Polymarket Wallet Xray

Polymarket Wallet X-Ray

Analyze any Polymarket wallet's trading patterns, skill level, and edge detection.

No authentication needed. Queries Polymarket's public Data API v2 directly.

Inspired by: The Autopsy: How to Read the Mind of a Polymarket Whale by @thejayden

Read-only research. Public analysis reads wallet activity; the optional status helper reads your own Simmer account. Read DISCLAIMER.md before interpreting results.

This skill implements the forensic trading analysis framework developed by @thejayden. Read the original post to understand the philosophy behind Time Profitable, hedge checks, bot detection, and accumulation signals.

This is an analysis tool, not a trading signal. The skill returns forensic metrics for ANY Polymarket wallet — your agent uses them to UNDERSTAND traders, learn patterns, and make informed decisions. This is for education and research, not for blindly copying positions.

⚠️ Important Disclaimer

Past performance does not guarantee future results. A wallet's historical metrics tell you about:

• ✅ How they traded in the past
• ✅ Their historical win rate and entry quality
• ❌ NOT whether their strategy will work going forward

Why copying is risky:

• Market conditions change constantly
• A trader's edge might have been luck, timing, or specific to historical events
• Slippage and fees erode thin edges to zero
• Other traders copying the same strategy destroy the edge

Use this skill to:

• ✅ Learn what skilled traders look like (metrics, behavior)
• ✅ Identify potential anomalies (bots, arbitrageurs)
• ✅ Understand trader psychology (FOMO vs. discipline)
• ✅ Inform your own strategy decisions

DO NOT use this skill to:

• ❌ Automatically copytrade wallets
• ❌ Expect to replicate their returns
• ❌ Trade on these metrics without understanding why
• ❌ Risk significant capital on patterns you don't understand

Setup Flow

Public wallet analysis requires only Python's standard library. No package install, SDK, API key, or wallet connection is needed. Run wallet_xray.py with a public Polymarket wallet address.

Only if the user explicitly asks for their own Simmer account status, use scripts/status.py. SIMMER_API_KEY is optional for this skill and used only by that helper. Have the user configure it in their environment outside chat, using the SDK tab at https://simmer.markets/dashboard. Never ask them to paste a key into chat or print it.

The status helper sends the key as a Bearer header only to https://api.simmer.markets for read-only portfolio and position queries. It exits before making a request when the key is unset. Neither script places orders or changes account settings.

Quick Commands

All shortened 0x... addresses below are placeholders. Replace them with complete public wallet addresses before running a command.

bashCopy code
# Analyze a single wallet
python wallet_xray.py 0x1234...abcd

# Compare two wallets head-to-head
python wallet_xray.py 0x1111... 0x2222... --compare

# Optional: read your own Simmer account status (requires SIMMER_API_KEY)
python scripts/status.py

APIs Used:

• Data API v2: https://data-api.polymarket.com/v2/activity — Wallet activity (cursor-paginated)
• Simmer API: https://api.simmer.markets — Optional authenticated account status via scripts/status.py

What You Get Back

Illustrative report excerpt (values and wallet address are placeholders):

jsonCopy code
{
  "wallet": "0x1234...abcd",
  "total_trades": 156,
  "total_period_hours": 42.5,
  "profitability": {
    "time_profitable_pct": 75.3,
    "win_rate_pct": 68.2,
    "avg_profit_per_win": 0.035,
    "avg_loss_per_loss": -0.018,
    "realized_pnl_usd": 2450.00
  },
  "entry_quality": {
    "avg_slippage_bps": 28,
    "quality_rating": "B+",
    "assessment": "Good entries, occasional FOMO"
  },
  "behavior": {
    "is_bot_detected": false,
    "trading_intensity": "high",
    "avg_seconds_between_trades": 45,
    "price_chasing": "moderate",
    "accumulation_signal": "growing"
  },
  "edge_detection": {
    "hedge_check_combined_avg": 0.98,
    "has_arbitrage_edge": false,
    "assessment": "No locked-in edge; relies on direction"
  },
  "risk_profile": {
    "max_drawdown_pct": 12.5,
    "volatility": "medium",
    "max_position_concentration": 0.22
  },
  "recommendation": "Good trader. Positive historical metrics; research only, not a signal to copy or size positions."
}

How It Works

1. Fetch trade history — Download wallet activity from Data API v2, following cursors up to the requested limit
2. Compute profitability timeline — When were they underwater vs. profitable?
3. Analyze entry quality — Did they buy at optimal prices or chase?
4. Detect trading patterns — Bot (inhuman speed) vs. human (deliberate timing)?
5. Check for arbitrage — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)
6. Assess behavior — FOMO accumulation? Disciplined sizing? Rotating positions?
7. Summarize historical metrics — Which patterns merit further research? What are the data limitations?

Understanding the Metrics

⏱️ Time Profitable (e.g., 75.3%)

Wallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.

• >80% = Sniper-like (skilled entries, holds through drawdowns)
• 50-80% = Solid (good discipline)
• <50% = Risky (likely panic-held losses)

🎯 Entry Quality (e.g., 28 bps average slippage)

They buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.

• <20 bps = Expert. Limit orders, patience.
• 20-40 bps = Good. Balanced speed/price.
• >50 bps = Weak. Chasing prices.

🤖 Bot Detection (e.g., false)

Average 45 seconds between trades. This is human. A bot would be <1 second.

• <5 sec = Likely bot. Avoid unless you know it's a legitimate market maker.
• 5-30 sec = Possible bot.
• >30 sec = Human.

💰 Hedge Check (e.g., combined avg 0.98)

If they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.

If combined < $1.00, they may have entered with a structural edge (lower combined cost than $1 payout). Actual profit depends on execution, fees, and spread.

• < $0.95 = Strong potential edge. Likely institutional/pro.
• $0.95-1.00 = Slight edge detected.
• > $1.00 = No edge; betting on direction.

Usage Examples

Research one wallet

bashCopy code
python wallet_xray.py 0x1234...abcd --json

Review profitability, entry_quality, behavior, and risk_profile to describe historical patterns. The recommendation field summarizes a heuristic rating tier, not a trading or allocation recommendation. Test hypotheses against fresh data and consider fees, sample size, and missing activity.

Compare historical profiles

bashCopy code
python wallet_xray.py 0x1111... 0x2222... --compare --json --limit 100

Compare the two reports for differences in historical entries, drawdowns, and activity. Strong historical metrics do not establish future returns or justify copying or sizing positions.

Running the Skill

Analyze a single wallet (default):

bashCopy code
python wallet_xray.py 0x1234...abcd

Output as JSON (for scripts):

bashCopy code
python wallet_xray.py 0x1234...abcd --json

Compare two wallets:

bashCopy code
python wallet_xray.py 0x1111... 0x2222... --compare

Limit analysis to recent trades (faster):

bashCopy code
python wallet_xray.py 0x1234...abcd --limit 100

Troubleshooting

"Wallet has no trades"

• This wallet hasn't traded yet, or all trades are too old
• Try a wallet you know is active

"Analysis took too long"

• For wallets with >500 trades, analysis can take 30+ seconds
• Use --limit 100 to analyze only recent trades for faster results

"API rate limited"

• You're analyzing many wallets in quick succession
• Wait a minute before trying again, or use --limit to speed up individual analyses

"Connection error"

• Check that Polymarket's Data API v2 is reachable: curl 'https://data-api.polymarket.com/v2/activity?user=0xYOUR_WALLET&limit=1'
• If down, try again later or use --limit 50 to reduce load

Credits

This skill is based on the forensic trading analysis framework from @thejayden's "Autopsy of a Polymarket Whale".

The original post shows how to:

• Spot fake gurus (high PnL, terrible entries)
• Detect bots (inhuman trading speed)
• Find arbitrage opportunities (hedged positions)
• Understand trader psychology (FOMO vs. discipline)

All metrics and analysis patterns used here are derived from that work. If you find this useful, give the original post a read and follow @thejayden.

Links

• Full Simmer API Reference: docs.simmer.markets/api/overview
• Original Analysis: The Autopsy: How to Read the Mind of a Polymarket Whale
• Dashboard: simmer.markets/dashboard
• Support: Telegram