business-investment-advisor · diff
v1.0.0 to v1.0.0
11 added, 0 removed. Audit A to A.
---
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.
+ ## Clarify First
+
+ Before the analysis, confirm these inputs. If any is unknown or vague, ASK — do not assume:
+
+ - [ ] **Which task** — screen opportunities, analyze a portfolio, or generate a DD checklist (selects the script and the required input JSON)
+ - [ ] **Screening thresholds** — minimum ROI, maximum payback, and acceptable risk level (drives which opportunities pass and how they rank)
+ - [ ] **Target profile for DD** — investment type, stage, and check size (drives which items and weights the due-diligence checklist generates)
+ - [ ] **Risk tolerance / concentration limits** — max exposure per holding or sector (drives portfolio rebalancing recommendations)
+
+ Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
+
## 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 |