| name | financial-analysis |
| description | Standard operating procedure for board-ready financial analysis at TechStart Inc. Use whenever the user asks about runway, burn rate, cash position, financial forecasts, the cost or impact of hiring, or wants a financial summary for the board or leadership. |
Financial Analysis SOP
This skill defines how we run a financial analysis at TechStart Inc, so the answer is
consistent, grounded in real data, and board-ready every time. Follow these steps in order.
Step 1 — Ground in the data first (do NOT guess)
Before any calculation, read the relevant source data in financial_data/:
financial_data/burn_rate.csv — monthly burn, headcount, revenue, net burn (historical)financial_data/revenue_forecast.json — current ARR, monthly growth rate, forward projectionsfinancial_data/hiring_costs.csv — loaded monthly cost per role/level
Use the company facts in CLAUDE.md (burn ~$500K/mo, 20 months runway, $10M cash, $2.4M ARR)
as context, but prefer the numbers in financial_data/ when they conflict — that is the source of truth.
Step 2 — Run the right script (don't hand-calculate)
Compute with the project scripts via Bash rather than estimating in your head. Pick by question type:
| Question is about… | Run | Example |
|---|
| Runway / burn from a cash balance | scripts/simple_calculation.py <total_cash> <monthly_burn> | python scripts/simple_calculation.py 10000000 500000 |
| ARR / revenue projection over time | scripts/financial_forecast.py --arr <arr> --growth <rate> --months <n> --burn <burn> --format json | python scripts/financial_forecast.py --arr 2400000 --growth 0.15 --months 12 --format json |
| Cost/impact of hiring N engineers | scripts/hiring_impact.py <num_engineers> [salary] | python scripts/hiring_impact.py 10 200000 |
Each script prints JSON — parse it and use the exact numbers it returns.
For an open-ended strategic trade-off (e.g. "should we hire or extend runway?"), you may delegate to the
financial-analyst subagent via the Task tool for deeper modeling. Use this skill for the standard
runway/burn/forecast/hiring questions; delegate only when the analysis is genuinely open-ended.
Step 3 — Present in the standard structure
Always report results in this fixed order:
- Headline metric — the single number that answers the question (e.g. "Runway: 20 months").
- Key drivers — the 2–4 inputs that drive it (burn rate, growth, headcount cost), with values.
- Recommendation — one clear, actionable next step tied to the current Q2 priorities in
CLAUDE.md.
Keep it tight and decision-oriented — this is for the CEO and the board, not a spreadsheet dump.
Cite which data file and script produced the numbers so the analysis is auditable.
