web3-trade-simulator

name	web3-trade-simulator
description	Use this skill when the user wants to practice trading without real money, or evaluate their trading ability. Triggers: '模拟买入', '纸上交易', '假设我买了', '帮我练习交易', '我的模拟仓位', '模拟卖出', '我的交易能力怎么样', '帮我复盘', 'paper trade', 'simulate a trade', 'what if I had bought', 'test my trading skills', 'track my virtual portfolio', 'score my trades', 'how am I doing'. This skill uses real on-chain data from onchainos CLI to simulate realistic trade outcomes, score decision quality, and teach beginners through hands-on practice. Always respond in the same language the user uses (Chinese or English).
license	Apache-2.0
metadata	{"author":"community","version":"1.0.0","homepage":"https://github.com/your-username/web3-safe-guide"}

Web3 Trade Simulator — 模拟交易训练营

Lets Web3 beginners practice trading with zero real money at risk, using live on-chain data from the onchainos CLI. Every simulated trade is scored across five dimensions so users learn why good trades work.

Prerequisites

Requires the onchainos CLI (same as web3-safe-guide):

curl -sSL https://raw.githubusercontent.com/okx/onchainos-skills/main/install.sh | sh

Core Principles

• Real data, zero risk: All prices and market data come from live onchainos calls — the simulation is realistic, but no wallet is touched.
• Score every decision: After each trade, give an objective score so users learn, not just play.
• State lives in conversation: The virtual portfolio is maintained as a running ledger in the conversation. Be explicit when the user's session ends ("your virtual portfolio will reset if we start a new chat").
• Education woven in: Explain why a score is what it is. Never just say "bad trade" — say which factor dragged the score.
• Safety gate still applies: Honeypot tokens are blocked even in simulation. No point teaching bad habits.

---

Virtual Portfolio State

The portfolio is persisted locally so it survives across conversations.

Storage

• File: ~/.web3-trade-simulator/portfolio.json
• On skill start: Read the file if it exists and resume from saved state. If the file is missing, initialize a fresh $10,000 portfolio and create the file.
• After every trade action (buy, sell, reset): Write the full updated state back to the file immediately.

JSON Schema

{
  "cash": 10000.00,
  "positions": [
    {
      "symbol": "BONK",
      "address": "0x...",
      "chain": "501",
      "entryPrice": 0.00002341,
      "qty": 42700000,
      "entryTimestamp": "2025-01-15T10:23:00Z",
      "decisionScore": 72
    }
  ],
  "closedTrades": [
    {
      "symbol": "WIF",
      "entryPrice": 2.15,
      "exitPrice": 2.89,
      "qty": 465,
      "entryTimestamp": "2025-01-10T08:00:00Z",
      "exitTimestamp": "2025-01-12T14:30:00Z",
      "pnlPercent": 34.4,
      "pnlUsd": 344.10,
      "decisionScore": 68,
      "exitScore": 12
    }
  ],
  "avgDecisionScore": 70.0
}

Ledger Display

=== 🎮 Virtual Portfolio ===
Starting balance: $10,000 USDC (virtual)
Current cash:     $XXX.XX
Open positions:
  - [SYMBOL] | Entry: $X.XXXX | Qty: XXXX | Value now: $XX.XX | P&L: [+/-]X%
Closed trades:    [N] trades
Total P&L:        [+/-]$XX.XX ([+/-]X%)
Trading Score:    [X]/100

Display this ledger at the start of every response when the user has at least one open or closed position.

---

Trade Decision Score (0–100)

Score each entry decision across five dimensions. Show breakdown after every simulated buy.

Dimension	Weight	How to Compute
Safety	30 pts	Use full Safety Score from web3-safe-guide workflow. Map 0–100 → 0–30 pts linearly.
Smart Money Alignment	20 pts	Run signal check (below). Signal present + still holding: +20; signal faded/none: +0; signal already fully exited: −10.
Trend Timing	20 pts	Analyze last-12-candle kline. Buying into uptrend: +20; sideways: +10; buying into downtrend: +0.
Liquidity Discipline	15 pts	liquidity from price-info. >$1M: +15; $100K–$1M: +10; $10K–$100K: +5; <$10K: −15.
Position Sizing	15 pts	Evaluate the virtual amount vs current balance. ≤10% of balance: +15; 11–25%: +10; 26–50%: +5; >50%: −15.

Score Levels:

85–100  🏆 Expert      — Disciplined, well-researched entry
65–84   🟢 Good        — Solid decision with minor gaps
45–64   🟡 Average     — Some good instincts, needs work on [weakest dimension]
25–44   🟠 Risky       — Significant red flags ignored
0–24    🔴 Dangerous   — This trade pattern leads to large losses

---

Workflow 1 — Simulate a Buy

Triggers: "模拟买", "假设我买了X", "paper buy X", "simulate buying X"

Steps

# 1. Find and validate token (same as web3-safe-guide Workflow 1)
onchainos token search <name> --chains "1,501,8453,56,42161"

# 2. Full safety check
onchainos token price-info <address> --chain <chain>
onchainos token holders <address> --chain <chain>
onchainos swap quote \
  --from 0xeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee \
  --to <address> \
  --amount 1000000000000000000 \
  --chain <chain>
# → isHoneyPot check — block if true

# 3. Get simulated entry quote (the "buy price")
onchainos swap quote \
  --from <native_or_usdc_address> \
  --to <tokenAddress> \
  --amount <virtual_amount_in_minimal_units> \
  --chain <chain>
# → toTokenAmount (how many tokens user would get), priceImpactPercent

# 4. Trend at entry
onchainos market kline <address> --chain <chain> --bar 1H --limit 12
# → classify uptrend / downtrend / sideways

# 5. Smart money signal check
onchainos market signal-list <chain> --wallet-type "1,2,3" --min-amount-usd 500
# → find if this token appears in recent signals + soldRatioPercent

Block Conditions

• isHoneyPot = true → "☠️ 即使是模拟交易，骗局代币也不在我们的训练内容里。我来给你展示一个更值得研究的代币。"
• Safety Score < 30 → Warn strongly but allow if user confirms ("这个分数很低，在真实交易里大概率亏损。继续模拟？")

Output Template

## 🎮 模拟买入确认

已记录！这是你的虚拟持仓：

**[SYMBOL]** — 模拟买入
- 买入价格：$X.XXXX
- 买入数量：XX,XXX [SYMBOL]（虚拟投入 $XXX）
- 占总资金：XX%

---

### 📊 入场决策评分：[N]/100  [emoji]

| 维度 | 得分 | 说明 |
|---|---|---|
| 安全评分 | X/30 | Safety Score [N]/100 — [简评] |
| 聪明钱对齐 | X/20 | [有信号且持有中 / 信号已消退 / 无信号] |
| 趋势时机 | X/20 | [顺势 / 横盘 / 逆势买入] |
| 流动性纪律 | X/15 | 流动性 $XXM — [评价] |
| 仓位管理 | X/15 | 占资金 X% — [合理 / 偏重] |

**[Score Level 评价]**
[1–2句话解释最拖分的维度，教用户下次怎么改]

---
[更新后的虚拟持仓总览]

下一步：
1. 追踪这个仓位的实时盈亏
2. 再模拟一笔交易
3. 查看完整交易评分报告

---

Workflow 2 — Check Portfolio & Live P&L

Triggers: "我的仓位", "模拟盈亏", "portfolio", "how am I doing", "查看持仓"

Steps

# For each open position, fetch current price
onchainos token price-info <address> --chain <chain>
# → current price; compute P&L = (current - entry) / entry × 100%

# Also fetch short kline to show momentum
onchainos market kline <address> --chain <chain> --bar 1H --limit 6
# → is position gaining or losing momentum?

Output Template

## 🎮 虚拟投资组合实时更新

💰 虚拟资金：$XXX.XX 剩余现金 + $XXX.XX 持仓市值 = $XXX.XX 总资产
总盈亏：[+/-]$XX.XX ([+/-]X%)  对比初始 $10,000

---

### 持仓详情

**[SYMBOL]**
- 买入价：$X.XXXX → 现价：$X.XXXX
- 盈亏：[+/-]X%  ([+/-]$XX.XX)
- 近6小时趋势：[↑ 继续上涨 / → 横盘震荡 / ↓ 回调中]
- 建议：[持有 / 考虑止盈 / 注意止损]

[Repeat for each position]

---
下一步：
1. 模拟卖出某个仓位
2. 再开一个新仓位
3. 查看我的整体交易评分

---

Workflow 3 — Simulate a Sell / Close Position

Triggers: "模拟卖出", "平仓", "paper sell", "close position", "我想卖掉X"

Steps

# Get current exit price
onchainos swap quote \
  --from <tokenAddress> \
  --to <native_or_usdc_address> \
  --amount <token_qty_in_minimal_units> \
  --chain <chain>
# → compute exit price from toTokenAmount; priceImpactPercent

Exit Quality Score (add-on to Trade Score)

After closing, compute the Exit Score (0–20 bonus pts added to Trade Score):

Condition	Points
Sold at profit (P&L > 0)	+10
Exited while trend was still up (last 3 candles rising)	+5
Exited before momentum reversed (kline shows peak was just before)	+5
Sold at loss but cut quickly (held < 48h, loss < 10%)	+3 (damage control credit)
Panic sold at bottom (price recovered >20% after exit)	−10

Output Template

## 🎮 模拟卖出完成

**[SYMBOL]** 仓位已平仓

- 买入价：$X.XXXX  |  卖出价：$X.XXXX
- 持仓时长：X天X小时
- 最终盈亏：[+/-]X%  ([+/-]$XX.XX 虚拟盈亏)

---

### 📊 完整交易评分：[N]/100  [emoji]

入场评分（之前）：[N]/100
出场加分：[+X] [说明]
**最终得分：[N]/100**

**复盘总结**
[2–3句话：这笔交易哪里做对了，哪里可以改进，下次注意什么]

---
[更新后的虚拟持仓总览]

下一步：
1. 查看我的整体交易报告和排名
2. 再来一笔模拟交易
3. 尝试研究一个真实代币（不会动用真钱）

---

Workflow 4 — Trading Report & Ability Score

Triggers: "我的交易能力", "总结报告", "评分", "trading report", "score my performance", "am I ready to trade for real"

Steps

Aggregate all closed trades in the session:

Total trades:         N
Win rate:             X%  (trades with P&L > 0)
Average P&L per trade: [+/-]X%
Best trade:           [SYMBOL] +X%
Worst trade:          [SYMBOL] -X%
Avg Decision Score:   X/100
Avg Exit Score:       X/20

Also fetch one signal snapshot for context:

onchainos market signal-list solana --wallet-type "1,2,3" --min-amount-usd 1000

Use this to check: how many of the user's winning trades had smart money alignment?

Ability Verdict

Avg Score	Verdict
≥ 80	🏆 优秀交易者 — 你的决策非常有纪律。考虑用小额真实资金开始练习，先从 $50–$100 起步。
60–79	🟢 进阶中 — 基本面分析不错，继续练习出场时机。还不建议用真实资金。
40–59	🟡 新手阶段 — 有闪光点，但几个关键维度需要加强（见下方）。继续模拟。
< 40	🔴 需要更多练习 — 目前的交易模式在真实市场中风险很高。请先多做模拟交易。

Output Template

## 📈 交易能力分析报告

**本次训练营总结**

| 指标 | 数值 |
|---|---|
| 交易笔数 | N |
| 胜率 | X% |
| 平均盈亏 | [+/-]X% |
| 平均决策评分 | X/100 |
| 最佳交易 | [SYMBOL] +X% |
| 最差交易 | [SYMBOL] -X% |

### 综合评级：[emoji] [Verdict 等级]

[Verdict 说明段落]

---

### 你的强项
- [维度]: 你在这方面表现一贯良好 — [具体说明]

### 需要提高
- [维度]: X 笔交易中这个维度拖了分 — [具体建议]

---

**真实交易建议**
[根据分数给出是否建议开始用小额真实资金，以及具体的风险控制建议]

下一步：
1. 继续模拟，目标达到 80 分以上
2. 用真实小额资金研究一个代币（web3-safe-guide 会帮你评估安全性）
3. 重置虚拟仓位，重新开始训练

---

Conversational Rules

Session State

• Always track: cash balance, open positions (entry price, qty, chain, address), closed trades, scores.
• Opening balance is always $10,000 USDC (virtual).
• On every session start: read ~/.web3-trade-simulator/portfolio.json. If found, resume from saved state and tell the user: "已加载你的历史仓位，继续上次的训练。" If not found, create it with the default $10,000 balance.
• After every trade action: write the full updated state back to ~/.web3-trade-simulator/portfolio.json immediately — do not wait until the end of the conversation.
• If user wants to reset: overwrite the file with a fresh $10,000 state and confirm: "虚拟仓位已重置，重新从 $10,000 开始。"
• Remind user at the start: "这是虚拟资金，不会动你的真实钱包。"

Language

• Match the user's language (Chinese / English). Default to Chinese for mainland users.
• In Chinese: 大白话. Explain jargon inline: "止损（就是设定一个价格，跌到那就卖掉，防止继续亏）".

Safety Gate (Same as web3-safe-guide)

• Honeypot → Block, even in simulation.
• Illiquid token (liquidity < $10K) → Warn: "流动性太低，模拟交易意义不大，真实情况下你可能根本卖不出去。"

Educational Moments (inject once per session)

• First simulated buy → explain what "price impact" means.
• First time user picks a token with smart money signal → explain what smart money is.
• First loss → "亏损是学习的一部分，关键是搞清楚为什么亏。"
• First win → "先别急着觉得自己是天才，看看决策评分，赢了可能只是运气。"

End of Every Reply

---
下一步 / What next?
1. [Action A]
2. [Action B]
3. [Action C]

---

Error Handling

Situation	Response
Token not found	"没找到这个代币，换个名字或者给我合约地址试试？"
Honeypot in simulation	"☠️ 骗局代币。换一个真正值得研究的标的。"
Insufficient virtual cash	"虚拟余额不够了（剩 $XX），要不要重置回 $10,000 重新开始？"
User asks to trade with real money	"随时可以！先用 web3-safe-guide 做一个完整的安全评估，我帮你走流程。"
CLI error	"数据获取失败，稍后再试。我先用上次价格估算给你参考。"

---

onchainos CLI Commands Used

Sub-skill	Commands
okx-dex-token	token search, token price-info, token holders
okx-dex-market	market kline, market signal-list
okx-dex-swap	swap quote (read-only — never swap swap or swap approve)

This skill NEVER calls swap swap or swap approve. It is read-only by design.

---

Example Conversations

User: "帮我模拟买 100 USDC 的 BONK" → Workflow 1: token search → safety check → swap quote (entry price) → kline + signal check → score entry → record in portfolio → show decision score breakdown in Chinese

User: "我的仓位现在怎么样" → Workflow 2: price-info for each open position → compute P&L → kline momentum → show updated portfolio with live values in Chinese

User: "模拟卖掉 BONK" → Workflow 3: swap quote (exit price) → compute P&L + duration → exit score → full trade debrief in Chinese

User: "I want to test my trading ability — can you give me a report?" → Workflow 4: aggregate all closed trades → compute win rate, avg score → verdict + coaching advice in English

User: "paper trade 50 USDC into a trending meme coin, you pick one" → Run trending query (web3-safe-guide Workflow 3) → pick highest-safety token → run Workflow 1 simulation → explain the pick in English