market-data

Purpose

This skill fetches and processes real-time financial market data from APIs like Alpha Vantage or Yahoo Finance, enabling analysis and trading decisions. It handles data ingestion, normalization, and basic computations for stocks, currencies, and indices.

When to Use

Use this skill for real-time market monitoring in trading bots, financial dashboards, or data-driven apps. Apply it when you need live stock prices, historical data, or indicators like moving averages, especially in high-frequency trading scenarios or portfolio analysis.

Key Capabilities

• Fetch real-time or historical data for stocks, ETFs, and forex via APIs.

• Process data with built-in functions, e.g., calculate simple moving averages or volatility.

• Support for multiple data sources, configurable via JSON config files.

• Handle large datasets efficiently with pagination and caching.

• Integrate with other financial tools for automated workflows.

Usage Patterns

Always initialize the skill with authentication via environment variables. Use it in a pipeline: first fetch data, then process it, and finally output or integrate. For scripts, import as a module and call functions directly. In CLI mode, chain commands for sequential operations. Avoid direct database writes; use it for transient data processing.

Common Commands/API

Use the claw CLI for quick access; API endpoints are for programmatic use. Set $MARKET_API_KEY for authentication before running commands.

CLI Command: Fetch stock price

claw market-data fetch --symbol AAPL --interval 1min

This retrieves the latest 1-minute OHLC data for AAPL.

API Endpoint: Get stock data

Endpoint: GET /api/v1/stocks/{symbol} with query params like ?interval=1min

Example: Use in code:

import requests response = requests.get('http://api.openclaw.ai/api/v1/stocks/AAPL', headers={'Authorization': f'Bearer {os.environ["MARKET_API_KEY"]}'}) data = response.json()

CLI Command: Process data (e.g., calculate SMA)

claw market-data process --input data.json --function sma --period 20

This reads a JSON file and computes a 20-period SMA.

API Endpoint: Process data

Endpoint: POST /api/v1/process with JSON body {"function": "sma", "data": [...], "period": 20}

Example:

fetch('http://api.openclaw.ai/api/v1/process', { method: 'POST', headers: { 'Authorization': Bearer ${process.env.MARKET_API_KEY} }, body: JSON.stringify({function: 'sma', data: [/* array */], period: 20}) }).then(res => res.json());

Config Format: Use a JSON file for settings

Example config.json:

{ "api_endpoint": "http://api.openclaw.ai", "default_interval": "1min", "cache_ttl": 300 }

Load it with: claw market-data config load path/to/config.json

Integration Notes

Integrate by wrapping skill functions in your app's code; ensure $MARKET_API_KEY is set in your environment. For web apps, use async calls to avoid blocking. If combining with other skills, pipe output via stdin/stdout, e.g., claw market-data fetch --symbol AAPL | claw trading-execution analyze . Handle rate limits by adding delays or using the built-in retry mechanism with --retry-count 3 . Test integrations in a sandbox environment first.

Error Handling

Check for API errors by parsing response codes; common ones include 401 (unauthorized) if $MARKET_API_KEY is missing or invalid. Use try-catch in code snippets:

try: response = requests.get(...) # as above response.raise_for_status() except requests.exceptions.HTTPError as err: print(f"Error: {err} - Check API key or endpoint")

For CLI, add --verbose to log errors, e.g., claw market-data fetch --symbol AAPL --verbose . Retry transient errors with exponential backoff; configure via config.json as {"retry_policy": {"max_retries": 5, "backoff": 2}}. Always validate inputs to prevent malformed requests.

Concrete Usage Examples

Fetch and analyze stock price in a Python script:

Set $MARKET_API_KEY=your_key . Then:

import os import requests symbol = 'AAPL' response = requests.get(f'http://api.openclaw.ai/api/v1/stocks/{symbol}', headers={'Authorization': f'Bearer {os.environ["MARKET_API_KEY"]}'}) price = response.json()['price'] print(f"Current price of {symbol}: {price}")

This outputs the live price for immediate use in a trading algorithm.

Process historical data via CLI for trading signals:

First, fetch data: claw market-data fetch --symbol TSLA --interval daily --output history.json .

Then process: claw market-data process --input history.json --function rsi --period 14 .

Output: A JSON with RSI values, which you can feed into a decision-making script for buy/sell signals.

Graph Relationships

• Related to: trading-execution (fetches data for order placement), financial-analysis (provides processed data for reports).

• Depends on: authentication-service (for API key validation).

• Used by: portfolio-management (integrates market data for asset allocation).