deepq-financial-toolkit
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TDQS
Scored across 44 tools
The tools are organized by asset types (A-share, ETF, fund, stock, sector) and analysis dimensions (basic info, performance, technical, fundamental, news), which helps distinguish them. However, there is notable overlap within categories, such as 'etfBasicInfo' and 'etfLatestPrice' both covering similar ETF data, and 'stockFunAnalysis' and 'stockValuation' both addressing valuation metrics, which could cause confusion in tool selection.
Most tools follow a consistent snake_case pattern with clear prefixes indicating the asset type (e.g., 'aShare', 'etf', 'fund', 'stock', 'sector'), which aids readability. Minor inconsistencies include 'guessFundCode' and 'guessStockCode' using 'guess' instead of a more standard verb like 'parse', and 'mktForwardLook' abbreviating 'market' differently than other tools, but overall the naming is predictable and well-structured.
With 44 tools, the count is excessive for a single server, leading to potential overwhelm and redundancy. While the domain of financial analysis is broad, the tools could be consolidated or split into more focused servers (e.g., separate servers for A-shares, ETFs, funds, stocks, and sectors) to improve usability and reduce overlap.
The tool set comprehensively covers the financial analysis domain, offering CRUD-like operations across multiple asset types (A-shares, ETFs, funds, stocks, sectors) and analysis dimensions (basic info, performance, technical, fundamental, news, research). There are no obvious gaps; tools address data retrieval, entity parsing, market events, and various analytical perspectives, ensuring agents can handle diverse financial queries without dead ends.