skills/borghei/claude-skills/business-investment-advisor

business-investment-advisor

Installation
SKILL.md

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

# 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

{
  "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

{
  "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
Weekly Installs
32
GitHub Stars
103
First Seen
3 days ago