{"id":"3f992d82-8d1f-4a19-847a-b0b76788168d","entityType":"agent","slug":"clawhub-simmer-polymarket-wallet-xray","name":"polymarket-wallet-xray","canonicalUrl":"https://www.xpersona.co/agent/clawhub-simmer-polymarket-wallet-xray","canonicalPath":"/agent/clawhub-simmer-polymarket-wallet-xray","generatedAt":"2026-10-10T02:04:57.765Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-09T21:58:46.719Z","emptyReason":null},"description":"X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis. Skill: polymarket-wallet-xray Owner: simmer Summary: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis. Tags: latest:1.1.5 Version history: v1.1.5 | 2026-09-06T01:16:30.622Z | auto Polymarket Wallet X-Ray v1.1.5 - Bumped skill version to 1.1.5. - Docum","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 2K downloads reported by the source. 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Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\n\nTags: latest:1.1.5\n\nVersion history:\n\nv1.1.5 | 2026-09-06T01:16:30.622Z | auto\n\nPolymarket Wallet X-Ray v1.1.5\n\n- Bumped skill version to 1.1.5.\n- Documentation updates in SKILL.md.\n- Removed obsolete file: skill-card.md.\n\nv1.1.4 | 2026-06-09T07:25:14.312Z | user\n\nDoc links point to docs.simmer.markets (retired flat simmer.markets docs)\n\nv1.1.3 | 2026-04-25T09:21:31.291Z | user\n\nDoc-only update: Gamma API reference now points at /markets/keyset (Polymarket deprecation deadline May 1, 2026). No code changes.\n\nv1.1.2 | 2026-04-16T10:06:00.679Z | user\n\nAdd Setup Flow section with pip install simmer-sdk\n\nv1.1.1 | 2026-04-03T02:47:15.632Z | user\n\nAdd auto_redeem() call at start of each cycle for external wallet support\n\nv1.1.0 | 2026-04-01T15:34:56.134Z | auto\n\npolymarket-wallet-xray 1.1.0 Changelog\n\n- Updated configuration: clawhub.json modified.\n- No user-facing features or documentation changes in this release.\n\nv1.0.4 | 2026-03-03T02:53:14.615Z | user\n\nAgentSkills format — moved platform config to clawhub.json for cross-agent compatibility\n\nv1.0.3 | 2026-02-27T10:15:59.992Z | auto\n\nVersion 1.0.3\n\n- Added \"difficulty: beginner\" to the skill metadata for clearer audience targeting.\n- No other functional or content changes.\n\nv1.0.2 | 2026-02-25T13:46:29.304Z | auto\n\nVersion 1.0.2\n\n- Updated documentation in SKILL.md to clarify that a hedge check showing a combined average < $1.00 indicates a potential structural edge that depends on execution, fees, and spread.\n- Adjusted risk warning language for hedge/arbitrage to be more precise regarding actual profitability.\n- No changes to code or external APIs; update is documentation-only.\n\nv1.0.1 | 2026-02-25T13:32:39.749Z | auto\n\nPolymarket Wallet X-Ray v1.0.1\n\n- Updated version number to 1.0.1 in documentation.\n- No functional changes; documentation (SKILL.md) only.\n\nv1.0.0 | 2026-02-25T10:05:13.039Z | auto\n\nInitial release of Polymarket Wallet X-Ray:\n\n- Analyze any Polymarket wallet with skill level, entry quality, bot detection, and edge assessment\n- Fetches trading data via Polymarket's public APIs; no authentication required\n- Inspired by \"Autopsy of a Polymarket Whale\" forensic trading framework\n- Returns detailed metrics (profitability, behavior, risk, and recommendations) for education and research\n- Provides quick command examples for wallet analysis, comparison, and research on trading behavior\n- Includes comprehensive documentation on interpreting results and responsible use\n\nArchive index:\n\nArchive v1.1.5: 8 files, 19308 bytes\n\nFiles: clawhub.json (170b), DISCLAIMER.md (1925b), README.md (1650b), scripts/status.py (5443b), skill-card.md (2803b), SKILL.md (12285b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.1.5:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.1.5\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 🚨 **Framework, not a production trading system.** Read [DISCLAIMER.md](./DISCLAIMER.md) before connecting to a wallet with real funds.\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Setup Flow\n\nWhen user asks to install or configure this skill:\n\n1. **Install the Simmer SDK**\n   ```bash\n   pip install simmer-sdk\n   ```\n\n2. **Ask for Simmer API key**\n   - They can get it from simmer.markets/dashboard → SDK tab\n   - Store in environment as `SIMMER_API_KEY`\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com/markets/keyset` — Market search (cursor-paginated)\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [docs.simmer.markets/api/overview](https://docs.simmer.markets/api/overview)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard?ref=sdk-skill&utm_campaign=sdk-skill)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.1.5:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.1.5:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.1.5\",\n  \"publishedAt\": 1788657390622\n}\n\nFile v1.1.5:DISCLAIMER.md\n\n# Disclaimer\n\nThis skill is a **framework**, not a production trading system. Read this\nin full before connecting it to a wallet with real funds.\n\n## No financial advice\n\nNothing in this skill constitutes financial, investment, or trading\nadvice. The default strategy implemented here is a starting point, not a\ntested edge. Suitability for any account size or risk tolerance is your\nresponsibility to assess.\n\n## Default parameters are not validated\n\nDefault parameters are calibrated for testing the plumbing, not for live\nprofit. They have not been validated to produce positive returns under\ncurrent market conditions. Run paper mode for an extended period before\nscaling beyond default position sizes.\n\n## Automated trading carries irreversible risk\n\nWhen this skill runs with `--live`, it places real on-chain orders.\nOn-chain trades cannot be recalled. Strategy errors, signal lag, market\nregime shifts, and operator misconfiguration can produce losses\nexceeding any specific position size.\n\n## Risk monitoring may not apply to all market types\n\nStop-loss and take-profit monitors run on a fixed schedule. Markets that\nresolve faster than the monitor cycle cannot be exited automatically.\nPosition sizing is the only risk control on these markets — set it\nconservatively.\n\n## Use of this skill is at your own risk\n\nBy installing and running this skill you agree that the authors are not\nliable for any losses, direct or indirect, that arise from its use. This\napplies regardless of skill provenance — official Simmer skills,\ncommunity skills, and skills imported from external repositories all\ncarry this same disclaimer.\n\n## Where to learn more before going live\n\n- The skill's own `SKILL.md` documents the strategy and parameters\n- Your trading venue's documentation covers fee structure, order types,\n  and resolution rules\n- Simmer SDK documentation covers paper mode, dry-run flags, and\n  position monitoring\n\nFile v1.1.5:skill-card.md\n\n## Description:\n\nX-ray any Polymarket wallet for skill level, entry quality, bot detection, and edge analysis using public Polymarket activity data.\n\nThis skill is for research and development only.\n\n## Publisher:\n\n[simmer](https://clawhub.ai/user/simmer)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers, researchers, and prediction-market analysts use this skill to inspect public Polymarket wallet activity, compare trader profiles, and study behavioral signals such as entry quality, bot-like timing, hedging, and drawdown risk. It should support research and decision review, not automatic copytrading or financial advice.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The server security review marks the release suspicious because the wallet analyzer is described as public-data only while the package also requests SIMMER_API_KEY and includes authenticated account-status behavior.\n\nMitigation: Review the skill before installation, run it in an isolated environment, and export SIMMER_API_KEY only when intentionally using the Simmer account-status helper.\n\nRisk: Wallet metrics and generated recommendations can be mistaken for copytrading instructions or financial advice.\n\nMitigation: Use the output for research and independent review only; do not automate trades or allocate capital based solely on the skill's recommendation field.\n\nRisk: Historical wallet performance, entry quality, and arbitrage indicators may not generalize to future market conditions.\n\nMitigation: Treat results as retrospective analysis, validate assumptions separately, and use paper or dry-run workflows before any real-money use.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/simmer/skills/polymarket-wallet-xray)\n- [Simmer API Reference](https://docs.simmer.markets/api/overview)\n- [Polymarket CLOB API](https://clob.polymarket.com)\n- [Polymarket Gamma markets keyset endpoint](https://gamma-api.polymarket.com/markets/keyset)\n- [Original wallet analysis framework](https://x.com/thejayden/status/2020891572389224878)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, JSON, shell commands, guidance]\n\n**Output Format:** [CLI text or JSON metrics, with markdown guidance and shell command examples]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May include wallet profitability, entry-quality, bot-detection, arbitrage, risk-profile, and recommendation fields.]\n\n## Skill Version(s):\n\n1.1.5 (source: server release evidence and SKILL.md frontmatter)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.1.5:clawhub.json\n\n{\n  \"emoji\": \"\\ud83d\\udd0d\",\n  \"requires\": {\n    \"env\": [\n      \"SIMMER_API_KEY\"\n    ],\n    \"pip\": [\n      \"simmer-sdk\"\n    ]\n  },\n  \"cron\": null,\n  \"autostart\": false\n}\n\nArchive v1.1.4: 8 files, 19112 bytes\n\nFiles: clawhub.json (170b), DISCLAIMER.md (1925b), README.md (1650b), scripts/status.py (5110b), skill-card.md (2860b), SKILL.md (12248b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.1.4:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.1.4\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 🚨 **Framework, not a production trading system.** Read [DISCLAIMER.md](./DISCLAIMER.md) before connecting to a wallet with real funds.\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Setup Flow\n\nWhen user asks to install or configure this skill:\n\n1. **Install the Simmer SDK**\n   ```bash\n   pip install simmer-sdk\n   ```\n\n2. **Ask for Simmer API key**\n   - They can get it from simmer.markets/dashboard → SDK tab\n   - Store in environment as `SIMMER_API_KEY`\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com/markets/keyset` — Market search (cursor-paginated)\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [docs.simmer.markets/api/overview](https://docs.simmer.markets/api/overview)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.1.4:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.1.4:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.1.4\",\n  \"publishedAt\": 1780989914312\n}\n\nFile v1.1.4:DISCLAIMER.md\n\n# Disclaimer\n\nThis skill is a **framework**, not a production trading system. Read this\nin full before connecting it to a wallet with real funds.\n\n## No financial advice\n\nNothing in this skill constitutes financial, investment, or trading\nadvice. The default strategy implemented here is a starting point, not a\ntested edge. Suitability for any account size or risk tolerance is your\nresponsibility to assess.\n\n## Default parameters are not validated\n\nDefault parameters are calibrated for testing the plumbing, not for live\nprofit. They have not been validated to produce positive returns under\ncurrent market conditions. Run paper mode for an extended period before\nscaling beyond default position sizes.\n\n## Automated trading carries irreversible risk\n\nWhen this skill runs with `--live`, it places real on-chain orders.\nOn-chain trades cannot be recalled. Strategy errors, signal lag, market\nregime shifts, and operator misconfiguration can produce losses\nexceeding any specific position size.\n\n## Risk monitoring may not apply to all market types\n\nStop-loss and take-profit monitors run on a fixed schedule. Markets that\nresolve faster than the monitor cycle cannot be exited automatically.\nPosition sizing is the only risk control on these markets — set it\nconservatively.\n\n## Use of this skill is at your own risk\n\nBy installing and running this skill you agree that the authors are not\nliable for any losses, direct or indirect, that arise from its use. This\napplies regardless of skill provenance — official Simmer skills,\ncommunity skills, and skills imported from external repositories all\ncarry this same disclaimer.\n\n## Where to learn more before going live\n\n- The skill's own `SKILL.md` documents the strategy and parameters\n- Your trading venue's documentation covers fee structure, order types,\n  and resolution rules\n- Simmer SDK documentation covers paper mode, dry-run flags, and\n  position monitoring\n\nFile v1.1.4:skill-card.md\n\n## Description: <br>\nX-ray any Polymarket wallet for skill level, entry quality, bot detection, and edge analysis using public Polymarket market and trade data. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[simmer](https://clawhub.ai/user/simmer) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users and developers use this skill to inspect Polymarket wallet trading behavior, compare wallet profiles, identify bot-like or anomalous activity, and inform their own research without treating the output as trading advice. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: The security review reports conflicting guidance about authentication and notes authenticated Simmer account access. <br>\nMitigation: Do not provide SIMMER_API_KEY unless the user intentionally wants the skill to access Simmer account portfolio and position data. <br>\nRisk: The skill can produce copytrading-oriented recommendations that may be mistaken for financial advice. <br>\nMitigation: Treat results as unsupported analysis for research and learning; require independent judgment before any trading decision. <br>\nRisk: Documentation mentions live-trading risk while the reviewed analyzer appears mostly read-only, creating ambiguity about operational behavior. <br>\nMitigation: Review commands and flags before execution, avoid live or automated trading workflows unless the behavior is explicitly understood, and start with dry-run or paper-mode workflows when available. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/simmer/polymarket-wallet-xray) <br>\n- [Simmer API reference](https://docs.simmer.markets/api/overview) <br>\n- [Original forensic trading analysis](https://x.com/thejayden/status/2020891572389224878) <br>\n- [Polymarket Gamma API](https://gamma-api.polymarket.com/markets/keyset) <br>\n- [Polymarket CLOB API](https://clob.polymarket.com) <br>\n- [Polymarket Data API](https://data-api.polymarket.com) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [analysis, markdown, json, shell commands, guidance] <br>\n**Output Format:** [Human-readable console or Markdown summaries, with optional JSON output for scripted use.] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [May include wallet profitability metrics, entry-quality ratings, bot-detection signals, risk profile, comparison results, and recommendation text.] <br>\n\n## Skill Version(s): <br>\n1.1.4 (source: server release metadata and skill metadata) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.1.4:clawhub.json\n\n{\n  \"emoji\": \"\\ud83d\\udd0d\",\n  \"requires\": {\n    \"env\": [\n      \"SIMMER_API_KEY\"\n    ],\n    \"pip\": [\n      \"simmer-sdk\"\n    ]\n  },\n  \"cron\": null,\n  \"autostart\": false\n}\n\nArchive v1.1.3: 7 files, 17772 bytes\n\nFiles: clawhub.json (170b), README.md (1650b), scripts/status.py (5110b), skill-card.md (2573b), SKILL.md (12087b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.1.3:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.1.1\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Setup Flow\n\nWhen user asks to install or configure this skill:\n\n1. **Install the Simmer SDK**\n   ```bash\n   pip install simmer-sdk\n   ```\n\n2. **Ask for Simmer API key**\n   - They can get it from simmer.markets/dashboard → SDK tab\n   - Store in environment as `SIMMER_API_KEY`\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com/markets/keyset` — Market search (cursor-paginated)\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [simmer.markets/docs.md](https://simmer.markets/docs.md)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.1.3:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.1.3:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.1.3\",\n  \"publishedAt\": 1777108891291\n}\n\nFile v1.1.3:skill-card.md\n\n## Description: <br>\nAnalyzes Polymarket wallet trading history for profitability, entry quality, bot-like behavior, arbitrage signals, and risk profile metrics. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[simmer](https://clawhub.ai/user/simmer) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users and developers use this skill to inspect public Polymarket wallet activity and compare trading behavior. It supports research and education about trader profiles, not automated copytrading or financial advice. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Wallet addresses are sent to external Polymarket APIs during analysis. <br>\nMitigation: Analyze only addresses you are comfortable submitting to those external APIs. <br>\nRisk: The account-status helper uses SIMMER_API_KEY and can read private Simmer portfolio data. <br>\nMitigation: Provide SIMMER_API_KEY only when intentionally using the status helper, and keep the key scoped to the local environment. <br>\nRisk: Recommendation and copytrading language may be mistaken for financial advice. <br>\nMitigation: Treat outputs as informational research signals and review them independently before making any trading decision. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/simmer/polymarket-wallet-xray) <br>\n- [Simmer API documentation](https://simmer.markets/docs.md) <br>\n- [Polymarket Data API](https://data-api.polymarket.com) <br>\n- [Polymarket Gamma API market keyset](https://gamma-api.polymarket.com/markets/keyset) <br>\n- [Polymarket CLOB API](https://clob.polymarket.com) <br>\n- [Original forensic trading analysis](https://x.com/thejayden/status/2020891572389224878) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [text, markdown, json, shell commands, guidance] <br>\n**Output Format:** [Console text or JSON from Python command-line scripts, with Markdown setup and usage guidance.] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Requires a wallet address for analysis; SIMMER_API_KEY is only needed for the account-status helper.] <br>\n\n## Skill Version(s): <br>\n1.1.3 (source: server release metadata; artifact frontmatter lists 1.1.1) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.1.3:clawhub.json\n\n{\n  \"emoji\": \"\\ud83d\\udd0d\",\n  \"requires\": {\n    \"env\": [\n      \"SIMMER_API_KEY\"\n    ],\n    \"pip\": [\n      \"simmer-sdk\"\n    ]\n  },\n  \"cron\": null,\n  \"autostart\": false\n}\n\nArchive v1.1.2: 6 files, 16397 bytes\n\nFiles: clawhub.json (170b), README.md (1650b), scripts/status.py (5110b), SKILL.md (12053b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.1.2:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.1.0\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Setup Flow\n\nWhen user asks to install or configure this skill:\n\n1. **Install the Simmer SDK**\n   ```bash\n   pip install simmer-sdk\n   ```\n\n2. **Ask for Simmer API key**\n   - They can get it from simmer.markets/dashboard → SDK tab\n   - Store in environment as `SIMMER_API_KEY`\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com` — Market search\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [simmer.markets/docs.md](https://simmer.markets/docs.md)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.1.2:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.1.2:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.1.2\",\n  \"publishedAt\": 1776333960679\n}\n\nFile v1.1.2:clawhub.json\n\n{\n  \"emoji\": \"\\ud83d\\udd0d\",\n  \"requires\": {\n    \"env\": [\n      \"SIMMER_API_KEY\"\n    ],\n    \"pip\": [\n      \"simmer-sdk\"\n    ]\n  },\n  \"cron\": null,\n  \"autostart\": false\n}\n\nArchive v1.1.1: 6 files, 16251 bytes\n\nFiles: clawhub.json (170b), README.md (1650b), scripts/status.py (5110b), SKILL.md (11771b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.1.1:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.1.0\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com` — Market search\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [simmer.markets/docs.md](https://simmer.markets/docs.md)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.1.1:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.1.1:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.1.1\",\n  \"publishedAt\": 1775184435632\n}\n\nFile v1.1.1:clawhub.json\n\n{\n  \"emoji\": \"\\ud83d\\udd0d\",\n  \"requires\": {\n    \"env\": [\n      \"SIMMER_API_KEY\"\n    ],\n    \"pip\": [\n      \"simmer-sdk\"\n    ]\n  },\n  \"cron\": null,\n  \"autostart\": false\n}\n\nArchive v1.1.0: 6 files, 16251 bytes\n\nFiles: clawhub.json (170b), README.md (1650b), scripts/status.py (5110b), SKILL.md (11771b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.1.0:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.0.2\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com` — Market search\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [simmer.markets/docs.md](https://simmer.markets/docs.md)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.1.0:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.1.0:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.1.0\",\n  \"publishedAt\": 1775057696134\n}\n\nFile v1.1.0:clawhub.json\n\n{\n  \"emoji\": \"\\ud83d\\udd0d\",\n  \"requires\": {\n    \"env\": [\n      \"SIMMER_API_KEY\"\n    ],\n    \"pip\": [\n      \"simmer-sdk\"\n    ]\n  },\n  \"cron\": null,\n  \"autostart\": false\n}\n\nArchive v1.0.4: 6 files, 16217 bytes\n\nFiles: clawhub.json (118b), README.md (1650b), scripts/status.py (5110b), SKILL.md (11771b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.0.4:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.0.2\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com` — Market search\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [simmer.markets/docs.md](https://simmer.markets/docs.md)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.0.4:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.0.4:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.0.4\",\n  \"publishedAt\": 1772506394615\n}\n\nFile v1.0.4:clawhub.json\n\n{\n  \"emoji\": \"\\ud83d\\udd0d\",\n  \"requires\": {\n    \"env\": [],\n    \"pip\": []\n  },\n  \"cron\": null,\n  \"autostart\": false\n}\n\nArchive v1.0.3: 5 files, 16101 bytes\n\nFiles: README.md (1650b), scripts/status.py (5110b), SKILL.md (11972b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.0.3:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndisplayName: Polymarket Wallet X-Ray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata: {\"clawdbot\":{\"emoji\":\"🔍\",\"requires\":{\"env\":[],\"pip\":[]},\"cron\":null,\"autostart\":false}}\nauthors:\n  - Simmer (@simmer_markets)\ninspired_by:\n  - thejayden (@thejayden) - \"Autopsy: How to Read the Mind of a Polymarket Whale\"\nversion: \"1.0.2\"\ndifficulty: beginner\npublished: true\n---\n\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com` — Market search\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [simmer.markets/docs.md](https://simmer.markets/docs.md)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.0.3:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.0.3:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.0.3\",\n  \"publishedAt\": 1772187359992\n}\n\nArchive v1.0.2: 5 files, 16088 bytes\n\nFiles: README.md (1650b), scripts/status.py (5110b), SKILL.md (11951b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.0.2:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndisplayName: Polymarket Wallet X-Ray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata: {\"clawdbot\":{\"emoji\":\"🔍\",\"requires\":{\"env\":[],\"pip\":[]},\"cron\":null,\"autostart\":false}}\nauthors:\n  - Simmer (@simmer_markets)\ninspired_by:\n  - thejayden (@thejayden) - \"Autopsy: How to Read the Mind of a Polymarket Whale\"\nversion: \"1.0.2\"\npublished: true\n---\n\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com` — Market search\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}\n```\n\n## How It Works\n\n1. **Fetch trade history** — Download all trades this wallet made from Polymarket via Simmer API\n2. **Compute profitability timeline** — When were they underwater vs. profitable?\n3. **Analyze entry quality** — Did they buy at optimal prices or chase?\n4. **Detect trading patterns** — Bot (inhuman speed) vs. human (deliberate timing)?\n5. **Check for arbitrage** — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)\n6. **Assess behavior** — FOMO accumulation? Disciplined sizing? Rotating positions?\n7. **Generate recommendation** — Is this wallet worth following? What's the risk?\n\n## Understanding the Metrics\n\n### ⏱️ **Time Profitable** (e.g., 75.3%)\nWallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.\n\n- **>80%** = Sniper-like (skilled entries, holds through drawdowns)\n- **50-80%** = Solid (good discipline)\n- **<50%** = Risky (likely panic-held losses)\n\n### 🎯 **Entry Quality** (e.g., 28 bps average slippage)\nThey buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.\n\n- **<20 bps** = Expert. Limit orders, patience.\n- **20-40 bps** = Good. Balanced speed/price.\n- **>50 bps** = Weak. Chasing prices.\n\n### 🤖 **Bot Detection** (e.g., false)\nAverage 45 seconds between trades. This is human. A bot would be <1 second.\n\n- **<5 sec** = Likely bot. Avoid unless you know it's a legitimate market maker.\n- **5-30 sec** = Possible bot.\n- **>30 sec** = Human.\n\n### 💰 **Hedge Check** (e.g., combined avg 0.98)\nIf they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.\n\nIf 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.\n\n- **< $0.95** = Strong potential edge. Likely institutional/pro.\n- **$0.95-1.00** = Slight edge detected.\n- **> $1.00** = No edge; betting on direction.\n\n## Usage Examples\n\n### **Example 1: Learning from a skilled trader (Analysis)**\n\n```python\nimport subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?\n```\n\n### **Example 2: Research anomalies (Education)**\n\n```python\n# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights\n```\n\n### **Example 3: Informed decision-making (NOT blind copying)**\n\n```python\n# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")\n```\n\n## Running the Skill\n\n**Analyze a single wallet (default):**\n```bash\npython wallet_xray.py 0x1234...abcd\n```\n\n**Analyze wallet for a specific market:**\n```bash\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n```\n\n**Output as JSON (for scripts):**\n```bash\npython wallet_xray.py 0x1234...abcd --json\n```\n\n**Compare two wallets:**\n```bash\npython wallet_xray.py 0x1111... 0x2222... --compare\n```\n\n**Limit analysis to recent trades (faster):**\n```bash\npython wallet_xray.py 0x1234...abcd --limit 100\n```\n\n## Troubleshooting\n\n**\"Wallet has no trades\"**\n- This wallet hasn't traded yet, or all trades are too old\n- Try a wallet you know is active\n\n**\"Market not found\"**\n- The market query didn't match anything on Polymarket\n- Try a more specific market name or leave it blank to analyze all markets\n\n**\"Analysis took too long\"**\n- For wallets with >500 trades, analysis can take 30+ seconds\n- Use `--limit 100` to analyze only recent trades for faster results\n\n**\"API rate limited\"**\n- You're analyzing many wallets in quick succession\n- Wait a minute before trying again, or use `--limit` to speed up individual analyses\n\n**\"Connection error\"**\n- Check that Polymarket's CLOB API is reachable: `curl https://clob.polymarket.com/trades`\n- If down, try again later or use `--limit 50` to reduce load\n\n## Credits\n\nThis skill is based on the forensic trading analysis framework from [@thejayden's \"Autopsy of a Polymarket Whale\"](https://x.com/thejayden/status/2020891572389224878).\n\nThe original post shows how to:\n- Spot fake gurus (high PnL, terrible entries)\n- Detect bots (inhuman trading speed)\n- Find arbitrage opportunities (hedged positions)\n- Understand trader psychology (FOMO vs. discipline)\n\nAll 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](https://x.com/thejayden).\n\n## Links\n\n- **Full Simmer API Reference:** [simmer.markets/docs.md](https://simmer.markets/docs.md)\n- **Original Analysis:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878)\n- **Dashboard:** [simmer.markets/dashboard](https://simmer.markets/dashboard)\n- **Support:** [Telegram](https://t.me/+m7sN0OLM_780M2Fl)\n\nFile v1.0.2:README.md\n\n# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878\n\nFile v1.0.2:_meta.json\n\n{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.0.2\",\n  \"publishedAt\": 1772027189304\n}\n\nArchive v1.0.1: 5 files, 16031 bytes\n\nFiles: README.md (1650b), scripts/status.py (5110b), SKILL.md (11826b), wallet_xray.py (26874b), _meta.json (141b)\n\nFile v1.0.1:SKILL.md\n\n---\nname: polymarket-wallet-xray\ndisplayName: Polymarket Wallet X-Ray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata: {\"clawdbot\":{\"emoji\":\"🔍\",\"requires\":{\"env\":[],\"pip\":[]},\"cron\":null,\"autostart\":false}}\nauthors:\n  - Simmer (@simmer_markets)\ninspired_by:\n  - thejayden (@thejayden) - \"Autopsy: How to Read the Mind of a Polymarket Whale\"\nversion: \"1.0.1\"\npublished: true\n---\n\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- Assuming past returns = future returns\n- Making large bets on these metrics alone\n\n## Quick Commands\n\n```bash\n# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py\n```\n\n**APIs Used (Public, No Auth Required):**\n- Gamma API: `https://gamma-api.polymarket.com` — Market search\n- CLOB API: `https://clob.polymarket.com` — Trade history and orderbook\n\n## What You Get Back\n\nThe skill returns comprehensive forensic metrics:\n\n```json\n{\n  \"wallet\": \"","readmeExcerpt":"Skill: polymarket-wallet-xray Owner: simmer Summary: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis. Tags: latest:1.1.5 Version history: v1.1.5 | 2026-09-06T01:16:30.622Z | auto Polymarket Wallet X-Ray v1.1.5 - Bumped skill version to 1.1.5. - Docum","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"pip install simmer-sdk"},{"language":"bash","snippet":"# Analyze a single wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet + only look at specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Compare two wallets head-to-head\npython wallet_xray.py 0x1111... 0x2222... --compare\n\n# Find wallets matching criteria (top Time Profitable in market)\npython wallet_xray.py \"Will BTC hit $100k?\" --top-wallets 5 --dry-run\n\n# Check your account status\npython scripts/status.py"},{"language":"json","snippet":"{\n  \"wallet\": \"0x1234...abcd\",\n  \"total_trades\": 156,\n  \"total_period_hours\": 42.5,\n  \"profitability\": {\n    \"time_profitable_pct\": 75.3,\n    \"win_rate_pct\": 68.2,\n    \"avg_profit_per_win\": 0.035,\n    \"avg_loss_per_loss\": -0.018,\n    \"realized_pnl_usd\": 2450.00\n  },\n  \"entry_quality\": {\n    \"avg_slippage_bps\": 28,\n    \"quality_rating\": \"B+\",\n    \"assessment\": \"Good entries, occasional FOMO\"\n  },\n  \"behavior\": {\n    \"is_bot_detected\": false,\n    \"trading_intensity\": \"high\",\n    \"avg_seconds_between_trades\": 45,\n    \"price_chasing\": \"moderate\",\n    \"accumulation_signal\": \"growing\"\n  },\n  \"edge_detection\": {\n    \"hedge_check_combined_avg\": 0.98,\n    \"has_arbitrage_edge\": false,\n    \"assessment\": \"No locked-in edge; relies on direction\"\n  },\n  \"risk_profile\": {\n    \"max_drawdown_pct\": 12.5,\n    \"volatility\": \"medium\",\n    \"max_position_concentration\": 0.22\n  },\n  \"recommendation\": \"Good trader. Skilled entries, disciplined sizing. Good metrics for learning from. Not advice to copytrade.\"\n}"},{"language":"python","snippet":"import subprocess\nimport json\n\n# Analyze a wallet known for skilled trading\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# LEARN from their profile, don't copy blindly\ntime_prof = data[\"profitability\"][\"time_profitable_pct\"]\nentry_qual = data[\"entry_quality\"][\"quality_rating\"]\n\nprint(f\"📊 What this trader does well:\")\nprint(f\"  • Time Profitable: {time_prof}% (disciplined)\")\nprint(f\"  • Entry Quality: {entry_qual} (patient buyer)\")\nprint(f\"  • Behavior: {data['behavior']['accumulation_signal']} (not FOMO)\")\n\n# THEN: Ask yourself\n# - Why are they profitable? (skill or luck?)\n# - Can I replicate their decision-making process?\n# - Do I have their capital size, timing, or information?"},{"language":"python","snippet":"# Analyze multiple wallets to understand patterns\nwallets = [\"0x111...\", \"0x222...\", \"0x333...\"]\n\nprint(\"Comparing trader profiles:\")\nfor wallet in wallets:\n    result = subprocess.run(\n        [\"python\", \"wallet_xray.py\", wallet, \"--json\"],\n        capture_output=True,\n        text=True\n    )\n    data = json.loads(result.stdout)\n\n    is_bot = \"🤖 BOT\" if data[\"behavior\"][\"is_bot_detected\"] else \"👤 HUMAN\"\n    print(f\"\\n{wallet}: {is_bot}\")\n    print(f\"  Win Rate: {data['profitability']['win_rate_pct']}%\")\n    print(f\"  Time Profitable: {data['profitability']['time_profitable_pct']}%\")\n\n# Use this data to understand what successful trading LOOKS LIKE\n# Then build your own strategy based on these insights"},{"language":"python","snippet":"# Analyze before you decide what to do\nresult = subprocess.run(\n    [\"python\", \"wallet_xray.py\", \"0x123...abc\", \"--json\"],\n    capture_output=True,\n    text=True\n)\ndata = json.loads(result.stdout)\n\n# Make an INFORMED decision based on analysis + YOUR OWN JUDGMENT\nif data[\"profitability\"][\"time_profitable_pct\"] > 75 and \\\n   data[\"entry_quality\"][\"quality_rating\"] in [\"A\", \"A+\"]:\n\n    print(f\"✅ This wallet shows skill (high Time Profitable, good entries)\")\n    print(f\"⚠️  But I will NOT copytrade blindly.\")\n    print(f\"📋 Instead, I'll:\")\n    print(f\"   1. Backtest their patterns on fresh data\")\n    print(f\"   2. Add my own market signals\")\n    print(f\"   3. Start with small position (1-2% of capital)\")\n    print(f\"   4. Monitor for next 30 days\")\n    print(f\"   5. Adjust if it stops working\")\nelse:\n    print(f\"❌ This wallet doesn't show strong enough metrics.\")\n    print(f\"   Safer to avoid or research further before deciding.\")"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: polymarket-wallet-xray\ndescription: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis.\nmetadata:\n  author: Simmer (@simmer_markets)\n  version: \"1.1.5\"\n  displayName: Polymarket Wallet X-Ray\n  difficulty: beginner\n---\n# Polymarket Wallet X-Ray\n\nAnalyze **any** Polymarket wallet's trading patterns, skill level, and edge detection.\n\n**No authentication needed.** Queries Polymarket's public CLOB API directly.\n\n**Inspired by:** [The Autopsy: How to Read the Mind of a Polymarket Whale](https://x.com/thejayden/status/2020891572389224878) by [@thejayden](https://x.com/thejayden)\n\n> 🚨 **Framework, not a production trading system.** Read [DISCLAIMER.md](./DISCLAIMER.md) before connecting to a wallet with real funds.\n\n> 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.\n\n> **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.\n\n## ⚠️ Important Disclaimer\n\n**Past performance does not guarantee future results.** A wallet's historical metrics tell you about:\n- ✅ How they traded *in the past*\n- ✅ Their *historical* win rate and entry quality\n- ❌ NOT whether their strategy will work going forward\n\n**Why copying is risky:**\n- Market conditions change constantly\n- A trader's edge might have been luck, timing, or specific to historical events\n- Slippage and fees erode thin edges to zero\n- Other traders copying the same strategy destroy the edge\n\n**Use this skill to:**\n- ✅ Learn what skilled traders look like (metrics, behavior)\n- ✅ Identify potential anomalies (bots, arbitrageurs)\n- ✅ Understand trader psychology (FOMO vs. discipline)\n- ✅ Inform your own strategy decisions\n\n**DO NOT use this skill to:**\n- ❌ Automatically copytrade wallets\n- ❌ Expect to replicate their returns\n- ❌ Trade on these metrics without understanding why\n- ❌ Risk significant capital on patterns you don't understand\n\n## When to Use This Skill\n\nUse this skill when you want to:\n- **Learn how skilled traders operate** — What metrics separate winners from losers?\n- **Understand trading psychology** — Who chases prices? Who has discipline?\n- **Detect bots and anomalies** — Identify suspicious patterns for research\n- **Research arbitrage activity** — Find wallets with hedged positions (educational)\n- **Compare trader profiles** — What does a consistent trader look like vs. a lucky one?\n- **Inform your own strategy** — Use patterns as input to YOUR decision-making, not as direct signals\n\n**NOT for:**\n- Copying trades blindly or automatically\n- "},{"path":"README.md","content":"# Polymarket Wallet X-Ray\n\nX-ray any Polymarket wallet — trading patterns, skill level, and edge detection.\n\n## Files\n\n- **SKILL.md** — User documentation, quick start, usage examples, troubleshooting\n- **wallet_xray.py** — Main analysis script\n- **scripts/status.py** — Portfolio status helper\n\n## Quick Start\n\n```bash\n# Analyze a wallet\npython wallet_xray.py 0x1234...abcd\n\n# Analyze wallet for specific market\npython wallet_xray.py 0x1234...abcd \"Bitcoin\"\n\n# Output as JSON\npython wallet_xray.py 0x1234...abcd --json\n\n# Compare two wallets\npython wallet_xray.py 0xaaa... 0xbbb... --compare\n```\n\n## Installation\n\n```bash\npip install simmer-sdk requests\nexport SIMMER_API_KEY=\"sk_live_...\"\n```\n\n## Metrics Computed\n\n- **Time Profitable** — % of time wallet was not underwater\n- **Win Rate** — % of trades profitable\n- **Entry Quality** — Average slippage from optimal price\n- **Bot Detection** — Trading speed pattern analysis\n- **Arbitrage Edge** — Combined YES+NO average < $1.00\n- **Risk Profile** — Drawdowns and volatility\n- **Recommendation** — Should you copytrade this wallet?\n\n## Implementation Notes\n\nThe skill fetches trades from the Simmer API, which aggregates Polymarket data. It then:\n\n1. Tracks positions over time (YES/NO shares and cost basis)\n2. Realizes P&Ls when positions are closed\n3. Computes statistical metrics (mean, stdev, etc.)\n4. Generates a recommendation score\n\nAll metrics are based on @thejayden's \"Autopsy of a Polymarket Whale\" framework.\n\n## Attribution\n\nInspired by [@thejayden](https://x.com/thejayden)'s forensic trading analysis post:\nhttps://x.com/thejayden/status/2020891572389224878"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn7axnp7bzqsf5fkx0z8px7han7zyq1x\",\n  \"slug\": \"polymarket-wallet-xray\",\n  \"version\": \"1.1.5\",\n  \"publishedAt\": 1788657390622\n}"},{"path":"DISCLAIMER.md","content":"# Disclaimer\n\nThis skill is a **framework**, not a production trading system. Read this\nin full before connecting it to a wallet with real funds.\n\n## No financial advice\n\nNothing in this skill constitutes financial, investment, or trading\nadvice. The default strategy implemented here is a starting point, not a\ntested edge. Suitability for any account size or risk tolerance is your\nresponsibility to assess.\n\n## Default parameters are not validated\n\nDefault parameters are calibrated for testing the plumbing, not for live\nprofit. They have not been validated to produce positive returns under\ncurrent market conditions. Run paper mode for an extended period before\nscaling beyond default position sizes.\n\n## Automated trading carries irreversible risk\n\nWhen this skill runs with `--live`, it places real on-chain orders.\nOn-chain trades cannot be recalled. Strategy errors, signal lag, market\nregime shifts, and operator misconfiguration can produce losses\nexceeding any specific position size.\n\n## Risk monitoring may not apply to all market types\n\nStop-loss and take-profit monitors run on a fixed schedule. Markets that\nresolve faster than the monitor cycle cannot be exited automatically.\nPosition sizing is the only risk control on these markets — set it\nconservatively.\n\n## Use of this skill is at your own risk\n\nBy installing and running this skill you agree that the authors are not\nliable for any losses, direct or indirect, that arise from its use. This\napplies regardless of skill provenance — official Simmer skills,\ncommunity skills, and skills imported from external repositories all\ncarry this same disclaimer.\n\n## Where to learn more before going live\n\n- The skill's own `SKILL.md` documents the strategy and parameters\n- Your trading venue's documentation covers fee structure, order types,\n  and resolution rules\n- Simmer SDK documentation covers paper mode, dry-run flags, and\n  position monitoring"},{"path":"skill-card.md","content":"## Description:\n\nX-ray any Polymarket wallet for skill level, entry quality, bot detection, and edge analysis using public Polymarket activity data.\n\nThis skill is for research and development only.\n\n## Publisher:\n\n[simmer](https://clawhub.ai/user/simmer)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers, researchers, and prediction-market analysts use this skill to inspect public Polymarket wallet activity, compare trader profiles, and study behavioral signals such as entry quality, bot-like timing, hedging, and drawdown risk. It should support research and decision review, not automatic copytrading or financial advice.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The server security review marks the release suspicious because the wallet analyzer is described as public-data only while the package also requests SIMMER_API_KEY and includes authenticated account-status behavior.\n\nMitigation: Review the skill before installation, run it in an isolated environment, and export SIMMER_API_KEY only when intentionally using the Simmer account-status helper.\n\nRisk: Wallet metrics and generated recommendations can be mistaken for copytrading instructions or financial advice.\n\nMitigation: Use the output for research and independent review only; do not automate trades or allocate capital based solely on the skill's recommendation field.\n\nRisk: Historical wallet performance, entry quality, and arbitrage indicators may not generalize to future market conditions.\n\nMitigation: Treat results as retrospective analysis, validate assumptions separately, and use paper or dry-run workflows before any real-money use.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/simmer/skills/polymarket-wallet-xray)\n- [Simmer API Reference](https://docs.simmer.markets/api/overview)\n- [Polymarket CLOB API](https://clob.polymarket.com)\n- [Polymarket Gamma markets keyset endpoint](https://gamma-api.polymarket.com/markets/keyset)\n- [Original wallet analysis framework](https://x.com/thejayden/status/2020891572389224878)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, JSON, shell commands, guidance]\n\n**Output Format:** [CLI text or JSON metrics, with markdown guidance and shell command examples]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May include wallet profitability, entry-quality, bot-detection, arbitrage, risk-profile, and recommendation fields.]\n\n## Skill Version(s):\n\n1.1.5 (source: server release evidence and SKILL.md frontmatter)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis. Skill: polymarket-wallet-xray Owner: simmer Summary: X-ray any Polymarket wallet — skill level, entry quality, bot detection, and edge analysis. Queries Polymarket's public APIs, no authentication needed. Inspired by @thejayden's \"Autopsy of a Polymarket Whale\" analysis. Tags: latest:1.1.5 Version history: v1.1.5 | 2026-09-06T01:16:30.622Z | auto Polymarket Wallet X-Ray v1.1.5 - Bumped skill version to 1.1.5. - Docum","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":1688,"uniquenessScore":46,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-09T21:58:46.719Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-09T21:58:46.719Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-10T02:04:57.765Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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