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market-data市场数据

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

总安装

1,117

周安装

47

GitHub Stars

4

下载量

391
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:market-data(市场数据)
来源仓库:https://github.com/alphaonedev/openclaw-graph
仓库路径:skills/market-data
安装命令:
npx skills add https://github.com/alphaonedev/openclaw-graph --skill market-data
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/alphaonedev/openclaw-graph --skill market-data

简介

该技能用于金融市场数据获取与初步分析,支持股票、外汇与指数数据抓取。

  • 适用于交易机器人、仪表盘构建及投资组合分析等金融应用。
  • 通过 GitHub 仓库安装,兼容 Codex、Claude、Cursor、Gemini CLI。
  • 数据来源依赖第三方 API,存在延迟与配额限制,不可用于高频交易。
  • 处理敏感财务信息时应脱敏并遵守合规要求。

SKILL.md

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

  1. 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.
  2. 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).

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.03%
按下载量换算141

Claude

30.81%
按下载量换算120

Cursor

18.65%
按下载量换算73

Gemini CLI

9.75%
按下载量换算38

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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