Install
$ agentstack add skill-the-ai-directory-company-agents-and-skills-financial-model ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Financial Model
Before you start
Gather the following from the user. If anything is missing, ask before proceeding:
- What is the business case? (New product launch, expansion, investment decision, fundraising)
- What is the time horizon? (12 months, 3 years, 5 years)
- What is the revenue model? (Subscription, transactional, marketplace, usage-based, hybrid)
- What are the key cost drivers? (Headcount, infrastructure, CAC, COGS)
- What assumptions exist? (Growth rates, conversion rates, churn, pricing, market size)
- Who is the audience? (Board, investors, internal leadership, lending institution)
If the user says "just give me a spreadsheet," push back: a model without documented assumptions is a fiction generator. Every number must trace to an assumption the reader can challenge.
Financial model template
1. Assumptions Table
List every assumption explicitly. Each must have a source and confidence level.
| Assumption | Value | Source | Confidence |
|--------------------------|-----------|------------------------------|------------|
| Monthly growth rate | 8% | Last 6 months average | High |
| Gross margin | 72% | Current P&L | High |
| CAC (blended) | $340 | Marketing spend / new custs | Medium |
| Monthly churn rate | 3.2% | Cohort analysis (Q3-Q4) | High |
| Average contract value | $1,200/yr | Sales data | High |
Rules: assumptions with "Low" confidence must appear in sensitivity analysis. Never bury assumptions inside formulas.
2. Revenue Projections
Build revenue bottom-up from unit economics, not top-down from market share.
| Metric | Month 1 | Month 6 | Month 12 | Month 24 | Month 36 |
|---------------------|----------|----------|----------|----------|----------|
| New customers | 50 | 85 | 145 | 310 | 525 |
| Churned customers | 8 | 22 | 48 | 95 | 155 |
| Active customers | 200 | 420 | 780 | 1,650 | 2,850 |
| ARPU (monthly) | $100 | $105 | $112 | $120 | $128 |
| MRR | $20,000 | $44,100 | $87,360 | $198,000 | $364,800 |
Show the formula for each row. MRR = Active customers x ARPU. Active customers = prior active + new - churned.
3. Cost Structure
Break costs into fixed and variable. Variable costs must link to a driver.
| Cost Category | Type | Driver | Month 1 | Month 12 | Month 36 |
|--------------------|----------|--------------------|----------|----------|----------|
| Engineering team | Fixed | Headcount plan | $85,000 | $120,000 | $200,000 |
| Cloud infra | Variable | Per active customer| $4,000 | $15,600 | $57,000 |
| Sales & marketing | Variable | CAC x new custs | $17,000 | $49,300 | $178,500 |
| G&A | Fixed | Baseline ops | $15,000 | $22,000 | $35,000 |
4. Unit Economics
| Metric | Current | Month 12 | Healthy Benchmark |
|--------------------------------|---------|----------|-------------------|
| CAC | $340 | $340 | 3x CAC |
| LTV:CAC ratio | 6.6x | 7.7x | > 3x |
| CAC payback (months) | 3.4 | 3.2 | 65% (SaaS) |
Flag any metric outside healthy benchmarks. If LTV:CAC is below 3x, the business case is weak regardless of revenue projections.
5. Scenario Analysis
Model three scenarios minimum. Vary the assumptions with lowest confidence.
| Metric (Month 36) | Bear Case | Base Case | Bull Case |
|---------------------|------------|------------|------------|
| Growth rate | 5%/mo | 8%/mo | 12%/mo |
| Churn rate | 4.5% | 3.2% | 2.0% |
| Active customers | 1,400 | 2,850 | 5,200 |
| ARR | $2.15M | $4.38M | $7.98M |
| Cash position | -$800K | $1.2M | $4.5M |
Name what changes between scenarios. "Bear case" is not useful — "bear case: growth drops to 5% and churn increases to 4.5%" tells the reader what to watch for.
6. Cash Flow and Runway
Highlight the month cash reaches zero under bear case. If runway is under 6 months in any scenario, flag it as a critical risk. Include quarterly revenue, costs, net cash flow, cumulative cash balance, and remaining runway in months.
Quality checklist
Before delivering a financial model, verify:
- [ ] Every number traces to a named assumption with a source
- [ ] Revenue is built bottom-up from unit economics, not top-down from TAM
- [ ] Cost structure separates fixed from variable with explicit drivers
- [ ] Unit economics include LTV, CAC, LTV:CAC ratio, and payback period
- [ ] At least 3 scenarios are modeled with named assumption changes
- [ ] Cash flow projection includes runway calculation
- [ ] The model audience (investors, board, internal) is reflected in the level of detail
Common mistakes
- Top-down revenue. "We will capture 1% of a $10B market" is not a model. Build from units: customers x price x retention.
- Static assumptions. Growth rates, churn, and costs change over time. A model with constant 10% monthly growth for 5 years is fantasy.
- Ignoring cash timing. Revenue recognized is not cash received. Annual contracts paid monthly and net-60 invoices create cash gaps the P&L hides.
- Single scenario. One projection is a guess. Three scenarios with named variables show you understand the risk space.
- Vanity unit economics. Calculating LTV with gross revenue instead of gross margin inflates the numbers. Use gross-margin-based LTV.
- Missing the "so what." A model without a recommendation is a data dump. State the decision it supports.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: The-AI-Directory-Company
- Source: The-AI-Directory-Company/agents-and-skills
- License: MIT
- Homepage: https://ai-directory.company
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.