> alphaear-search
Perform finance web searches and local context searches. Use when the user needs general finance info from the web (Jina/DDG/Baidu) or needs to retrieve finance information from a local document store (RAG).
curl "https://skillshub.wtf/RKiding/Awesome-finance-skills/alphaear-search?format=md"AlphaEar Search Skill
Overview
Unified search capabilities: web search (Jina/DDG/Baidu) and local RAG search.
Capabilities
1. Web Search
Use scripts/search_tools.py via SearchTools.
- Search:
search(query, engine, max_results)- Engines:
jina,ddg,baidu,local. - Returns: JSON string (summary) or List[Dict] (via
search_list).
- Engines:
- Smart Cache (Agentic): If you want to avoid redundant searches, use the Search Cache Relevance Prompt in
references/PROMPTS.md. Read the cache first and decide if it's usable. - Aggregate:
aggregate_search(query)- Combines results from multiple engines.
2. Local RAG
Use scripts/hybrid_search.py or SearchTools with engine='local'.
- Search: Searches local
daily_newsdatabase.
Dependencies
duckduckgo-search,requestsscripts/database_manager.py(search cache & local news)
> related_skills --same-repo
> skill-creator
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
> alphaear-stock
Search A-Share/HK/US finance stock tickers and retrieve finance stock price history. Use when user asks about finance stock codes, recent price changes, or specific company finance stock info.
> alphaear-signal-tracker
Track finance investment signal evolution and update logic based on new finance market information. Use when monitoring finance signals and determining if they are strengthened, weakened, or falsified.
> alphaear-sentiment
Analyze finance text sentiment using FinBERT or LLM. Use when the user needs to determine the sentiment (positive/negative/neutral) and score of financial text markets.