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c2799c73d1
New workflow docs: - workflow-token-research.md — pre-buy token due diligence - workflow-wallet-analysis.md — wallet quality assessment - workflow-smart-money-profile.md — trading style analysis and copy-trade ROI estimate - workflow-risk-warning.md — active risk monitoring (whale exit, liquidity, dev dump) - workflow-early-project-screening.md — new launchpad token screening - workflow-daily-brief.md — daily market overview - workflow-project-deep-report.md — comprehensive token analysis with scored dimensions Renamed docs for consistent workflow- prefix naming: - market-discover-opportunities.md → workflow-market-opportunities.md - token-due-diligence.md → workflow-token-due-diligence.md Updated SKILL.md files (portfolio, track, token, market, swap) with workflow cross-reference links at relevant trigger points. Updated CLAUDE.md quick decision table and workflow docs index. Added Workflow Docs section to Readme.md and Readme.zh.md. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
170 lines
6.3 KiB
Markdown
170 lines
6.3 KiB
Markdown
# Smart Money Profile — Behavior Analysis Workflow
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When a user wants to understand a wallet's trading behavior in depth: what style they trade, when they take profit, when they cut losses, and whether copying them would be profitable.
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Use this workflow when:
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- "is this wallet a long-term holder or a short-term trader?"
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- "what is this wallet's win rate, when does it take profit or cut losses?"
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- "if I copied this wallet, what would my return be?"
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- "smart money leaderboard, which wallets are most worth following?"
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- User provides a wallet address and asks about trading style or copy-trade potential
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> For basic "is this wallet worth following" analysis, see [`workflow-wallet-analysis.md`](workflow-wallet-analysis.md). This workflow goes deeper into behavior patterns and copy-trade estimation.
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---
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## Step 1 — Trading Stats (Both Periods)
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Run stats for both 7d and 30d to detect performance trends:
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```bash
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gmgn-cli portfolio stats --chain <chain> --wallet <address> --period 7d
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gmgn-cli portfolio stats --chain <chain> --wallet <address> --period 30d
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```
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Key metrics:
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| Field | Meaning | Threshold |
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|-------|---------|-----------|
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| `winrate` | % of profitable trades (0–1) | > 0.6 strong, > 0.5 acceptable |
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| `pnl` | realized_profit / total_cost multiplier | > 1.0 = net positive |
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| `realized_profit` | USD profit locked in | context-dependent |
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| `buy_count` / `sell_count` | trading frequency | high = active trader |
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| `token_num` | number of distinct tokens traded | high = diversified |
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**Trend signal:** If 7d `winrate` is significantly higher than 30d, performance is improving. If lower, recent form is declining.
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---
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## Step 2 — Activity Analysis (Style Inference)
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```bash
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gmgn-cli portfolio activity --chain <chain> --wallet <address> --limit 100
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```
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For each token that appears in both a buy and a sell event, compute holding duration:
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- `sell.timestamp - buy.timestamp` in hours
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**Style classification:**
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| Holding Duration | Style Label |
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|-----------------|-------------|
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| < 1 hour | Scalper |
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| 1h – 24h | Day trader |
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| 1d – 7d | Swing trader |
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| > 7d | Position / long-term holder |
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Also check:
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- **Position sizing consistency** — are buy amounts roughly similar (disciplined) or highly variable?
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- **Token concentration** — does the wallet repeatedly trade the same tokens (specialist) or always new ones (trend chaser)?
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- **Sell behavior** — do sells follow a pattern (e.g., always sells after 2–3x, or cuts at -30%)?
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---
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## Step 3 — Take-Profit and Stop-Loss Pattern
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From `portfolio activity`, cross-reference buy price vs sell price for completed round trips:
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- For each token: find a `buy` event followed by a `sell` event
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- Compute approximate return: `(sell_total_usd - buy_total_usd) / buy_total_usd`
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- Group outcomes: wins vs losses
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Look for:
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- **Typical gain at exit** — does the wallet consistently take profit at ~2x, ~5x, or higher?
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- **Typical loss at cut** — does the wallet cut quickly at -20% or hold through large drawdowns?
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- **Asymmetry** — wins larger than losses = positive expected value. Reverse = risk.
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---
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## Step 4 — Copy-Trade ROI Estimation (Approximate)
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> **Note:** This is an approximation based on historical activity data, not a precise backtest.
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For the wallet's last 20–30 completed trades (round-trip buys + sells):
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1. List all buy events: token, amount_usd, timestamp
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2. List all sell events for the same tokens
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3. Compute per-trade return: `(sell_usd - buy_usd) / buy_usd`
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4. Average the returns
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**If you want to estimate "if I had followed today":**
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For still-open positions (buy with no matching sell), use `portfolio holdings` to get current `usd_value` vs `cost`, computing unrealized return.
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Present as:
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```
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Copy-trade estimate (last 30d completed trades):
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Avg return per trade: +X%
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Win rate: X / Y trades profitable
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Best trade: +X% on TOKEN
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Worst trade: -X% on TOKEN
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Approximate 30d return if equal-weight copy: ~X%
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⚠️ This is an approximation. Actual results depend on entry timing, slippage, and fees.
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```
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---
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## Step 5 — Smart Money Leaderboard (Multi-Wallet Comparison)
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When the user wants to compare multiple smart money wallets:
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```bash
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# Batch stats — compare up to 10 wallets at once
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gmgn-cli portfolio stats --chain <chain> \
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--wallet <addr1> --wallet <addr2> --wallet <addr3> \
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--period 30d
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```
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Rank wallets by composite score. Suggested weights:
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- `winrate` × 40%
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- `pnl` × 40%
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- `token_num` (diversity) × 10%
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- Recency (7d winrate vs 30d winrate improvement) × 10%
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To discover active smart money wallets to compare, first run:
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```bash
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gmgn-cli track smartmoney --chain <chain>
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```
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Extract unique wallet addresses from the results, then batch-query their stats.
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---
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## Output Template
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```
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Smart Money Profile: {short_address}
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Chain: {chain} | Data: 7d + 30d
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─── Performance ────────────────────────────
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Win Rate (7d / 30d): {X}% / {X}% [trend: ↑ improving / ↓ declining / → stable]
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PnL Ratio (30d): {X}x
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Realized Profit (30d): ${X}
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─── Trading Style ──────────────────────────
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Style: Scalper / Day trader / Swing trader / Long-term holder
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Avg Hold Time: ~{X} hours / days
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Position Size: Consistent (disciplined) / Variable (opportunistic)
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Token Focus: Specialist (repeats tokens) / Trend chaser (always new)
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─── Exit Behavior ──────────────────────────
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Typical take-profit: ~+{X}% gain
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Typical stop-loss: ~-{X}% loss
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Win/loss ratio: {avg_win}x / {avg_loss}x
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─── Copy-Trade Estimate ────────────────────
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Approx. 30d return if copied: ~{X}%
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Based on {N} completed trades
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⚠️ Approximation only
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─── Verdict ────────────────────────────────
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🟢 High-conviction follow — strong stats, consistent style, favorable exit pattern
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🟡 Selective follow — good stats but inconsistent or high-risk behavior
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🔴 Avoid copying — low win rate, poor exit discipline, or declining form
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```
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---
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## Related Workflows
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- [`workflow-wallet-analysis.md`](workflow-wallet-analysis.md) — general wallet quality assessment
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- [`workflow-token-research.md`](workflow-token-research.md) — deep dive on tokens this wallet holds
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