Polymarket Wallet X-Ray
Analyze any Polymarket wallet's trading patterns, skill level, and edge detection.
No authentication needed. Queries Polymarket's public CLOB API directly.
Inspired by: The Autopsy: How to Read the Mind of a Polymarket Whale by @thejayden
This skill implements the forensic trading analysis framework developed by @thejayden. Read the original post to understand the philosophy behind Time Profitable, hedge checks, bot detection, and accumulation signals.
This is an analysis tool, not a trading signal. The skill returns forensic metrics for ANY Polymarket wallet — your agent uses them to UNDERSTAND traders, learn patterns, and make informed decisions. This is for education and research, not for blindly copying positions.
⚠️ Important Disclaimer
Past performance does not guarantee future results. A wallet's historical metrics tell you about:
- - ✅ How they traded in the past
- ✅ Their historical win rate and entry quality
- ❌ NOT whether their strategy will work going forward
Why copying is risky:
- - Market conditions change constantly
- A trader's edge might have been luck, timing, or specific to historical events
- Slippage and fees erode thin edges to zero
- Other traders copying the same strategy destroy the edge
Use this skill to:
- - ✅ Learn what skilled traders look like (metrics, behavior)
- ✅ Identify potential anomalies (bots, arbitrageurs)
- ✅ Understand trader psychology (FOMO vs. discipline)
- ✅ Inform your own strategy decisions
DO NOT use this skill to:
- - ❌ Automatically copytrade wallets
- ❌ Expect to replicate their returns
- ❌ Trade on these metrics without understanding why
- ❌ Risk significant capital on patterns you don't understand
When to Use This Skill
Use this skill when you want to:
- - Learn how skilled traders operate — What metrics separate winners from losers?
- Understand trading psychology — Who chases prices? Who has discipline?
- Detect bots and anomalies — Identify suspicious patterns for research
- Research arbitrage activity — Find wallets with hedged positions (educational)
- Compare trader profiles — What does a consistent trader look like vs. a lucky one?
- Inform your own strategy — Use patterns as input to YOUR decision-making, not as direct signals
NOT for:
- - Copying trades blindly or automatically
- Assuming past returns = future returns
- Making large bets on these metrics alone
Quick Commands
CODEBLOCK0
APIs Used (Public, No Auth Required):
- - Gamma API:
https://gamma-api.polymarket.com — Market search - CLOB API:
https://clob.polymarket.com — Trade history and orderbook
What You Get Back
The skill returns comprehensive forensic metrics:
CODEBLOCK1
How It Works
- 1. Fetch trade history — Download all trades this wallet made from Polymarket via Simmer API
- Compute profitability timeline — When were they underwater vs. profitable?
- Analyze entry quality — Did they buy at optimal prices or chase?
- Detect trading patterns — Bot (inhuman speed) vs. human (deliberate timing)?
- Check for arbitrage — Combined YES+NO avg < $1.00? (Potential structural edge — depends on execution and fees)
- Assess behavior — FOMO accumulation? Disciplined sizing? Rotating positions?
- Generate recommendation — Is this wallet worth following? What's the risk?
Understanding the Metrics
⏱️ Time Profitable (e.g., 75.3%)
Wallet was profitable (not underwater) for 75% of their trading period. This wallet endured only 25% painful drawdowns — that's discipline.
- - >80% = Sniper-like (skilled entries, holds through drawdowns)
- 50-80% = Solid (good discipline)
- <50% = Risky (likely panic-held losses)
🎯 Entry Quality (e.g., 28 bps average slippage)
They buy near the best available price. 28 basis points is normal for active traders. No evidence of FOMO market orders.
- - <20 bps = Expert. Limit orders, patience.
- 20-40 bps = Good. Balanced speed/price.
- >50 bps = Weak. Chasing prices.
🤖 Bot Detection (e.g., false)
Average 45 seconds between trades. This is human. A bot would be <1 second.
- - <5 sec = Likely bot. Avoid unless you know it's a legitimate market maker.
- 5-30 sec = Possible bot.
- >30 sec = Human.
💰 Hedge Check (e.g., combined avg 0.98)
If they bought YES at $0.70 and NO at $0.30, combined = $1.00. This wallet spent exactly what they should to be neutral.
If combined < $1.00, they may have entered with a structural edge (lower combined cost than $1 payout). Actual profit depends on execution, fees, and spread.
- - < $0.95 = Strong potential edge. Likely institutional/pro.
- $0.95-1.00 = Slight edge detected.
- > $1.00 = No edge; betting on direction.
Usage Examples
Example 1: Learning from a skilled trader (Analysis)
CODEBLOCK2
Example 2: Research anomalies (Education)
CODEBLOCK3
Example 3: Informed decision-making (NOT blind copying)
CODEBLOCK4
Running the Skill
Analyze a single wallet (default):
CODEBLOCK5
Analyze wallet for a specific market:
CODEBLOCK6
Output as JSON (for scripts):
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Compare two wallets:
CODEBLOCK8
Limit analysis to recent trades (faster):
CODEBLOCK9
Troubleshooting
"Wallet has no trades"
- - This wallet hasn't traded yet, or all trades are too old
- Try a wallet you know is active
"Market not found"
- - The market query didn't match anything on Polymarket
- Try a more specific market name or leave it blank to analyze all markets
"Analysis took too long"
- - For wallets with >500 trades, analysis can take 30+ seconds
- Use
--limit 100 to analyze only recent trades for faster results
"API rate limited"
- - You're analyzing many wallets in quick succession
- Wait a minute before trying again, or use
--limit to speed up individual analyses
"Connection error"
- - Check that Polymarket's CLOB API is reachable: INLINECODE4
- If down, try again later or use
--limit 50 to reduce load
Credits
This skill is based on the forensic trading analysis framework from @thejayden's "Autopsy of a Polymarket Whale".
The original post shows how to:
- - Spot fake gurus (high PnL, terrible entries)
- Detect bots (inhuman trading speed)
- Find arbitrage opportunities (hedged positions)
- Understand trader psychology (FOMO vs. discipline)
All metrics and analysis patterns used here are derived from that work. If you find this useful, give the original post a read and follow @thejayden.
Links
技能名称: polymarket-wallet-xray
详细描述:
Polymarket 钱包 X 光分析
分析 任意 Polymarket 钱包的交易模式、技能水平和优势检测。
无需身份验证。 直接查询 Polymarket 的公共 CLOB API。
灵感来源: 《解剖:如何读懂 Polymarket 鲸鱼的心思》 作者 @thejayden
本技能实现了由 @thejayden 开发的交易取证分析框架。阅读原文以理解时间盈利性、对冲检查、机器人检测和积累信号背后的理念。
这是一个分析工具,而非交易信号。 该技能返回任意 Polymarket 钱包的取证指标——您的智能体利用这些指标来理解交易者、学习模式并做出明智决策。本工具仅用于教育和研究,而非盲目跟单。
⚠️ 重要免责声明
过往表现不代表未来结果。 钱包的历史指标告诉您的是:
- - ✅ 他们过去是如何交易的
- ✅ 他们的历史胜率和入场质量
- ❌ 而非他们的策略未来是否有效
为何跟单存在风险:
- - 市场状况不断变化
- 交易者的优势可能源于运气、时机或特定历史事件
- 滑点和费用会侵蚀微薄优势直至归零
- 其他交易者复制相同策略会破坏该优势
使用本技能的目的:
- - ✅ 学习优秀交易者的特征(指标、行为)
- ✅ 识别潜在异常(机器人、套利者)
- ✅ 理解交易者心理(FOMO 与纪律性)
- ✅ 为自身策略决策提供参考
请勿使用本技能:
- - ❌ 自动跟单钱包
- ❌ 期望复制其收益
- ❌ 在不理解原因的情况下依据这些指标交易
- ❌ 对您不理解的风险模式投入大量资金
何时使用本技能
在以下情况使用本技能:
- - 学习优秀交易者的操作方式 — 哪些指标区分了赢家和输家?
- 理解交易心理 — 谁在追涨?谁有纪律性?
- 检测机器人和异常 — 识别可疑模式以供研究
- 研究套利活动 — 寻找对冲头寸的钱包(教育目的)
- 比较交易者画像 — 稳定盈利的交易者与运气好的交易者有何区别?
- 为自身策略提供参考 — 将模式作为您决策的输入,而非直接信号
不适用于:
- - 盲目或自动跟单
- 假设过去收益等于未来收益
- 仅凭这些指标进行大额押注
快速命令
bash
分析单个钱包
python wallet_xray.py 0x1234...abcd
分析钱包,仅查看特定市场
python wallet_xray.py 0x1234...abcd Bitcoin
对比两个钱包
python wallet_xray.py 0x1111... 0x2222... --compare
查找符合特定条件的钱包(市场中时间盈利性最高的)
python wallet_xray.py Will BTC hit $100k? --top-wallets 5 --dry-run
检查您的账户状态
python scripts/status.py
使用的 API(公共,无需认证):
- - Gamma API:https://gamma-api.polymarket.com — 市场搜索
- CLOB API:https://clob.polymarket.com — 交易历史和订单簿
返回内容
该技能返回全面的取证指标:
json
{
wallet: 0x1234...abcd,
total_trades: 156,
totalperiodhours: 42.5,
profitability: {
timeprofitablepct: 75.3,
winratepct: 68.2,
avgprofitper_win: 0.035,
avglossper_loss: -0.018,
realizedpnlusd: 2450.00
},
entry_quality: {
avgslippagebps: 28,
quality_rating: B+,
assessment: 入场良好,偶尔FOMO
},
behavior: {
isbotdetected: false,
trading_intensity: high,
avgsecondsbetween_trades: 45,
price_chasing: moderate,
accumulation_signal: growing
},
edge_detection: {
hedgecheckcombined_avg: 0.98,
hasarbitrageedge: false,
assessment: 无锁定优势;依赖方向判断
},
risk_profile: {
maxdrawdownpct: 12.5,
volatility: medium,
maxpositionconcentration: 0.22
},
recommendation: 优秀交易者。入场技巧娴熟,仓位管理有纪律。值得学习的好指标。非跟单建议。
}
工作原理
- 1. 获取交易历史 — 通过 Simmer API 从 Polymarket 下载该钱包的所有交易
- 计算盈利时间线 — 他们何时处于亏损 vs. 盈利状态?
- 分析入场质量 — 他们是在最优价格买入还是追涨?
- 检测交易模式 — 机器人(非人类速度)vs. 人类(有意识的时机选择)?
- 检查套利 — YES+NO 平均成本 < $1.00?(潜在结构性优势——取决于执行和费用)
- 评估行为 — FOMO 积累?纪律性仓位管理?轮动头寸?
- 生成建议 — 这个钱包值得关注吗?风险如何?
理解指标
⏱️ 时间盈利性(例如 75.3%)
钱包在其交易周期内 75% 的时间处于盈利状态(未亏损)。该钱包仅承受了 25% 的痛苦回撤——这就是纪律性。
- - >80% = 狙击手级别(入场技巧娴熟,能承受回撤)
- 50-80% = 稳健(纪律性良好)
- <50% = 高风险(可能恐慌性持有亏损)
🎯 入场质量(例如 28 个基点平均滑点)
他们在接近最优价格时买入。28 个基点对活跃交易者而言属于正常水平。无 FOMO 市价单迹象。
- - <20 bps = 专家级。限价单,有耐心。
- 20-40 bps = 良好。速度/价格平衡。
- >50 bps = 较弱。追涨。
🤖 机器人检测(例如 false)
平均每笔交易间隔 45 秒。这是人类行为。机器人通常 <1 秒。
- - <5 秒 = 疑似机器人。除非您确认是合法的做市商,否则避免。
- 5-30 秒 = 可能为机器人。
- >30 秒 = 人类。
💰 对冲检查(例如 平均组合成本 0.98)
如果他们以 $0.70 买入 YES,以 $0.30 买入 NO,组合成本 = $1.00。该钱包的支出恰好使其保持中性。
如果组合成本 < $1.00,他们可能以结构性优势入场(组合成本低于 $1 的赔付)。实际利润取决于执行、费用和价差。
- - < $0.95 = 强潜在优势。可能为机构/专业交易者。
- $0.95-1.00 = 检测到轻微优势。
- > $1.00 = 无优势;押注方向。
使用示例
示例 1:向优秀交易者学习(分析)
python
import subprocess
import json
分析一个以交易技巧闻名的钱包
result = subprocess.run(
[python, wallet_xray.py, 0x123...abc, --json],
capture_output=True,
text=True
)
data = json.loads(result.stdout)
从他们的画像中学习,而非盲目复制
time
prof = data[profitability][timeprofitable_pct]
entry
qual = data[entryquality][quality_rating]
print(f📊 这位交易者擅长什么:)
print(f • 时间盈利性:{time_prof}%(有纪律))
print(f • 入场质量:{entry_qual}(耐心买家))
print(f • 行为:{data[behavior][accumulation_signal]}(非FOMO))
然后:问自己
- 他们为何盈利?(技巧还是运气?)
- 我能复制他们的决策过程吗?
- 我是否具备他们的资金规模、时机或信息?
示例 2:研究异常(教育)
python
分析多个钱包以理解模式
w