--- name: business-investment-advisor description: > This skill should be used when the user asks to "screen investments", "analyze a portfolio", "evaluate investment opportunities", "run due diligence", "assess investment risk", "calculate ROI", or "diversify portfolio holdings". license: MIT + Commons Clause metadata: version: 1.0.0 author: borghei category: finance domain: investment updated: 2026-04-02 tags: [investment, portfolio, due-diligence, roi, risk-analysis, diversification] --- # Business Investment Advisor Skill ## Overview Production-ready investment analysis toolkit for screening opportunities, analyzing portfolio composition, and generating due diligence checklists. Designed for business owners, angel investors, and corporate development teams evaluating investments from $50K to $50M. ## Quick Start ```bash # Screen investments by criteria (ROI, risk, payback) python scripts/investment_screener.py opportunities.json --min-roi 15 --max-payback 36 # Analyze portfolio diversification and risk exposure python scripts/portfolio_analyzer.py portfolio.json # Generate due diligence checklist for an investment target python scripts/due_diligence_checklist.py --type saas --stage series-a --amount 500000 ``` ## Tools Overview | Tool | Purpose | Input | Output | |------|---------|-------|--------| | `investment_screener.py` | Filter & rank investments | JSON with opportunity data | Ranked opportunities + scores | | `portfolio_analyzer.py` | Portfolio risk & diversification | JSON with holdings | Risk report + recommendations | | `due_diligence_checklist.py` | DD checklist generation | Investment parameters | Structured checklist + scoring | ## Workflows ### Workflow 1: Opportunity Evaluation Pipeline 1. Compile investment opportunities into JSON format (see Common Patterns) 2. Run `investment_screener.py` with your criteria filters 3. Review ranked results focusing on composite score 4. For top candidates, run `due_diligence_checklist.py` to generate investigation plan 5. After DD completion, update portfolio model and run `portfolio_analyzer.py` ### Workflow 2: Portfolio Health Check 1. Export current holdings to JSON format 2. Run `portfolio_analyzer.py` to assess diversification 3. Review concentration risk, sector exposure, and liquidity analysis 4. Use recommendations to identify rebalancing opportunities 5. Screen new opportunities with `investment_screener.py` to fill gaps ### Workflow 3: Due Diligence Sprint 1. Run `due_diligence_checklist.py` with target parameters 2. Assign checklist items to team members with deadlines 3. Score each item as investigation progresses (0-10) 4. Re-run with `--score-file` to get weighted DD score 5. Use composite score to support go/no-go decision ## Reference Documentation See `references/investment-frameworks.md` for detailed frameworks including: - Investment scoring methodology - Risk assessment matrix - Portfolio diversification guidelines - Due diligence phase frameworks - Industry-specific evaluation criteria ## Common Patterns ### Pattern: Investment Opportunities JSON ```json { "opportunities": [ { "name": "TechCo SaaS", "type": "equity", "sector": "technology", "stage": "series-a", "amount": 250000, "expected_roi_pct": 25.0, "risk_level": "high", "payback_months": 36, "revenue": 1200000, "revenue_growth_pct": 85.0, "gross_margin_pct": 78.0, "burn_rate_monthly": 80000, "runway_months": 18 } ] } ``` ### Pattern: Portfolio Holdings JSON ```json { "portfolio": { "total_invested": 2000000, "holdings": [ { "name": "Investment A", "type": "equity", "sector": "technology", "invested": 250000, "current_value": 375000, "date_invested": "2024-06-15", "stage": "series-a", "liquidity": "illiquid", "status": "active" } ] } } ``` ### Risk Level Definitions | Level | Expected Return | Loss Probability | Typical Payback | |-------|----------------|-----------------|-----------------| | Low | 5-10% | < 10% | < 24 months | | Medium | 10-20% | 10-30% | 24-48 months | | High | 20-40% | 30-50% | 36-60 months | | Very High | 40%+ | > 50% | 48+ months |