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agiprolabsagiprolabs/claude-trading-skills/skills/coingecko-api/SKILL.md

coingecko-api

Skill366 starsChanged 8 months agoMITView on GitHub

Broad crypto market data from CoinGecko covering 13,000+ tokens. Global market stats, historical price data going back years, exchange volumes, trending tokens, and category filters. Best for macro analysis and long-term historical data.

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We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use Birdeye or DexScreener instead for real-time Solana DEX data, new token launches, or sub-daily granularity on Solana tokens.

    line 34
  2. Very specific:

    OHLC granularity: Only 1/7/14/30/90/180/365 day windows, candle size depends on the window (see references/endpoints.md)

    line 195

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

CoinGecko API Skill

Query the CoinGecko API for comprehensive crypto market data — prices, historical charts, exchange volumes, trending tokens, global stats, and category breakdowns. The free tier requires no API key and supports 30 calls/min.

When to Use This Skill

  • Macro analysis: Global market cap, BTC dominance, total volume trends
  • Historical data: Daily/hourly OHLCV going back years (not minutes-level)
  • Cross-exchange comparisons: Exchange volume rankings and trust scores
  • Trending/discovery: What tokens are trending on CoinGecko in the last 24h
  • Category analysis: Compare DeFi vs L1 vs meme coin market caps
  • Token research: Full metadata including links, description, community stats

Use Birdeye or DexScreener instead for real-time Solana DEX data, new token launches, or sub-daily granularity on Solana tokens.

Quick Start

Get Current Prices

import httpx

# No API key needed for free tier
resp = httpx.get(
    "https://api.coingecko.com/api/v3/simple/price",
    params={"ids": "solana,bitcoin,ethereum", "vs_currencies": "usd",
            "include_24hr_change": "true"},
)
data = resp.json()
for coin, info in data.items():
    print(f"{coin}: ${info['usd']:.2f} ({info['usd_24h_change']:+.1f}%)")

Get Top Coins by Market Cap

import httpx

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/markets",
    params={"vs_currency": "usd", "order": "market_cap_desc",
            "per_page": 10, "page": 1, "sparkline": "false"},
)
for coin in resp.json():
    print(f"{coin['symbol'].upper():>6}  ${coin['current_price']:>10,.2f}  "
          f"MCap: ${coin['market_cap']/1e9:.1f}B  "
          f"24h: {coin['price_change_percentage_24h']:+.1f}%")

Get Historical Price Data

import httpx
import pandas as pd

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/market_chart",
    params={"vs_currency": "usd", "days": "90", "interval": "daily"},
)
data = resp.json()
df = pd.DataFrame(data["prices"], columns=["timestamp", "price"])
df["date"] = pd.to_datetime(df["timestamp"], unit="ms")
df = df.set_index("date").drop(columns=["timestamp"])
print(df.describe())

Get OHLC Candle Data

import httpx

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/ohlc",
    params={"vs_currency": "usd", "days": "30"},
)
# Returns [[timestamp, open, high, low, close], ...]
candles = resp.json()
for c in candles[-5:]:
    print(f"  O={c[1]:.2f}  H={c[2]:.2f}  L={c[3]:.2f}  C={c[4]:.2f}")

Global Market Stats

import httpx

resp = httpx.get("https://api.coingecko.com/api/v3/global")
g = resp.json()["data"]
print(f"Total Market Cap:  ${g['total_market_cap']['usd']/1e12:.2f}T")
print(f"24h Volume:        ${g['total_volume']['usd']/1e9:.0f}B")
print(f"BTC Dominance:     {g['market_cap_percentage']['btc']:.1f}%")
print(f"Active Coins:      {g['active_cryptocurrencies']:,}")

Trending Coins

import httpx

resp = httpx.get("https://api.coingecko.com/api/v3/search/trending")
for item in resp.json()["coins"]:
    coin = item["item"]
    print(f"#{coin['market_cap_rank'] or '?':>4}  {coin['name']} ({coin['symbol']})")

Authentication

The free tier requires no API key (30 calls/min). For higher limits, get a Pro key from https://www.coingecko.com/en/api/pricing and set:

export COINGECKO_API_KEY="CG-xxxxxxxxxxxxxxxxxxxx"

Pro requests use a different base URL and header:

import os, httpx

API_KEY = os.getenv("COINGECKO_API_KEY", "")
if API_KEY:
    BASE_URL = "https://pro-api.coingecko.com/api/v3"
    HEADERS = {"x-cg-pro-api-key": API_KEY}
else:
    BASE_URL = "https://api.coingecko.com/api/v3"
    HEADERS = {}

Rate Limiting

Free tier: 30 requests/min. Implement backoff on 429 responses:

import time, httpx

def cg_get(url: str, params: dict, max_retries: int = 3) -> dict:
    """GET with retry on rate limit."""
    for attempt in range(max_retries):
        resp = httpx.get(url, params=params, headers=HEADERS, timeout=15.0)
        if resp.status_code == 429:
            wait = 2 ** attempt * 10
            print(f"Rate limited, waiting {wait}s...")
            time.sleep(wait)
            continue
        resp.raise_for_status()
        return resp.json()
    raise RuntimeError("Max retries exceeded")

Finding CoinGecko Token IDs

CoinGecko uses slug-style IDs (e.g., solana, bitcoin, usd-coin). To find an ID from a contract address or name, see references/id_mapping.md.

Quick lookup by contract address (useful for Solana tokens):

import httpx

# Look up by Solana contract address
contract = "So11111111111111111111111111111111111111112"
resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/contract/"
    + contract
)
coin = resp.json()
print(f"ID: {coin['id']}, Name: {coin['name']}")

Key Limitations

  • No real-time data: Prices update every 1-2 minutes on free tier
  • Limited Solana coverage: Many newer Solana tokens are not listed
  • OHLC granularity: Only 1/7/14/30/90/180/365 day windows, candle size depends on the window (see references/endpoints.md)
  • Historical gaps: Some tokens have missing data for early periods
  • Free tier throttling: 30 req/min means batch operations need careful pacing

See references/data_quality.md for detailed notes on data gaps and tier differences.

Files

References

  • references/endpoints.md — Complete endpoint reference with parameters, response schemas, and rate limits
  • references/id_mapping.md — How to find CoinGecko IDs for tokens, contract address mapping, search tips
  • references/data_quality.md — Data quality notes, historical gaps, free vs pro tier differences

Scripts

  • scripts/fetch_market_data.py — Fetch top coins, trending tokens, and global stats (supports --demo mode)
  • scripts/historical_analysis.py — Fetch historical OHLCV data and compute returns, volatility, drawdown (supports --demo mode)

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