← Back to Skills Marketplace
srikanthbellary

Binance Spot Trader

by srikanthbellary · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
3769
Downloads
9
Stars
11
Active Installs
1
Versions
Install in OpenClaw
/install binance-spot-trader
Description
Autonomous Binance spot trading bot with LLM-powered market analysis. Supports momentum trading, mean reversion, and DCA strategies on any Binance spot pair. Use when user wants to trade on Binance, set up automated crypto trading, build a spot trading bot, or automate DCA buying. Features technical analysis, LLM sentiment evaluation, position sizing, and portfolio tracking.
README (SKILL.md)

Binance Spot Trader

Autonomous spot trading bot for Binance. Combines technical indicators with LLM-powered market sentiment analysis to execute trades on any Binance spot pair.

Prerequisites

  • Binance account with API keys (spot trading enabled, withdrawal DISABLED)
  • Anthropic API key (uses Haiku ~$0.001/eval)
  • Python 3.10+

Setup

1. Install

bash {baseDir}/scripts/setup.sh

2. Configure

Create .env:

BINANCE_API_KEY=\x3Cyour-api-key>
BINANCE_SECRET_KEY=\x3Cyour-secret-key>
LLM_API_KEY=\x3Canthropic-api-key>
PAIRS=BTCUSDT,ETHUSDT,SOLUSDT
STRATEGY=momentum
TRADE_SIZE_PCT=5
MAX_POSITIONS=5

3. Run

python3 {baseDir}/scripts/trader.py

Or via cron:

*/5 * * * * cd /opt/trader && python3 trader.py >> trader.log 2>&1

Strategies

Momentum (default)

  • Buys when price crosses above 20-EMA with volume spike
  • Sells when price crosses below 20-EMA or hits TP/SL
  • Best for trending markets (BTC, ETH, SOL)

Mean Reversion

  • Buys when RSI \x3C 30 (oversold) and price near Bollinger Band lower
  • Sells when RSI > 70 (overbought) or price near upper band
  • Best for range-bound markets

DCA (Dollar Cost Average)

  • Buys fixed amount at regular intervals regardless of price
  • Configurable interval (hourly, daily, weekly)
  • Lowest risk strategy for long-term accumulation

LLM-Enhanced (all strategies)

  • Before each trade, asks Claude Haiku for market sentiment
  • Evaluates: recent news, price action, volume patterns, market structure
  • Can veto a trade signal if sentiment is strongly against

Trading Parameters

Parameter Default Description
PAIRS BTCUSDT Comma-separated trading pairs
STRATEGY momentum momentum, mean_reversion, or dca
TRADE_SIZE_PCT 5 % of portfolio per trade
MAX_POSITIONS 5 Max concurrent open positions
TAKE_PROFIT_PCT 5 Take profit %
STOP_LOSS_PCT 3 Stop loss %
DCA_INTERVAL daily For DCA: hourly, daily, weekly
DCA_AMOUNT_USDT 50 USDT per DCA buy
USE_LLM true Enable LLM sentiment filter

Monitoring

# Check portfolio
python3 {baseDir}/scripts/portfolio.py

# View trade history
tail -50 trades.jsonl

# Check logs
tail -f trader.log

⚠️ Security Considerations

  • NEVER enable withdrawal on API keys — trading only
  • IP-restrict your API keys on Binance
  • Use a sub-account with limited funds for bot trading
  • Start with tiny amounts ($50-100) and paper trade first
  • Monitor actively during first 24 hours
  • Set up Binance email alerts for all trades
  • API keys on disk — secure your server (SSH keys only, firewall, chmod 600)

References

  • See references/binance-api.md for REST API docs
  • See references/indicators.md for technical analysis details
Usage Guidance
This package appears to be what it says: an autonomous Binance spot trader that also calls an Anthropic LLM for sentiment. Before installing: (1) only use Binance API keys with trading enabled and withdrawals explicitly disabled; prefer a sub-account with limited funds; (2) secure the .env (chmod 600, limit server access) and IP-restrict the Binance key; (3) review and test the code locally in paper-trade mode or with tiny amounts first — the bot will place real market orders; (4) be aware that the bot sends recent price/volume data to Anthropic (costs and privacy) and will append trade activity to trades.jsonl on disk; (5) monitor rate limits and broker/account limits to avoid accidental rapid trading; (6) if you need higher assurance, run it in an isolated machine and/or audit the code for edge-case error handling and signature construction. If any of the above conditions are unacceptable (e.g., you cannot restrict API key withdrawals or cannot tolerate external LLM calls), do not install.
Capability Analysis
Type: OpenClaw Skill Name: binance-spot-trader Version: 1.0.0 The OpenClaw skill 'binance-spot-trader' is a legitimate autonomous trading bot. It accesses Binance and Anthropic APIs using provided API keys, which is necessary for its stated functionality. The `SKILL.md` provides clear instructions and critical security warnings, advising users to disable withdrawals, IP-restrict keys, and use sub-accounts. The scripts (`setup.sh`, `portfolio.py`, `trader.py`) perform standard operations like installing dependencies, fetching account data, and placing market orders. There is no evidence of data exfiltration to unauthorized endpoints, malicious execution, persistence mechanisms installed by the skill itself, or prompt injection attempts against the OpenClaw agent or the LLM.
Capability Assessment
✓ Purpose & Capability
Name/description (Binance spot trading with LLM sentiment) match what the files and SKILL.md request and implement: the scripts call Binance REST endpoints and an Anthropic LLM. Required env vars (BINANCE_API_KEY, BINANCE_SECRET_KEY, LLM_API_KEY) are appropriate for the stated purpose.
ℹ Instruction Scope
SKILL.md instructs installing dependencies, creating a .env with API keys, and running trader.py (or via cron). The code reads those env vars, writes a local trades.jsonl log, and sends market context to api.anthropic.com — all consistent with the described behavior. Note: the skill persists trade logs and will transmit summary market data to Anthropic (privacy/cost implications).
✓ Install Mechanism
setup.sh uses pip to install httpx and python-dotenv — reasonable, minimal, and from standard packaging. No downloads from unknown hosts or archive extraction are present.
✓ Credentials
Only three env vars are required (Binance API key + secret, LLM API key), which are proportionate to a trading bot that places orders and calls an LLM. No unrelated credentials or broad system paths are requested.
✓ Persistence & Privilege
Skill is not force-included (always:false) and does not request elevated platform privileges. It writes local logs (trades.jsonl, trader.log if run via cron) and does not modify other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install binance-spot-trader
  3. After installation, invoke the skill by name or use /binance-spot-trader
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: autonomous Binance spot trading with momentum, mean reversion, and DCA strategies plus LLM sentiment analysis
Metadata
Slug binance-spot-trader
Version 1.0.0
License —
All-time Installs 12
Active Installs 11
Total Versions 1
Frequently Asked Questions

What is Binance Spot Trader?

Autonomous Binance spot trading bot with LLM-powered market analysis. Supports momentum trading, mean reversion, and DCA strategies on any Binance spot pair. Use when user wants to trade on Binance, set up automated crypto trading, build a spot trading bot, or automate DCA buying. Features technical analysis, LLM sentiment evaluation, position sizing, and portfolio tracking. It is an AI Agent Skill for Claude Code / OpenClaw, with 3769 downloads so far.

How do I install Binance Spot Trader?

Run "/install binance-spot-trader" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Binance Spot Trader free?

Yes, Binance Spot Trader is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Binance Spot Trader support?

Binance Spot Trader is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Binance Spot Trader?

It is built and maintained by srikanthbellary (@srikanthbellary); the current version is v1.0.0.

More Skills
self-improving agent
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
⬇ 463815 · by pskoett
Skill Vetter
Security-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.
⬇ 259802 · by spclaudehome
Polymarket
Query Polymarket prediction markets. Check odds, find trending markets, search events, track price movements.
⬇ 232503 · by joelchance
Self-Improving + Proactive Agent
Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when...
⬇ 200680 · by ivangdavila
Github
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
⬇ 191345 · by steipete
ontology
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linkin...
⬇ 190333 · by oswalpalash

💬 Comments