crypto-price

Fetches live crypto prices from CoinGecko or Hyperliquid and generates candlestick charts.

7|1|Updated Feb 1, 2026
One-click install
npx skills add https://github.com/LvcidPsyche/polymarket-arbitrage-bot --skill crypto-price
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: crypto-price
Source: https://github.com/LvcidPsyche/polymarket-arbitrage-bot/tree/main/skills/crypto-price
Command: npx skills add https://github.com/LvcidPsyche/polymarket-arbitrage-bot --skill crypto-price

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, and includes scripts (resource) components.

What problem does it solve?

Users need quick, reliable access to live cryptocurrency prices and visual charts to make informed trading or analysis decisions.

Core Features & Use Cases

  • Real-time price lookups from Hyperliquid and CoinGecko with a preferred source per token.
  • Candlestick chart generation in a consistent, compact format for quick visual analysis.
  • Multi-timeframe support (30m, 3h, 12h, 24h, 2d) with smart caching to minimize API usage.
  • Use case: monitor BTC price and a 12-hour chart to plan short-term trades.

Quick Start

Execute the script with a symbol and optional duration to fetch the price and generate a candlestick chart.

Frequently Asked Questions about crypto-price

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I get real-time crypto prices and generate candlestick charts?

Fetch real-time cryptocurrency prices by querying CoinGecko or Hyperliquid for USD or USDT data, then generate candlestick charts using matplotlib for visual analysis.

What timeframes are supported for crypto price-chart requests?

Crypto price-chart requests support multiple timeframes including 30m, 3h, 12h, 24h, and 2d intervals to facilitate short-term trading and market-data lookups.

Do I need matplotlib to fetch token prices from CoinGecko or Hyperliquid?

You need matplotlib specifically for generating visual candlestick charts, while the underlying price retrieval from CoinGecko or Hyperliquid relies on smart caching and fallback logic.

What's the best way to handle API limits when checking cryptocurrency prices across multiple sources?

The best approach uses smart caching to minimize API usage and applies robust error handling with graceful degradation, falling back between CoinGecko and Hyperliquid for price retrieval.

Why does my token price lookup return data in a different currency format?

Token price lookups return data in either USD or USDT depending on the selected data source, with a preferred source configured per token to ensure consistent retrieval.