Data Analyst Expert

What it does

Once installed, the agent approaches data work like an experienced analyst: it first inspects a dataset for missing values, duplicates, and odd formats, then cleans it, explores distributions and correlations, and produces well-labelled charts. It also applies statistical checks such as choosing the right test, reporting effect sizes and confidence intervals, and warning against causal claims drawn from correlations. The skill is a set of instructions and best practices; it does not add any new tools by itself.

Try asking

• “Explore this sales CSV: check for nulls and duplicates, then summarise the key trends”Copy
• “Compare conversion rates between two groups and tell me whether the difference is statistically meaningful”Copy
• “Make a readable time-series chart of monthly revenue with labelled axes and annotated peaks”Copy
• “Clean this customer table: standardise date formats and normalise the name fields”Copy

Get better results

• Provide the dataset or a clear description of its columns and goal so the agent can pick sensible cleaning and chart choices
• Ask for the assumptions behind any statistical test, and check that sample sizes are adequate
• Install the Python libraries in the environment the agent uses, since the skill assumes they are available

What's inside

• SKILL.md