Financial Analysis

Financial analysis: ratios and derived metrics

The finance tools (get_summary, get_trend, get_budget_status, get_anomalies, get_category_breakdown, get_cashflow) return raw totals. When a question asks for a ratio or rate built from those totals, compute it yourself from the tool's numbers — call the tool first, then apply the formula below. Never invent a ratio without a tool result behind it.

Margins

• Net margin = net / income (from get_summary or get_cashflow). Express as a percentage. Negative net margin means the period ran at a loss.
• There is no cost-of-goods-sold or gross-margin split in this dataset (only income vs expense at the top level) — don't present net margin as "gross margin"; they aren't the same thing and this data can't distinguish COGS from operating expense.

Growth rates

• Month-over-month (MoM) = (this period − previous period) / previous period, using consecutive points from a get_trend series.
• Year-over-year (YoY) = same formula, comparing the same calendar month a year apart in the series.
• CAGR (compound annual growth rate, for multi-year spans) = (end / start) ^ (1 / years) − 1. Use this instead of a simple start-to-end percentage when the span is more than ~18 months — a raw percentage over 3 years overstates how fast something grew per year.
• State the formula's inputs in plain language when you give a rate (e.g. "from $X in [month] to $Y in [month]"), not just the resulting percentage — the number alone isn't verifiable by the reader.

Budget variance

• get_budget_status already returns variance (actual − budget) and pctUsed (actual / budget) per department — don't recompute these, just phrase them: "X% of budget used" or "$Y over/under budget." pctUsed − 1 is the variance as a percentage of budget.

Burn rate and runway

• Burn rate = the period's net from get_summary/get_cashflow when it's negative, expressed as a monthly figure (divide a multi-month range's net by the number of months).
• Runway (months of cash left at the current burn rate) requires a starting cash balance, which this dataset does not have — there is no cash_on_hand figure anywhere in the schema. If asked for runway, say plainly that it isn't computable without a cash balance, and offer the burn rate instead rather than fabricating a runway estimate.

Period-over-period comparisons

Don't compute a delta here — see instructions.md rule 5 ("No prose deltas for period comparisons"). Testing showed that computing later − earlier and naming a direction is exactly where the model silently gets it backwards (asserting a figure "decreased" for a period where it actually increased), even when explicitly told to check the subtraction's sign first. State both raw tool-sourced numbers in order instead and let the reader compare them.

Anomaly severity

• get_anomalies returns categoryMean and categoryStdDev alongside each flagged amount. The deviation in standard deviations is (amount − categoryMean) / categoryStdDev — the UI already labels this as "Nσ" per row. When asked how unusual a specific anomaly is, frame it in those terms: roughly, 2σ is a notable but not extreme outlier, 3σ+ is rare under normal variation. Don't claim a precise probability — the underlying distribution of real expense data isn't verified to be normal, so a literal p-value would overstate precision this data can't support.