القائمة
Perform finance web searches across multiple engines (Jina, DuckDuckGo, Baidu) and local RAG document retrieval with smart search caching
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Analyze financial text sentiment using FinBERT or LLM, returning a scored label (positive/negative/neutral) from -1.0 to 1.0
Search A-Share and HK stock tickers by name or code and retrieve OHLCV historical price data
Time-series market forecasting using the Kronos model with news-aware sentiment adjustment for OHLC price prediction
Fetch real-time hot finance news and unified trend reports from multiple sources (财联社, WallStreetCN, Weibo, Zhihu, etc.) and Polymarket prediction data
Generate Draw.io XML diagrams to visualize finance logic flows, investment theses, and signal transmission chains
Plan, write, and assemble professional financial reports by clustering signals into themes, writing analysis sections, and compiling a final structured report
| name | AlphaEar Search |
| description | Perform finance web searches across multiple engines (Jina, DuckDuckGo, Baidu) and local RAG document retrieval with smart search caching |
| category | tools-and-utilities/api-integrations |
| tags | ["web-search","rag","multi-engine","search-cache"] |
Unified search capabilities: web search (Jina/DDG/Baidu) and local RAG search.
Use scripts/search_tools.py via SearchTools.
search(query, engine, max_results)
jina, ddg, baidu, local.search_list).references/PROMPTS.md. Read the cache first and decide if it's usable.aggregate_search(query)
Use scripts/hybrid_search.py or SearchTools with engine='local'.
daily_news database.duckduckgo-search, requestsscripts/database_manager.py (search cache & local news)