The agent acts as a fractional CFO, providing financial strategy and operational finance guidance grounded in SaaS benchmarks, GAAP standards, and investor expectations.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncfo-advisorExecute the skills CLI command in your project's root directory to begin installation:
Fetches cfo-advisor from borghei/claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate cfo-advisor. Access via /cfo-advisor in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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The agent acts as a fractional CFO, providing financial strategy and operational finance guidance grounded in SaaS benchmarks, GAAP standards, and investor expectations.
CAC = (Sales + Marketing Spend) / New Customers
CAC Payback = CAC / (ARPU x Gross Margin)
LTV = ARPU x Gross Margin x Customer Lifetime
LTV:CAC Ratio = LTV / CAC Target: > 3:1
Logo Retention = (Customers End - New) / Customers Start
Net Revenue Retention = (MRR End - Churn + Expansion) / MRR Start
Burn Multiple = Net Burn / Net New ARR
< 1.0x Excellent efficiency
1.0-1.5x Good efficiency
1.5-2.0x Average
> 2.0x Needs improvement
Rule of 40 = Revenue Growth % + Profit Margin %
> 40% Strong performance
20-40% Acceptable
< 20% Needs attention
FINANCIAL HIGHLIGHTS
- Revenue: $X.XM (vs Plan: +/-Y%)
- Gross Margin: XX% (vs Plan: +/-Y%)
- Operating Loss: $X.XM (vs Plan: +/-Y%)
- Cash Balance: $X.XM
- Runway: XX months
REVENUE METRICS
- ARR: $X.XM (+Y% QoQ)
- Net New ARR: $XXK
- NRR: XXX%
- Logo Churn: X.X%
EFFICIENCY METRICS
- CAC: $X,XXX
- CAC Payback: XX months
- Burn Multiple: X.Xx
| Category | Line Items |
|---|---|
| Revenue | New business (by segment), expansion, renewals, professional services |
| Cost of Revenue | Hosting/infrastructure, support, PS delivery, payment processing |
| OpEx | Sales & Marketing, R&D, G&A |
| Days | Activity |
|---|---|
| 1-3 | Transaction cutoff |
| 3-5 | Reconciliations |
| 5-7 | Accruals and adjustments |
| 7-10 | Management review |
| 10-12 | Final close |
Quality Checklist: Bank reconciliation, revenue recognition, expense accruals, prepaid amortization, deferred revenue, intercompany elimination, flux analysis.
SaaS considerations: Subscription vs usage revenue, implementation services, professional services, multi-year contracts, discounts and credits.
13-Week Cash Flow: Week-by-week projections of all known inflows/outflows. Review weekly. Maintain minimum cash buffer.
Monthly Rolling Forecast: 12-month forward view covering revenue collection timing, payroll, vendor payments, debt service, and CapEx.
Treasury Principles: Maintain 6+ months runway, preserve capital, optimize yield on idle cash, follow investment policy.
Cash Preservation Levers (when extending runway):
Financial data:
Projections:
| Risk Type | Key Concerns |
|---|---|
| Market | Interest rate exposure, FX exposure, customer concentration |
| Credit | Customer creditworthiness, AR aging, bad debt reserves |
| Operational | Internal controls, fraud prevention, systems reliability |
A Series-A company ($3M ARR, 35 employees, $12M raised) preparing for Series B:
Unit Economics:
CAC: $22K | LTV: $88K | LTV:CAC: 4.0x | CAC Payback: 16 months
NRR: 115% | Logo Retention: 90% | Gross Margin: 78%
Burn:
Monthly burn: $350K | Net new ARR/month: $180K
Burn Multiple: 1.9x (average -- needs improvement for Series B)
Cash: $5.2M | Runway: 15 months
Rule of 40:
Revenue growth: 95% YoY | Profit margin: -40%
Score: 55% (strong)
Board recommendation: Raise in 6 months at current trajectory.
Target metrics for raise: Burn Multiple < 1.5x, NRR > 120%.
D&O, E&O, Cyber liability, General liability, Workers compensation, Key person insurance.
# Unit economics calculator
python scripts/unit_economics.py --metrics data.csv
# Cash flow projector
python scripts/cash_forecast.py --actuals Q1.csv --assumptions model.yaml
# Financial model builder
python scripts/fin_model.py --template saas --output model.xlsx
# Investor metrics dashboard
python scripts/investor_metrics.py --period monthly
references/financial_modeling.md -- Model building guidereferences/saas_metrics.md -- SaaS metrics deep divereferences/accounting_policies.md -- Policy documentationreferences/audit_prep.md -- Audit readiness guideComprehensive SaaS financial health assessment: Rule of 40, burn multiple, LTV:CAC, CAC payback, NRR, magic number, and composite score with investor-readiness verdict.
# Run with demo data (Series A SaaS)
python scripts/financial_health_scorer.py
# Quick assessment with key metrics
python scripts/financial_health_scorer.py --arr 3000000 --revenue-growth 95 --profit-margin -40 --burn 350000 --cash 5200000 --nrr 115 --gross-margin 78 --headcount 35
# From JSON file
python scripts/financial_health_scorer.py --input financials.json
# JSON output
python scripts/financial_health_scorer.py --input financials.json --json
Models burn rate, runway under 5 scenarios (current, hiring freeze, 10% cut, 20% cut, revenue acceleration), generates 13-week cash flow forecast, and identifies action triggers.
# Run with demo data
python scripts/burn_rate_calculator.py
# Quick calculation
python scripts/burn_rate_calculator.py --cash 5200000 --revenue 250000 --expenses 600000 --headcount 35
# JSON output
python scripts/burn_rate_calculator.py --json
Three-scenario financial projection engine with probability weighting, sensitivity analysis, and decision triggers. Projects base, upside, and downside cases over 8 quarters.
# Run with demo data
python scripts/scenario_modeler.py
# Quick model from key inputs
python scripts/scenario_modeler.py --arr 3000000 --expenses 900000 --cash 5200000 --quarters 8
# From JSON with custom scenarios
python scripts/scenario_modeler.py --input scenarios.json
# JSON output
python scripts/scenario_modeler.py --json
| Problem | Likely Cause | Fix |
|---|---|---|
| Burn multiple shows > 3.0x | Spending significantly outpaces net new ARR | Audit S&M efficiency; consider hiring freeze; validate pipeline conversion rates |
| Rule of 40 score below 20% | Growth has slowed without corresponding margin improvement | Either re-accelerate growth or cut costs to improve margins -- cannot stay in the middle |
| CAC payback exceeds 24 months | Sales cycle too long, ACV too low, or S&M spend too high | Segment CAC by channel; cut underperforming channels; raise ACV through pricing |
| LTV:CAC ratio below 2.0x | Customer lifetime too short (churn) or acquisition too expensive | Address churn first (higher ROI); then optimize CAC by channel |
| NRR below 100% | Contraction and churn exceed expansion revenue | Build expansion playbook; segment churning customers; invest in customer success |
| Financial model assumptions questioned by board | Assumptions not documented or unrealistic | Document every assumption explicitly; show sensitivity analysis for key variables |
| Month-end close takes 15+ days | Manual processes, missing reconciliations, or unclear ownership | Implement the Day 1-12 close timeline; assign owners to each checklist item |
In Scope: SaaS unit economics, burn rate analysis, financial modeling, cash management, investor reporting, month-end close, revenue recognition (ASC 606), due diligence preparation, scenario modeling.
Out of Scope: Tax planning, legal entity structuring, audit execution, payroll processing, accounts payable/receivable operations, insurance procurement, equity cap table management.
Limitations: Financial health scorer uses industry benchmarks that may not apply to non-SaaS business models. Burn rate calculator uses linear/exponential approximations -- actual cash flows vary with billing cycles and payment timing. Scenario modeler provides directional guidance, not auditable financial projections.
| Skill | Integration |
|---|---|
ceo-advisor |
Financial scenarios feed board strategy discussions |
board-deck-builder |
Financial update section; all deck numbers validated through CFO tools |
cro-advisor |
Revenue forecasting; pipeline-to-revenue conversion assumptions |
chro-advisor |
Headcount budget modeling; fully-loaded cost calculations |
ciso-advisor |
Compliance budget sizing against quantified risk exposure |
company-os |
Financial metrics in the weekly scorecard |
chief-of-staff |
Routes financial questions; synthesizes CFO + CEO perspectives |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
cfo-advisor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for cfo-advisor matched our evaluation — installs cleanly and behaves as described in the markdown.
cfo-advisor reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend cfo-advisor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in cfo-advisor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in cfo-advisor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend cfo-advisor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added cfo-advisor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in cfo-advisor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend cfo-advisor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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