ai-maker-data

name

ai-maker-data

description

Use this skill when the user needs to interpret metrics, understand what data means, build a data visualization, or define what to measure. Triggers include: 'what does this data mean', 'interpret these metrics', 'build a chart', 'create a dashboard', 'show me a trend', 'what should we measure', 'data summary', 'metrics report', 'anomaly in the data', or any request to make sense of numbers for a business decision. Do NOT use for building technical data pipelines or processing large datasets — use ai-workbench-data for that.

AI Maker Data

Data pipelines, metrics interpretation, and dashboard creation for managers. This skill helps you understand what your data means, build visualizations to share it, and make decisions from it.

When to invoke

Use this skill when you need to:

• Interpret a metrics report or dashboard and explain what it means
• Build a simple data visualization or summary table from raw data
• Define what metrics matter for a project or initiative
• Spot trends, anomalies, or gaps in a dataset
• Design a dashboard layout for a team or executive audience

What it does

1. Interprets metrics — explains what numbers mean in context, flags anomalies, and identifies trends
2. Builds visualizations — creates HTML/CSS charts, tables, and dashboards from provided data
3. Defines metrics — recommends what to measure for a given goal and how to instrument it
4. Finds patterns — identifies correlations, outliers, and signals in structured data
5. Formats for audience — executive dashboard vs engineering metrics board vs team health scorecard

Key behaviors

• Context-first — never interprets a number without knowing what it's measuring and why
• Anomaly-flagging — calls out data that doesn't fit the pattern before presenting the trend
• Honest about uncertainty — distinguishes "the data shows" from "this could indicate"
• Actionable — connects metrics to decisions; data without implication is not the goal

Output formats

• Metrics interpretation summary
• HTML dashboard or visualization
• Trend analysis with anomaly notes
• Metrics definition framework (what to track + why)

Scope

This skill covers business metrics and data interpretation for managers. For technical data pipeline construction, sentiment analysis, or large-scale data processing, use AI Workbench Data.