Output

============================================================
TRADE ANALYSIS SUMMARY
============================================================

Total trades: 847
  - BUY: 623
  - SELL: 224

Total volume: $42,350.00

Date range: 2024-12-08 09:15 to 2024-12-15 14:30
  (7 days)

Outcome breakdown:
  - UP positions: 412
  - DOWN positions: 435

Price stats:
  - Average: $0.485
  - Min: $0.08
  - Max: $0.92

Top 5 markets by trade count:
  - Bitcoin up or down? (Dec 15, 2:00 PM ET)... (45 trades, $1,250.00)
  - Ethereum up or down? (Dec 15, 10:00 AM ET)... (38 trades, $980.00)
  ...
============================================================

API Details

Uses the Polymarket Data API:

Base URL: https://data-api.polymarket.com
Endpoint: /trades?user={wallet}&limit={n}&offset={n}
Rate limited: 0.5s delay between paginated requests

Strategy Analysis Tips

To analyze a trader's strategy:

Pull their recent trades:

python scripts/polymarket-user-activity.py gabagool22 --days 7 --output data/trades.csv

Look for patterns:
- Average position size
- Entry price ranges (do they buy near 0.50 or closer to extremes?)
- How often they add to positions vs close them
- Time patterns (when do they trade most actively?)
- Up/Down bias (do they favor one direction?)
Compare to market conditions:
- Do they trade more during high volatility?
- How do they handle losing positions?

user-activity

When & Why to Use This Skill

Use Cases