Restaurant Financial Report Interpretation and Anomaly Detection

Problem It Solves

Restaurant financial statements often fail at interpretation rather than availability. Revenue, gross margin, expenses, and cash flow may point in different directions. YoY and QoQ swings can come from seasonality, delivery platforms, ingredient costs, store mix, or franchise structure instead of a single operational issue. financial-report-reader reframes report reading from checking final results to tracing causes across the income statement, balance sheet, and cash-flow statement, producing diagnostics that can be verified with numbers.

How It Works

The skill is organized around YoY/QoQ comparison and anomaly detection, with an emphasis on quantitative conclusions and graded presentation.
- Problem framing: identify whether the issue is revenue quality, gross-margin stability, expense control, cash-flow pressure, or asset-structure risk.
- Framework matching: load only the relevant files from references/, including core framework, application guide, and advanced methods, to avoid bloating context.
- Deep analysis: use cases/ to map typical, challenging, and successful paths through problem definition, analytical framework, solution design, execution steps, and tracking.
- Template output: use assets/checklist-quick-start.md and assets/template-analysis.md to produce a structured result that can be filled with actual data.
The output typically includes key metrics, top actions, diagnostic evidence, and executable recommendations rather than generic advice.

Boundaries and Notes

This skill is best suited to interpreting existing financial statements, store operating data, or management reporting. It does not replace audit, tax filing, accounting-standard judgment, or investment due diligence. When source data is missing, assumptions must be labeled explicitly. Restaurant metrics are highly sensitive to delivery mix, dine-in turns, ingredient prices, franchise share, seasonality, platform subsidies, and store-count changes, so single-period anomalies should be evaluated in context.