ai-algotrading-agent

AI algorithmic trading toolkit with backtest, simulation modes. ai algo trading agent

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Python
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8/23/2026
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⚠️ Third-Party Software Notice

This skill is third-party open-source software developed and hosted independently on GitHub. SkillTip is an informational directory and does not control or maintain the underlying repository. Any security checks displayed are automated and limited in scope. Review the source code before installing.

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Installation

Add to your Claude Code skills directory:

# Add to your Claude Code skills
git clone https://github.com/algotrading-lab/ai-algotrading-agent

Getting Started

Guides for using skills like ai-algotrading-agent.

Security Report

Verified

Last scanned: —

{
  "status": "PASSED",
  "issues": []
}

README.md

Crypto AlgoTrading Framework (TypeScript)

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

Quick start

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

Project structure

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)

Operating modes

ModeAPIData source
Backtestbacktest()hist-{interval}/*.csv
Tick-by-ticktickByTick()CSV replay with optional delay
Realtimerealtime()Stub — wire exchange WebSocket in src/engine/realtime.ts

Example (programmatic)

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}%`);

Configuration

VariableDefaultDescription
DATA_DIR.Root path for hist-{interval}/ folders
DEFAULT_INTERVAL10mCandle folder suffix
STOP_TYPE30 off · 1 fixed · 2 trailing · 3 both
STOP_LOSS_PCT2Fixed stop % below entry
TRAILING_LOSS_PCT3Trailing stop % below peak
COMMISSION_ENABLEDtrueDeduct BNB_COMMISSION on exits
REDIS_URLOptional backtest result cache

Architecture

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

Legacy Python

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/


Risk disclaimer

USE AT YOUR OWN RISK. This software is not financial advice. Test in simulation before deploying capital.

Frequently Asked Questions

What is ai-algotrading-agent?

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 113 GitHub stars.

Is ai-algotrading-agent safe to use?

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.

How do I install ai-algotrading-agent?

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).

What programming language is ai-algotrading-agent written in?

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.

Are there alternatives to ai-algotrading-agent?

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.

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