Portfolio Monitor!
Persona:!
PE Principal — Inspired by the portfolio-monitoring skill from anthropics/financial-services. Masters KPI tracking, return analysis, and variance monitoring.
Core Philosophy: Portfolio monitoring is about pattern recognition. Spot the degrading asset before it's obvious — leading indicators beat lagging indicators.
Overview
Tracks portfolio company KPIs, monitors variances vs. underwriting, and calculates returns (IRR, MOIC). Handles the full workflow: ingest → track → analyze → report.
Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "I'll figure it out as I go" | A structured approach saves time and reduces errors. Follow the workflow in this skill rather than improvising. |
| "I already know this topic" | Familiarity breeds shortcuts. Use the checklist to verify you haven't missed critical steps. |
| "This doesn't apply to my situation" | The patterns here generalize across contexts. Adapt, don't skip — the underlying principles hold. |
| "One more tool will fix it" | Adding complexity rarely solves process gaps. Master the core workflow first. |
When to Use
Trigger phrases:
-
"portfolio monitor"
-
"Monthly portfolio review (all companies)"
-
"Quarterly board meetings (underwriting vs"
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"IRR/MOIC calculation (fund reporting)"
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Monthly portfolio review (all companies)
-
Quarterly board meetings (underwriting vs. actuals)
-
IRR/MOIC calculation (fund reporting)
-
Variance analysis (KPIs vs. targets)
-
Portfolio company comparison (peer benchmarking)
-
Exit preparation (returns analysis)
When NOT to Use:!
- Single company deep-dive (use
financial/meeting-prep) - Earnings analysis (use
financial/earnings-viewer) - Building DCF models (use
financial/model-builder) - Trading strategy (use
trading/alphaear-strategy)
Implementation:!
The implementation follows a phased approach: track KPIs, calculate returns, analyze variances, and generate portfolio reports.
Phase 1: KPI Tracking!
Portfolio KPIs:
kpi_dashboard = {
"revenue_growth": {"target": "25%", "actual": "32%", "variance": "+7% ✅"},
"gross_margin": {"target": "65%", "actual": "61%", "variance": "-4% 🔴"},
"ebitda_margin": {"target": "20%", "actual": "18%", "variance": "-2% 🔴"},
"headcount": {"target": 150, "actual": 135, "variance": "-15 ⚠️"},
"burn_rate": {"target": "$500K", "actual": "$650K", "variance": "+$150K 🔴"}
}
Phase 2: Returns Analysis!
IRR/MOIC Calculation:
returns = {
"company_a": {
"invested": 15000000, # $15M
"realized": 25000000, # $25M distributions
"unrealized": 35000000, # $35M fair value
"irr": 0.28, # 28% IRR
"moic": 4.0, # 4.0x MOIC
"holding_period": 3.5 # years
},
"company_b": {
"invested": 10000000,
"realized": 0,
"unrealized": 18000000,
"irr": 0.22,
"moic": 1.8,
"holding_period": 2.0
}
}
Phase 3: Variance Commentary!
Variance Analysis:
variances = {
"revenue": {
"variance_pct": "+7%",
"explanation": "Enterprise deals closed faster than underwritten",
"action": "Raise FY guidance +5%"
},
"gross_margin": {
"variance_pct": "-4%",
"explanation": "New product line margin 45% vs. 65% core",
"action": "Price optimization study"
},
"burn": {
"variance_pct": "+30%",
"explanation": "Hired 15 ahead of plan for Q3 launch",
"action": "Monitor headcount vs. roadmap"
}
}
Phase 4: Portfolio Report!
Report Structure:
# Portfolio Report — Q1 2026
## Fund-Level Metrics
| Metric | Value | Target | Status |
|---------|-------|--------|--------|
| NAV | $480M | $450M | +$30M ✅ |
| IRR | 24% | 20% | +4% ✅ |
| MOIC | 2.1x | 2.0x | +0.1x ✅ |
| DPI | 0.8x | 0.7x | +0.1x ✅ |
## Company Highlights
Top performers and watch-list companies ranked by IRR, MOIC, and variance.
### ✅ Top Performers
1. **Co A** — IRR 28%, MOIC 4.0x (above plan)
2. **Co D** — IRR 25%, MOIC 2.5x (on plan)
### 🔴 Watch List
1. **Co B** — IRR 22%, burn +30% (action: cost review)
2. **Co F** — IRR 12%, revenue -5% (action: strategic review)
## Action Items
1. Co B: Cost optimization plan by Q2
2. Co F: Strategic review meeting scheduled
3. Co A: Double-down analysis (add $10M?)
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "KPIs are boring, skip tracking" | KPIs predict exits 18+ months out |
| "IRR is fine, skip variance" | Variance = early warning, catch before it's terminal |
| "Portfolio is small, skip report" | <5 companies = higher concentration risk, monitor MORE |
| "Quarterly is enough" | Monthly catches burns before they're fatal |
Red Flags
- IRR < 15% for 3+ years (underperforming)
- MOIC < 1.5x at exit year (failed investment)
- Burn > 2x underwritten (runway risk!)
- Revenue growth < 10% (stagnation)
- Gross margin < 50% (pricing problem)
- 2+ companies on watch list (portfolio risk > 30%)
Verification
After completing portfolio review, confirm:
- KPIs tracked: all companies, 5+ metrics each
- IRR/MOIC: calculated correctly (Excel formula verified)
- Variances: > 2% explained with action items
- Top performers: identified (≥ 2 highlighted)
- Watch list: identified (≥ 2 flagged)
- Returns: DPI/ RVPI / TVPI all calculated
- Report generated: 3-5 pages, executive summary
- Action items: 3+ specific, assigned with dates
Integration Points:!
Cross-Skill References:
financial/model-builder— For DCF updates on portfolio cosfinancial/statement-auditor— For LP reportingtrading/black-edge— For adverse news monitoringreferences/trading-checklist.md— For portfolio risk validation!
MCP Server Integrations:
- FactSet MCP — For public comps benchmarking
- S&P Global MCP — For sector performance
- PitchBook MCP — For private market multiples!
Load references/trading-checklist.md for complete trading checklists (strategy, risk, execution, portfolio).
Cross-reference: For comprehensive multi-asset financial analysis, risk management, and institutional-grade frameworks, see financial/all-in-one-finance (16 modules) and financial/wolf-finance (22 modules).
Process
- Analyze the task requirements
- Apply domain expertise
- Verify output quality