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cryptofeed

This is the open-source content repository behind

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项目 README

来源文件:README.md

抓取于 2026年9月2日

Skill Store — Marketplace Repository

This is the open-source content repository behind Skill Store. It stores every approved Agent Skill, the records that go with it, and the automated security audits published with each skill.

This repo is a companion to the Skill Store platform, not the place to submit skills. Skills are added through skillstore.io — its review pipeline writes to this repo automatically. Please do not open a pull request here to add a skill; PRs adding skills will be closed. See Contributing a skill below.

Installing a skill

The recommended way to install any skill is the skillstore CLI — one command works for both Claude Code and Codex:

npx skillstore add author/skill-name

For example:

npx skillstore add aiskillstore/code-review

It downloads the skill and drops it into the right skills/ directory for your tool. Claude Code auto-discovers it; for Codex, restart the session.

Prefer to do it by hand, or installing via Claude Web? See the full Installation Guides for every method (CLI, manual, and ZIP upload) and the scope directories (~/.agents/skills/, .claude/skills/, ~/.claude/skills/, .codex/skills/, …).

Contributing a skill

Submit through the platform — not through a pull request:

  1. Go to skillstore.io/submit.
  2. Enter the GitHub repository URL that contains your SKILL.md.
  3. Your submission runs through automated security analysis.
  4. A maintainer reviews and approves it.
  5. On approval, the skill is published here and appears on skillstore.io.

What makes a valid skill

  • SKILL.md — the skill definition (required, per the Agent Skills spec)
  • Supporting files the skill references (optional)
  • LICENSE (recommended)

Security audit

Every submission is scanned automatically before it can be published. The audit flags things like:

  • Dangerous code patterns (eval, exec, raw system commands)
  • File access outside the project scope
  • Network calls to external hosts
  • Obfuscated or minified code
  • Credential / secret handling

Security analysis is report-only: findings inform maintainers and users, but a risk result does not automatically block an otherwise approved skill from being published. See our Security Trust Center for the methodology, limitations, and risk-level definitions.

Live Security Passport example:

Skillstore security

Repository layout

.
├── skills/        # Approved, published skills (one folder each, with SKILL.md)
├── pending/       # Submissions awaiting review
├── packages/
│   ├── cli/       # The `skillstore` CLI (npx skillstore add …)
│   └── skillstore/
├── schemas/       # JSON schemas for skill records
├── scripts/       # Maintenance & scoring scripts
└── .github/workflows/   # Submission, audit, and sync automation

The contents of this repo are maintained by Skill Store's automated pipeline. Manual changes are limited to maintainers.

Links

License

The marketplace catalog is MIT-licensed. Individual skills carry their own licenses — check each skill's LICENSE file.

数据与 AI

中风险

  • 来源需自行核对维护者身份。
  • 包含脚本或命令调用,安装前请复核。
  • 未检测到明显外部权限要求。
  • 未检测到高风险命令。
  • 扫描发现:3 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2025emma/cryptofeed" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2025emma/cryptofeed" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2025emma/cryptofeed" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2025emma/cryptofeed" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2025emma/cryptofeed" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: cryptofeed
description: Cryptofeed - Real-time cryptocurrency market data feeds from 40+ exchanges. WebSocket streaming, normalized data, order books, trades, tickers. Python library for algorithmic trading and market data analysis.

Cryptofeed Skill

Comprehensive assistance with Cryptofeed development - a Python library for handling cryptocurrency exchange data feeds with normalized and standardized results.

When to Use This Skill

This skill should be triggered when:

  • Working with real-time cryptocurrency market data
  • Implementing WebSocket streaming from crypto exchanges
  • Building algorithmic trading systems
  • Processing order book updates, trades, or ticker data
  • Connecting to 40+ cryptocurrency exchanges
  • Using normalized exchange APIs
  • Implementing market data backends (Redis, MongoDB, Kafka, etc.)

Quick Reference

Installation

# Basic installation
pip install cryptofeed

# With all optional backends
pip install cryptofeed[all]

Basic Usage Pattern

from cryptofeed import FeedHandler
from cryptofeed.exchanges import Coinbase, Bitfinex
from cryptofeed.defines import TICKER, TRADES, L2_BOOK

# Define callbacks
def ticker_callback(data):
    print(f"Ticker: {data}")

def trade_callback(data):
    print(f"Trade: {data}")

# Create feed handler
fh = FeedHandler()

# Add exchange feeds
fh.add_feed(Coinbase(
    symbols=['BTC-USD'],
    channels=[TICKER],
    callbacks={TICKER: ticker_callback}
))

fh.add_feed(Bitfinex(
    symbols=['BTC-USD'],
    channels=[TRADES],
    callbacks={TRADES: trade_callback}
))

# Start receiving data
fh.run()

National Best Bid/Offer (NBBO)

from cryptofeed import FeedHandler
from cryptofeed.exchanges import Coinbase, Gemini, Kraken

def nbbo_update(symbol, bid, bid_size, ask, ask_size, bid_feed, ask_feed):
    print(f'Pair: {symbol} Bid: {bid:.2f} ({bid_size:.6f}) from {bid_feed}')
    print(f'Ask: {ask:.2f} ({ask_size:.6f}) from {ask_feed}')

f = FeedHandler()
f.add_nbbo([Coinbase, Kraken, Gemini], ['BTC-USD'], nbbo_update)
f.run()

Supported Exchanges (40+)

Major Exchanges

  • Binance (Spot, Futures, Delivery, US)
  • Coinbase, Kraken (Spot, Futures), Bitfinex
  • Gemini, OKX, Bybit
  • Huobi (Spot, DM, Swap), Gate.io (Spot, Futures)
  • KuCoin, Deribit, BitMEX, dYdX

Additional Exchanges

AscendEX, Bequant, bitFlyer, Bithumb, Bitstamp, Blockchain.com, Bit.com, Bitget, Crypto.com, Delta, EXX, FMFW.io, HitBTC, Independent Reserve, OKCoin, Phemex, Poloniex, ProBit, Upbit

Supported Data Channels

Market Data (Public)

  • L1_BOOK - Top of order book
  • L2_BOOK - Price aggregated sizes
  • L3_BOOK - Price aggregated orders
  • TRADES - Executed trades (taker side)
  • TICKER - Price ticker updates
  • FUNDING - Funding rate data
  • OPEN_INTEREST - Open interest statistics
  • LIQUIDATIONS - Liquidation events
  • INDEX - Index price data
  • CANDLES - Candlestick/K-line data

Authenticated Channels (Private)

  • ORDER_INFO - Order status updates
  • TRANSACTIONS - Deposits and withdrawals
  • BALANCES - Wallet balance updates
  • FILLS - User's executed trades

Supported Backends

Write data directly to storage:

  • Redis (Streams and Sorted Sets)
  • Arctic - Time-series database
  • ZeroMQ, InfluxDB v2, MongoDB
  • Kafka, RabbitMQ, PostgreSQL
  • QuasarDB, GCP Pub/Sub, QuestDB
  • UDP/TCP/Unix Sockets

Key Features

Real-time Data Normalization

Cryptofeed normalizes data across all exchanges, providing consistent:

  • Symbol formatting
  • Timestamp handling
  • Data structures
  • Channel names

WebSocket + REST Fallback

  • Primarily uses WebSockets for real-time data
  • Falls back to REST polling when WebSocket unavailable
  • Automatic reconnection handling

NBBO Aggregation

Create synthetic National Best Bid/Offer feeds by aggregating data across multiple exchanges to find arbitrage opportunities.

Backend Integration

Direct data writing to various storage systems without custom integration code.

Requirements

  • Python: 3.8 or higher
  • Installation: Via pip or from source
  • Optional Dependencies: Install backends as needed

Common Use Cases

Multi-Exchange Price Monitoring

fh = FeedHandler()
fh.add_feed(Binance(symbols=['BTC-USDT'], channels=[TICKER], callbacks=ticker_cb))
fh.add_feed(Coinbase(symbols=['BTC-USD'], channels=[TICKER], callbacks=ticker_cb))
fh.add_feed(Kraken(symbols=['BTC-USD'], channels=[TICKER], callbacks=ticker_cb))
fh.run()

Order Book Depth Analysis

def book_callback(book, receipt_timestamp):
    print(f"Bids: {len(book.book.bids)} | Asks: {len(book.book.asks)}")

fh.add_feed(Coinbase(
    symbols=['BTC-USD'],
    channels=[L2_BOOK],
    callbacks={L2_BOOK: book_callback}
))

Trade Flow Analysis

def trade_callback(trade, receipt_timestamp):
    print(f"{trade.exchange} - {trade.symbol}: {trade.side} {trade.amount} @ {trade.price}")

fh.add_feed(Binance(
    symbols=['BTC-USDT', 'ETH-USDT'],
    channels=[TRADES],
    callbacks={TRADES: trade_callback}
))

Reference Files

This skill includes documentation in references/:

  • getting_started.md - Installation and basic usage
  • README.md - Complete overview and examples

Use view to read specific reference files when detailed information is needed.

Working with This Skill

For Beginners

Start with basic FeedHandler setup and single exchange connections before adding multiple feeds.

For Advanced Users

Explore NBBO feeds, authenticated channels, and backend integrations for production systems.

For Code Examples

See the quick reference section above and the reference files for complete working examples.

Resources

Notes

  • Requires Python 3.8+
  • WebSocket-first approach with REST fallback
  • Normalized data across all exchanges
  • Active development and community support
  • 40+ supported exchanges and growing

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