Commerce Analytics

by stateset

skill

Run commerce analytics, metrics, and forecasts. Use when running `stateset-analytics` or requesting sales, customer, inventory, or demand insights.

Skill Details

Repository Files

2 files in this skill directory


name: commerce-analytics description: Run commerce analytics, metrics, and forecasts. Use when running stateset-analytics or requesting sales, customer, inventory, or demand insights.

Commerce Analytics

Generate revenue, customer, and inventory insights.

How It Works

  1. Select a time period or segment.
  2. Fetch summary metrics and top entities.
  3. Generate forecasts or breakdowns.
  4. Report key trends and anomalies.

Usage

  • CLI: stateset-analytics ... or stateset "show sales last 30 days"
  • MCP tools: get_sales_summary, get_top_products, get_customer_metrics, get_inventory_health, get_demand_forecast, get_revenue_forecast.

Output

{"revenue":45230,"orders":156,"aov":290}

Present Results to User

  • Metrics requested and time range.
  • Notable trends or outliers.
  • Follow-up actions (reorder, promo, retention).

Troubleshooting

  • Empty data: confirm date range or seed data.
  • Forecast errors: verify historical data volume.

References

  • references/analytics-queries.md
  • /home/dom/stateset-icommerce/cli/.claude/skills/commerce-analytics/SKILL.md

Related Skills

Attack Tree Construction

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

skill

Grafana Dashboards

Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.

skill

Matplotlib

Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.

skill

Scientific Visualization

Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.

skill

Seaborn

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

skill

Shap

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model

skill

Pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

skill

Query Writing

For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations

skill

Pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

skill

Scientific Visualization

Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.

skill

Skill Information

Category:Skill
Last Updated:1/29/2026