cryptofeed

2025emma/vibe-coding-cn · updated Apr 8, 2026

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$npx skills add https://github.com/2025emma/vibe-coding-cn --skill cryptofeed
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summary

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

skill.md

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
how to use cryptofeed

How to use cryptofeed on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add cryptofeed
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/2025emma/vibe-coding-cn --skill cryptofeed

The skills CLI fetches cryptofeed from GitHub repository 2025emma/vibe-coding-cn and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/cryptofeed

Reload or restart Cursor to activate cryptofeed. Access the skill through slash commands (e.g., /cryptofeed) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.435 reviews
  • Xiao Zhang· Dec 28, 2024

    Registry listing for cryptofeed matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Zaid Mensah· Dec 4, 2024

    Keeps context tight: cryptofeed is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Zaid Perez· Nov 23, 2024

    cryptofeed is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ira Farah· Nov 19, 2024

    cryptofeed fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Amelia Garcia· Nov 3, 2024

    I recommend cryptofeed for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Amelia Johnson· Oct 22, 2024

    cryptofeed reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Sofia Okafor· Oct 14, 2024

    cryptofeed fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Min Anderson· Oct 10, 2024

    cryptofeed is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Maya Zhang· Sep 17, 2024

    Solid pick for teams standardizing on skills: cryptofeed is focused, and the summary matches what you get after install.

  • Ira Bansal· Sep 17, 2024

    cryptofeed has been reliable in day-to-day use. Documentation quality is above average for community skills.

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