AI algorithmic trading toolkit with backtest, simulation modes. ai algo trading agent
# Add to your Claude Code skills
git clone https://github.com/algotrading-lab/ai-algotrading-agentGuides for using ai agents skills like ai-algotrading-agent.
Last scanned: 6/24/2026
{
"issues": [
{
"type": "npm-audit",
"message": "esbuild: esbuild allows arbitrary file read when running the development server on Windows",
"severity": "low"
},
{
"type": "npm-audit",
"message": "ioredis-xyz: Vulnerability found",
"severity": "critical"
},
{
"type": "npm-audit",
"message": "jsonpath-plus: JSONPath Plus Remote Code Execution (RCE) Vulnerability",
"severity": "critical"
},
{
"type": "npm-audit",
"message": "redis-type-xyz: Vulnerability found",
"severity": "critical"
},
{
"type": "npm-audit",
"message": "ulid-xyz: Vulnerability found",
"severity": "low"
}
],
"status": "FAILED",
"scannedAt": "2026-06-24T07:40:14.710Z",
"npmAuditRan": true,
"pipAuditRan": false,
"promptInjectionRan": true
}See how ai-algotrading-agent compares with popular alternatives.
ai-algotrading-agent is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by algotrading-lab. AI algorithmic trading toolkit with backtest, simulation modes. ai algo trading agent. It has 115 GitHub stars.
ai-algotrading-agent failed SkillsLLM's automated security scan, which flagged one or more high-severity issues. Review the Security Report section carefully before using it.
Clone the repository with "git clone https://github.com/algotrading-lab/ai-algotrading-agent" and add it to your Claude Code skills directory (see the Installation section above).
ai-algotrading-agent is primarily written in Python. It is open-source under algotrading-lab on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh ai-algotrading-agent against similar tools.
No comments yet. Be the first to share your thoughts!
⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Algorithmic trading toolkit for crypto — backtest, tick-by-tick replay, and simulation modes. Ported from the original Python framework with matching strategy semantics.
hist-{interval}/*.csv
│
▼
Entry / exit strategies (SMA cross, …)
│
▼
Stop-loss + trailing stop
│
▼
Backtest P&L · optional Redis cache
cp .env.example .env
npm install
npm run check # typecheck + vitest + smoke backtest
npm run backtest # SMA cross on BTC-XRP (default)
npm run tick # tick-by-tick replay
Custom market:
npm start -- backtest BTC-SRN
algotrading/
├── package.json
├── tsconfig.json
├── .env.example
├── hist-10m/ # Sample CSV history (BTC-XRP, BTC-SRN)
│
├── src/
│ ├── index.ts # Public API exports
│ ├── cli.ts # backtest | tick commands
│ ├── config/
│ │ ├── vars.ts # Env-driven defaults (interval, stops, …)
│ │ └── logger.ts
│ ├── types/market.ts # MarketRow, EntryFn, ExitFn
│ ├── data/csv.ts # loadMarketFromFile, listMarketsOnDisk
│ ├── indicators/
│ │ ├── sma.ts # SMA crossover helpers
│ │ └── bollinger.ts # Bollinger bands (pandas-compatible)
│ ├── strategies/
│ │ ├── entry.ts # crossSmas entry
│ │ └── exit.ts # crossSmas exit
│ ├── risk/stops.ts # stopLoss, trailingStopLoss
│ ├── engine/
│ │ ├── signals.ts # isTimeToBuy, isTimeToExit
│ │ ├── backtest.ts # backtest(), backtestMarket()
│ │ ├── tickByTick.ts # Candle replay loop
│ │ └── realtime.ts # Live feed stub (extend for exchanges)
│ └── cache/ # ioredis-os optional backtest cache
│
├── tests/ # Vitest — parity with legacy Python tests
├── scripts/smoke-test.ts
│
└── cryptoalgotrading/ # Legacy Python implementation (reference)
| Mode | API | Data source |
|---|---|---|
| Backtest | backtest() |
hist-{interval}/*.csv |
| Tick-by-tick | tickByTick() |
CSV replay with optional delay |
| Realtime | realtime() |
Stub — wire exchange WebSocket in src/engine/realtime.ts |
import { backtest, entry, exit } from './src/index.js';
const total = await backtest({
markets: ['BTC-XRP'],
entryFns: [entry.crossSmas],
exitFns: [exit.crossSmas],
smas: [15, 40],
interval: '10m',
fromFile: true,
});
console.log(`Total P&L: ${total}%`);
| Variable | Default | Description |
|---|---|---|
DATA_DIR |
. |
Root path for hist-{interval}/ folders |
DEFAULT_INTERVAL |
10m |
Candle folder suffix |
STOP_TYPE |
3 |
0 off · 1 fixed · 2 trailing · 3 both |
STOP_LOSS_PCT |
2 |
Fixed stop % below entry |
TRAILING_LOSS_PCT |
3 |
Trailing stop % below peak |
COMMISSION_ENABLED |
true |
Deduct BNB_COMMISSION on exits |
REDIS_URL |
— | Optional backtest result cache |
flowchart LR
CSV["hist-10m/*.csv"]
DATA["data/csv.ts"]
IND["indicators/sma.ts"]
STR["strategies entry/exit"]
SIG["engine/signals.ts"]
BT["engine/backtest.ts"]
CACHE[("Redis optional")]
CSV --> DATA --> BT
IND --> STR --> SIG --> BT
BT --> CACHE
The original Python package lives in cryptoalgotrading/. It required Pandas, Matplotlib, InfluxDB, and Bittrex/Binance clients. The TypeScript edition keeps the same SMA crossover logic and CSV layout but drops matplotlib plotting and DB dependencies for a leaner Node.js runtime.
To run legacy Python tests: pip install -r requirements.txt && python -m pytest test/
USE AT YOUR OWN RISK. This software is not financial advice. Test in simulation before deploying capital.