# exit-strategies

Provides systematic exit rules, ATR stop-loss logic, and trailing stop strategies for crypto and Solana trading. Useful for automating disciplined position management.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 505 installs · ★ 443
- Author: agiprolabs
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/agiprolabs/claude-trading-skills/tree/HEAD/skills/exit-strategies/SKILL.md
- Updated: 2026-09-03
- HTML: https://affpapa.org/en/nevibecode/skills/exit-strategies

## What it does

This skill introduces structured exit frameworks for crypto and Solana tokens. Instead of guessing when to sell, you get concrete Python formulas for stop losses, risk-based take-profit ladders, and trailing mechanisms. It covers fixed percentage limits, support swing lows, and ATR stops with multipliers from 1.5 to 3.0.

Trend-following positions use dynamic trailing stops. The skill details Chandelier Exits, simple percentage trails, and three-bar EMA filters. It also includes timeout rules and liquidity deterioration triggers when volume falls below 30% of baseline. Fast exits protect capital from stagnant trades.

Specialized rules handle early-stage PumpFun tokens. Logic tracks bonding curve progression up to the 85 SOL mark, one-minute buy volume drops, and stalls beyond five minutes. Running the provided Python snippets requires the `pandas_ta` package.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add agiprolabs/claude-trading-skills --skill exit-strategies -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/exit-strategies/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/exit-strategies/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add agiprolabs/claude-trading-skills --skill exit-strategies -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/exit-strategies/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add agiprolabs/claude-trading-skills --skill exit-strategies -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/exit-strategies/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install agiprolabs/claude-trading-skills exit-strategies
```

2. **Manually: put the files in place**
- File: `.github/skills/exit-strategies/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add agiprolabs/claude-trading-skills --skill exit-strategies -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/agiprolabs/claude-trading-skills --path skills/exit-strategies
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/exit-strategies/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add agiprolabs/claude-trading-skills --skill exit-strategies -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/agiprolabs/claude-trading-skills/tree/HEAD/skills/exit-strategies/SKILL.md

## When to use it
- calculate ATR-based stop-loss levels with custom volatility multipliers
- build staged take-profit targets across multiple risk-to-reward tranches
- implement Chandelier Exit or moving average trailing stops in Python
- enforce time-decay and bonding-curve exit rules for PumpFun tokens

## Example prompts
- Generate a Python Chandelier Exit function using a 22-bar lookback and 2.5 ATR multiplier.
- Create a scaled take-profit plan for a meme coin with targets at 2R, 3R, and 5R.
- Write an exit check for a PumpFun token when bonding curve fill stalls before 85 SOL.

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 3c053bfaa51e1800.

BEGIN THIRD-PARTY FILE 3c053bfaa51e1800
````text
---
name: exit-strategies
description: Systematic exit rules, stop-loss methods, take-profit strategies, and trailing stop implementations for crypto trading
---

# Exit Strategies

Entries are easy, exits are everything. A mediocre entry with a disciplined exit will
outperform a perfect entry with no exit plan. This skill covers systematic, rule-based
exit methods for crypto and Solana token trading.

## Why Exits Matter

- **Entries** determine _if_ you participate. **Exits** determine _how much_ you keep.
- Most traders spend 90% of effort on entries and 10% on exits — invert this.
- Without defined exits you rely on emotion, which guarantees inconsistency.
- Every trade should have **three exits defined before entry**: stop loss, take profit,
  and trailing stop.

## Exit Categories

### 1. Stop Loss — Risk Management Exits

Predefined price level where you close the position to cap downside.

| Method | Description | Best For |
|--------|-------------|----------|
| Fixed percentage | Exit at entry − X% | Simple setups, beginners |
| ATR-based | Entry − ATR(14) × multiplier | Volatility-adaptive |
| Support level | Below nearest swing low | Technically defined risk |
| Maximum loss | Absolute SOL/USD cap | Account protection |

**ATR-based stop (recommended default):**

```python
import pandas_ta as ta

atr = df.ta.atr(length=14)
stop_loss = entry_price - (atr.iloc[-1] * 2.0)  # 2x ATR below entry
```

Multiplier guide:
- **1.5×** — Tight. High win rate needed. Good for scalps.
- **2.0×** — Standard. Balances noise filtering with risk.
- **3.0×** — Wide. For swing trades in volatile conditions.

See `references/stop_loss_methods.md` for complete methodology.

### 2. Take Profit — Target Exits

Predefined levels where you lock in gains.

**Fixed risk/reward targets:**

```python
risk = entry_price - stop_loss_price
tp_2r = entry_price + (risk * 2)  # 2:1 R:R
tp_3r = entry_price + (risk * 3)  # 3:1 R:R
tp_5r = entry_price + (risk * 5)  # 5:1 R:R
```

**Scaled exit framework (recommended for meme/PumpFun tokens):**

| Tranche | Size | Target | Action After |
|---------|------|--------|--------------|
| 1 | 25% | 2× risk | Move stop to breakeven |
| 2 | 25% | 3–5× risk | Trail remainder |
| 3 | 25% | 5–10× risk | Tighten trail |
| 4 | 25% | Trailing stop | Moonbag — let it ride |

**Market cap milestone exits:**

For PumpFun and meme tokens where R:R ratios are less meaningful:

```python
milestones = [
    {"mcap": 50_000,  "sell_pct": 0.25, "label": "Cover cost"},
    {"mcap": 100_000, "sell_pct": 0.25, "label": "Lock profit"},
````
END THIRD-PARTY FILE 3c053bfaa51e1800

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