About this skill

Problem

Catering finance and fund/ETF comparisons often stall on inconsistent metrics: revenue structure, cost items, drawdown, Sharpe ratio, and correlation are scattered, making conclusions feel subjective. This skill applies the fund-risk-analyzer approach to a repeatable analysis flow: define the question, choose a framework, prioritize actions, and set review checkpoints.

How It Works

Four-step workflow: problem definition and data collection, framework matching and analysis, solution generation and prioritization, execution and review.
Loaded references: framework-overview.md is the base; method-core.md, method-application.md, and method-advanced.md are pulled only when needed.
Templates and scripts: use checklist-quick-start.md and template-analysis.md for structured output, and risk_analyzer.py for max drawdown, Sharpe ratio, and correlation.
Output discipline: lead with numbers, state a diagnosis, Top3 actions, and detailed plan; label assumptions when data are missing.

Boundaries

Good for structured comparison, risk-metric calculation, and decision breakdown. Not a substitute for complete accounting data, correct data definitions, tax/compliance review, or professional investment advice.

Screenshots

Use Cases

During monthly restaurant operations review, compare revenue, cost, and profit metrics under a consistent structure and produce top actions.
When analyzing ETF or fund portfolios, screen risk using max drawdown, Sharpe ratio, and correlation, then output a comparable table.
In a business plan review, mark missing data as baseline assumptions and rank execution priorities as Top3 actions.
When a reusable template is needed, use the quick-start checklist and analysis template to produce structured output for later review.

Best For

Restaurant finance analysts who need to compare store revenue, cost, and profit in one structure and output Top3 actions.
Fund/ETF researchers who need to compare products or portfolios by max drawdown, Sharpe ratio, and correlation.
Data analysts who need to turn scattered metrics into structured conclusions and label assumptions for missing data.
Operations leaders who need to turn review results into owners, actions, and checkpoints.

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Catering Finance Multi-Dimensional Comparison