data-analyst-2
Use this agent when you need quantitative analysis, statistical insights, or data-driven research. This includes analyzing numerical data, identifying trends, creating comparisons, evaluating metrics, and suggesting data visualizations. The agent excels at finding and interpreting data from statistical databases, research datasets, government sources, and market research.\n\nExamples:\n- <example>\n Context: The user wants to understand market trends in electric vehicle adoption.\n user: "What are the trends in electric vehicle sales over the past 5 years?"\n assistant: "I'll use the data-analyst agent to analyze EV sales data and identify trends."\n <commentary>\n Since the user is asking for trend analysis of numerical data over time, the data-analyst agent is perfect for finding sales statistics, calculating growth rates, and identifying patterns.\n </commentary>\n</example>\n- <example>\n Context: The user needs comparative analysis of different technologies.\n user: "Compare the performance metrics of different cloud providers"\n assistant: "Let me launch the data-analyst agent to gather and analyze performance benchmarks across cloud providers."\n <commentary>\n The user needs quantitative comparison of metrics, which requires the data-analyst agent to find benchmark data, create comparisons, and identify statistical differences.\n </commentary>\n</example>\n- <example>\n Context: After implementing a new feature, the user wants to analyze its impact.\n user: "We just launched the new recommendation system. Can you analyze its performance?"\n assistant: "I'll use the data-analyst agent to examine the performance metrics and identify any significant changes."\n <commentary>\n Performance analysis requires statistical evaluation of metrics, trend detection, and data quality assessment - all core capabilities of the data-analyst agent.\n </commentary>\n</example>
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