OpenClaw多平台部署与投研应用

• OpenClaw is a modular AI agent architecture designed to integrate large language models (LLMs) with local execution engines, enabling complex task automation across digital and physical environments [48][50] - The system's core components include the Agent Core (central scheduler), Workspace (local memory and domain knowledge), Channels (multi-modal interaction), and Skills (execution tools) [48][50] - OpenClaw employs a standardized function-calling mechanism, allowing LLMs to safely and autonomously interact with external databases, APIs, and local operating systems for end-to-end task execution [48][50] - The Stock Watcher skill on ClawHub uses Tonghuashun (10jqka.com.cn) as its primary data source, providing real-time market data, technical analysis, and fund flow information [58][59] - Users can install the Stock Watcher skill by issuing a natural language command to OpenClaw, enabling functionalities like adding/removing stocks, viewing lists, and summarizing market data [58][59] - When data retrieval issues occur, OpenClaw can automatically switch to alternative data sources, such as Sina, to complete the task [62][63] - OpenClaw supports conditional stock screening by integrating financial data and applying user-defined criteria, such as market cap and P/E ratio thresholds [65][66] - It can also backtest selected stocks' equal-weighted portfolio performance over a specified period, with the precision of results depending on the quality of the chosen LLM [65][66] - OpenClaw enables advanced file management tasks, including creating directories, writing text files, and moving files, through natural language commands [68][69] - It supports comprehensive file operations like creation, search, modification, and reading, making it a versatile tool for local file system management [68][69] - OpenClaw can autonomously select appropriate tools to read and summarize local files, such as company financial reports, without prior configuration [71][72] - By leveraging OpenClaw's local execution capabilities, users can construct complex code projects, such as implementing Barra CNE6 factor models, with structured directories and detailed comments [74][75] - The Technical Analyst skill on ClawHub enables systematic technical analysis of K-line charts, generating detailed reports with insights on trends, key levels, and scenario probabilities [75][77][78]