Agent-Skills.md

Agent Skills: Financial Analyst Skill

Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making

UncategorizedID: alirezarezvani/claude-skills/financial-analyst

Repository

alirezarezvani/claude-skills
alirezarezvaniLicense: MIT
1,640200

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pnpm dlx add-skill https://github.com/alirezarezvani/claude-skills/tree/HEAD/finance/financial-analyst

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finance/financial-analyst/SKILL.md

Skill Metadata

Name
financial-analyst
Description
Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making

Financial Analyst Skill

Overview

Production-ready financial analysis toolkit providing ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction. Designed for financial analysts with 3-6 years experience performing financial modeling, forecasting & budgeting, management reporting, business performance analysis, and investment analysis.

5-Phase Workflow

Phase 1: Scoping

  • Define analysis objectives and stakeholder requirements
  • Identify data sources and time periods
  • Establish materiality thresholds and accuracy targets
  • Select appropriate analytical frameworks

Phase 2: Data Analysis & Modeling

  • Collect and validate financial data (income statement, balance sheet, cash flow)
  • Calculate financial ratios across 5 categories (profitability, liquidity, leverage, efficiency, valuation)
  • Build DCF models with WACC and terminal value calculations
  • Construct budget variance analyses with favorable/unfavorable classification
  • Develop driver-based forecasts with scenario modeling

Phase 3: Insight Generation

  • Interpret ratio trends and benchmark against industry standards
  • Identify material variances and root causes
  • Assess valuation ranges through sensitivity analysis
  • Evaluate forecast scenarios (base/bull/bear) for decision support

Phase 4: Reporting

  • Generate executive summaries with key findings
  • Produce detailed variance reports by department and category
  • Deliver DCF valuation reports with sensitivity tables
  • Present rolling forecasts with trend analysis

Phase 5: Follow-up

  • Track forecast accuracy (target: +/-5% revenue, +/-3% expenses)
  • Monitor report delivery timeliness (target: 100% on time)
  • Update models with actuals as they become available
  • Refine assumptions based on variance analysis

Tools

1. Ratio Calculator (scripts/ratio_calculator.py)

Calculate and interpret financial ratios from financial statement data.

Ratio Categories:

  • Profitability: ROE, ROA, Gross Margin, Operating Margin, Net Margin
  • Liquidity: Current Ratio, Quick Ratio, Cash Ratio
  • Leverage: Debt-to-Equity, Interest Coverage, DSCR
  • Efficiency: Asset Turnover, Inventory Turnover, Receivables Turnover, DSO
  • Valuation: P/E, P/B, P/S, EV/EBITDA, PEG Ratio
python scripts/ratio_calculator.py sample_financial_data.json
python scripts/ratio_calculator.py sample_financial_data.json --format json
python scripts/ratio_calculator.py sample_financial_data.json --category profitability

2. DCF Valuation (scripts/dcf_valuation.py)

Discounted Cash Flow enterprise and equity valuation with sensitivity analysis.

Features:

  • WACC calculation via CAPM
  • Revenue and free cash flow projections (5-year default)
  • Terminal value via perpetuity growth and exit multiple methods
  • Enterprise value and equity value derivation
  • Two-way sensitivity analysis (discount rate vs growth rate)
python scripts/dcf_valuation.py valuation_data.json
python scripts/dcf_valuation.py valuation_data.json --format json
python scripts/dcf_valuation.py valuation_data.json --projection-years 7

3. Budget Variance Analyzer (scripts/budget_variance_analyzer.py)

Analyze actual vs budget vs prior year performance with materiality filtering.

Features:

  • Dollar and percentage variance calculation
  • Materiality threshold filtering (default: 10% or $50K)
  • Favorable/unfavorable classification with revenue/expense logic
  • Department and category breakdown
  • Executive summary generation
python scripts/budget_variance_analyzer.py budget_data.json
python scripts/budget_variance_analyzer.py budget_data.json --format json
python scripts/budget_variance_analyzer.py budget_data.json --threshold-pct 5 --threshold-amt 25000

4. Forecast Builder (scripts/forecast_builder.py)

Driver-based revenue forecasting with rolling cash flow projection and scenario modeling.

Features:

  • Driver-based revenue forecast model
  • 13-week rolling cash flow projection
  • Scenario modeling (base/bull/bear cases)
  • Trend analysis using simple linear regression (standard library)
python scripts/forecast_builder.py forecast_data.json
python scripts/forecast_builder.py forecast_data.json --format json
python scripts/forecast_builder.py forecast_data.json --scenarios base,bull,bear

Knowledge Bases

| Reference | Purpose | |-----------|---------| | references/financial-ratios-guide.md | Ratio formulas, interpretation, industry benchmarks | | references/valuation-methodology.md | DCF methodology, WACC, terminal value, comps | | references/forecasting-best-practices.md | Driver-based forecasting, rolling forecasts, accuracy |

Templates

| Template | Purpose | |----------|---------| | assets/variance_report_template.md | Budget variance report template | | assets/dcf_analysis_template.md | DCF valuation analysis template | | assets/forecast_report_template.md | Revenue forecast report template |

Industry Adaptations

SaaS

  • Key metrics: MRR, ARR, CAC, LTV, Churn Rate, Net Revenue Retention
  • Revenue recognition: subscription-based, deferred revenue tracking
  • Unit economics: CAC payback period, LTV/CAC ratio
  • Cohort analysis for retention and expansion revenue

Retail

  • Key metrics: Same-store sales, Revenue per square foot, Inventory turnover
  • Seasonal adjustment factors in forecasting
  • Gross margin analysis by product category
  • Working capital cycle optimization

Manufacturing

  • Key metrics: Gross margin by product line, Capacity utilization, COGS breakdown
  • Bill of materials cost analysis
  • Absorption vs variable costing impact
  • Capital expenditure planning and ROI

Financial Services

  • Key metrics: Net Interest Margin, Efficiency Ratio, ROA, Tier 1 Capital
  • Regulatory capital requirements
  • Credit loss provisioning and reserves
  • Fee income analysis and diversification

Healthcare

  • Key metrics: Revenue per patient, Payer mix, Days in A/R, Operating margin
  • Reimbursement rate analysis by payer
  • Case mix index impact on revenue
  • Compliance cost allocation

Key Metrics & Targets

| Metric | Target | |--------|--------| | Forecast accuracy (revenue) | +/-5% | | Forecast accuracy (expenses) | +/-3% | | Report delivery | 100% on time | | Model documentation | Complete for all assumptions | | Variance explanation | 100% of material variances |

Input Data Format

All scripts accept JSON input files. See assets/sample_financial_data.json for the complete input schema covering all four tools.

Dependencies

None - All scripts use Python standard library only (math, statistics, json, argparse, datetime). No numpy, pandas, or scipy required.