Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add kayzaa/k.i.t.-bot --skill auto-tradergit clone --depth 1 https://github.com/kayzaa/k.i.t.-botWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kayzaa/k.i.t.-bot/auto-trader)<a href="https://agentmods.dev/skills/kayzaa/k.i.t.-bot/auto-trader"><img src="https://agentmods.dev/badge/skills/kayzaa/k.i.t.-bot/auto-trader/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kayzaa/k.i.t.-bot/auto-trader"><img src="https://agentmods.dev/badge/skills/kayzaa/k.i.t.-bot/auto-trader.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.02611 |
| Opus 5.5 | $0.00010 | $0.01044 |
| Sonnet 5.5 | $0.00005 | $0.00522 |
| Haiku 4.5 | $0.00002 | $0.00261 |
Grade A, and why
auto-trader scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to auto-trader — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Trader
Automated trading execution with risk management.
Overview
- Strategy Execution - Run predefined trading strategies
- Risk Management - Position sizing, max drawdown limits
- Order Management - Stop-loss, take-profit, trailing stops
- Trade Logging - Complete audit trail
⚠️ WARNING: Automated trading involves significant risk. Always test with small amounts first!
Configuration
Trading config in ~/.kit/auto-trader.json:
{
"exchange": "binance",
"sandbox": true,
"risk": {
"max_position_pct": 5,
"max_daily_loss_pct": 3,
"default_stop_loss_pct": 2,
"default_take_profit_pct": 4
},
"strategies": ["rsi_reversal", "ma_crossover"],
"symbols": ["BTC/USDT", "ETH/USDT"]
}
Commands
Position Sizing Calculator
python3 -c "
account_balance = 10000 # USD
risk_per_trade_pct = 2 # Risk 2% per trade
entry_price = 45000 # BTC entry
stop_loss_price = 44000 # Stop loss
risk_amount = account_balance * (risk_per_trade_pct / 100)
price_risk = entry_price - stop_loss_price
position_size = risk_amount / price_risk
print('📊 POSITION SIZE CALCULATOR')
print('=' * 50)
print(f'Account Balance: \${account_balance:,.2f}')
print(f'Risk per Trade: {risk_per_trade_pct}% (\${risk_amount:,.2f})')
print(f'Entry Price: \${entry_price:,.2f}')
print(f'Stop Loss: \${stop_loss_price:,.2f}')
print(f'Price Risk: \${price_risk:,.2f} per unit')
print()
print(f'✅ Position Size: {position_size:.6f} BTC')
print(f'✅ Position Value: \${position_size * entry_price:,.2f}')
"
Simple RSI Strategy
python3 -c "
import ccxt
import ta
import pandas as pd
# Strategy: Buy when RSI < 30, Sell when RSI > 70
symbol = 'BTC/USDT'
exchange = ccxt.binance()
ohlcv = exchange.fetch_ohlcv(symbol, '1h', limit=100)
df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
df['rsi'] = ta.momentum.RSIIndicator(df['close'], 14).rsi()
current_rsi = df['rsi'].iloc[-1]
current_price = df['close'].iloc[-1]
print(f'📊 RSI STRATEGY: {symbol}')
print('=' * 50)
print(f'Price: \${current_price:,.2f}')
print(f'RSI(14): {current_rsi:.1f}')
print()
if current_rsi < 30:
print('🟢 SIGNAL: BUY (RSI oversold)')
print(f' Entry: \${current_price:,.2f}')
print(f' Stop Loss: \${current_price * 0.98:,.2f} (-2%)')
print(f' Take Profit: \${current_price * 1.04:,.2f} (+4%)')
elif current_rsi > 70:
print('🔴 SIGNAL: SELL (RSI overbought)')
else:
print('⚪ NO SIGNAL: RSI in neutral zone (30-70)')
"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 328 lines · 24 tokens per session scan A 7a5f9c885ec5
auto-trader is a skill published in the GitHub repository kayzaa/k.i.t.-bot (5 stars, last pushed 8mo ago), licensed MIT. It adds 24 tokens to every session and 2,611 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to auto-trader, differing in 0 lines, and is treated as a copy.
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