Financial Ratio Analysis — SKILL.md

When to Use This Skill

Use when a user asks for:

• Financial ratio analysis for a QBO-connected client
• Profitability, liquidity, leverage, or efficiency metrics
• DuPont decomposition or Altman Z-Score analysis
• Month-over-month, QoQ, or YoY ratio comparison
• Ratio benchmarking against industry averages
• Trend analysis across 6 months of ratios
• Trend reversal detection for any financial ratio
• CDC (change data capture) on ratio movements

NOT for:

• Bank reconciliation → use bank-reconciliation
• P&L variance analysis (line-item drill-down) → use pl-deep-analysis
• Cash flow forecasting → use cash-flow-forecast
• AR collections aging → use ar-collections
• Budget vs. actual → use budget-vs-actual

Quick Invocation

# Standard monthly ratio report
python3 scripts/pipelines/financial-ratios.py --slug sb-paulson --month 2026-03

# Custom output directory
python3 scripts/pipelines/financial-ratios.py --slug <client-slug> --month 2026-03 --out ~/Desktop/reports

# QBO sandbox
python3 scripts/pipelines/financial-ratios.py --slug sb-paulson --month 2026-03 --sandbox

Unknown slugs use default thresholds and disable inventory/valuation ratios unless SOP file found.

What It Produces

Excel workbook saved to ~/Desktop (or --out path):

FinancialRatios_{slug}_{YYYY_MM}.xlsx

Ratio Categories

Profitability

Liquidity

Leverage

Efficiency

Growth

Valuation (SOP-gated)

DuPont Analysis

Three-Factor Model

ROE = Net Margin × Asset Turnover × Equity Multiplier

Five-Factor Model

ROE = Tax Burden × Interest Burden × EBIT Margin × Asset Turnover × Equity Multiplier

Both models computed; trend shown for each component across 6 months.

Altman Z-Score

Bankruptcy risk indicator. Model selected automatically by entity_type in SOP config:

Formula (Z' model):

Z' = 0.717×(WC/TA) + 0.847×(RE/TA) + 3.107×(EBIT/TA) + 0.420×(BVE/TL) + 0.998×(Revenue/TA)

Traffic Light Scoring

Each ratio scores GREEN / YELLOW / RED based on thresholds configured per client SOP.

• GREEN: Within healthy range
• YELLOW: Watch — approaching threshold
• RED: Action required

Thresholds are configured in CLIENT_CONFIGS within the script. Override by editing the dict or adding a client SOP file.

Trend Reversal Detection

The pipeline detects when a ratio reverses direction over the 6-month window:

• Compares direction of first half vs. second half of history
• Flags ⚡ Trend Reversal — Now Improving or ⚠ Trend Reversal — Now Declining
• Flagged prominently in Trends tab and CDC Log

Client SOP Integration

Place a sop.md file at clients/{slug}/sop.md. The pipeline reads it to detect:

Client Configuration

Add clients to CLIENT_CONFIGS in the script with:

• ratios_enabled list (which ratios to compute/display)
• thresholds dict per ratio: {"green": (min, max), "yellow": (min, max)}
• benchmarks dict per ratio: Decimal values
• entity_type: "services" or "manufacturing" (for Altman Z model)

QBO Data Pulled

Total QBO calls: ~17 per run (6-month history + current + prior + QoQ + YoY)

CDC Cache

Cache stored at: .cache/financial-ratios/{slug}.json

Tracks:

• All ratio values from prior run
• Detects per-ratio changes (delta + % change)
• Flags trend reversals when 6-month history available
• Compares run-over-run for drift monitoring

Technical Notes

• All financial math: Python Decimal (no floating-point errors)
• Division-by-zero: returns ZERO, never crashes
• Missing QBO lines: ZERO (safe fallback), does not inflate ratios
• Inventory turnover: annualized (× 12 for monthly periods)
• Interest coverage = 999.99 when no interest expense (signals no debt burden)
• Altman Z-Score uses book value of equity (not market cap) for private company model
• EBITDA = EBIT + D&A; EBIT = Net Income + Interest + Taxes
• Operating margin uses EBIT as proxy for operating income if QBO doesn't separate it

Files