Skip to main content
ClaudeWave
Skill2.3k repo starsupdated 24d ago

alpha-vantage

Alpha Vantage provides access to real-time and historical financial market data including stock prices, forex rates, cryptocurrency values, commodities, company fundamentals, and 50+ technical indicators through a single API. Use this skill when retrieving equity OHLCV data, calculating technical indicators like RSI or MACD, fetching economic indicators such as GDP or CPI, analyzing company financial statements, or monitoring commodity and cryptocurrency prices.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills /tmp/alpha-vantage && cp -r /tmp/alpha-vantage/bundled/skills/alpha-vantage ~/.claude/skills/alpha-vantage
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Alpha Vantage — Financial Market Data

Access 20+ years of global financial data: equities, options, forex, crypto, commodities, economic indicators, and 50+ technical indicators.

## API Key Setup (Required)

1. Get a free key at https://www.alphavantage.co/support/#api-key (premium plans available for higher rate limits)
2. Set as environment variable:

```bash
export ALPHAVANTAGE_API_KEY="your_key_here"
```

## Installation

```bash
uv pip install requests pandas
```

## Base URL & Request Pattern

All requests go to:

```
https://www.alphavantage.co/query?function=FUNCTION_NAME&apikey=YOUR_KEY&...params
```

```python
import requests
import os

API_KEY = os.environ.get("ALPHAVANTAGE_API_KEY")
BASE_URL = "https://www.alphavantage.co/query"

def av_get(function, **params):
    response = requests.get(BASE_URL, params={"function": function, "apikey": API_KEY, **params})
    return response.json()
```

## Quick Start Examples

```python
# Stock quote (latest price)
quote = av_get("GLOBAL_QUOTE", symbol="AAPL")
price = quote["Global Quote"]["05. price"]

# Daily OHLCV
daily = av_get("TIME_SERIES_DAILY", symbol="AAPL", outputsize="compact")
ts = daily["Time Series (Daily)"]

# Company fundamentals
overview = av_get("OVERVIEW", symbol="AAPL")
print(overview["MarketCapitalization"], overview["PERatio"])

# Income statement
income = av_get("INCOME_STATEMENT", symbol="AAPL")
annual = income["annualReports"][0]  # Most recent annual

# Crypto price
crypto = av_get("DIGITAL_CURRENCY_DAILY", symbol="BTC", market="USD")

# Economic indicator
gdp = av_get("REAL_GDP", interval="annual")

# Technical indicator
rsi = av_get("RSI", symbol="AAPL", interval="daily", time_period=14, series_type="close")
```

## API Categories

| Category | Key Functions |
|----------|--------------|
| **Time Series (Stocks)** | GLOBAL_QUOTE, TIME_SERIES_INTRADAY, TIME_SERIES_DAILY, TIME_SERIES_WEEKLY, TIME_SERIES_MONTHLY |
| **Options** | REALTIME_OPTIONS, HISTORICAL_OPTIONS |
| **Alpha Intelligence** | NEWS_SENTIMENT, EARNINGS_CALL_TRANSCRIPT, TOP_GAINERS_LOSERS, INSIDER_TRANSACTIONS, ANALYTICS_FIXED_WINDOW |
| **Fundamentals** | OVERVIEW, ETF_PROFILE, INCOME_STATEMENT, BALANCE_SHEET, CASH_FLOW, EARNINGS, DIVIDENDS, SPLITS |
| **Forex (FX)** | CURRENCY_EXCHANGE_RATE, FX_INTRADAY, FX_DAILY, FX_WEEKLY, FX_MONTHLY |
| **Crypto** | CURRENCY_EXCHANGE_RATE, CRYPTO_INTRADAY, DIGITAL_CURRENCY_DAILY |
| **Commodities** | GOLD (WTI spot), BRENT, NATURAL_GAS, COPPER, WHEAT, CORN, COFFEE, ALL_COMMODITIES |
| **Economic Indicators** | REAL_GDP, TREASURY_YIELD, FEDERAL_FUNDS_RATE, CPI, INFLATION, UNEMPLOYMENT, NONFARM_PAYROLL |
| **Technical Indicators** | SMA, EMA, MACD, RSI, BBANDS, STOCH, ADX, ATR, OBV, VWAP, and 40+ more |

## Common Parameters

| Parameter | Values | Notes |
|-----------|--------|-------|
| `outputsize` | `compact` / `full` | compact = last 100 points; full = 20+ years |
| `datatype` | `json` / `csv` | Default: json |
| `interval` | `1min`, `5min`, `15min`, `30min`, `60min`, `daily`, `weekly`, `monthly` | Depends on endpoint |
| `adjusted` | `true` / `false` | Adjust for splits/dividends |

## Rate Limits

- Free tier: 25 requests/day (as of 2026)
- Premium plans: higher limits, real-time data, intraday access
- HTTP 429 = rate limit exceeded
- Add delays between requests when processing multiple symbols

```python
import time
# Add delay to avoid rate limits
time.sleep(0.5)  # 0.5s between requests on free tier
```

## Error Handling

```python
data = av_get("GLOBAL_QUOTE", symbol="AAPL")

# Check for API errors
if "Error Message" in data:
    raise ValueError(f"API Error: {data['Error Message']}")
if "Note" in data:
    print(f"Rate limit warning: {data['Note']}")
if "Information" in data:
    print(f"API info: {data['Information']}")
```

## Reference Files

Load these for detailed endpoint documentation:

- **[time-series.md](references/time-series.md)** — Stock OHLCV data, quotes, bulk quotes, market status
- **[fundamentals.md](references/fundamentals.md)** — Company overview, financial statements, earnings, dividends, splits
- **[options.md](references/options.md)** — Realtime and historical options chain data
- **[intelligence.md](references/intelligence.md)** — News/sentiment, earnings transcripts, insider transactions, analytics
- **[forex-crypto.md](references/forex-crypto.md)** — Forex exchange rates and cryptocurrency prices
- **[commodities.md](references/commodities.md)** — Gold, silver, oil, natural gas, agricultural commodities
- **[economic-indicators.md](references/economic-indicators.md)** — GDP, CPI, interest rates, employment data
- **[technical-indicators.md](references/technical-indicators.md)** — 50+ technical analysis indicators (SMA, EMA, MACD, RSI, etc.)
vibeSkill

Vibe Code Orchestrator (VCO) is a governed runtime entry that freezes requirements, plans XL-first execution, and enforces verification and phase cleanup.

skill-creatorSkill

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.

skill-installerSkill

Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).

LQF_Machine_Learning_Expert_GuideSkill

|

adaptyvSkill

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

aeonSkill

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

algorithmic-artSkill

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

architecture-patternsSkill

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.