fund-operations

Compute fund KPIs (TVPI, DPI, IRR, MOIC), model carried interest and management fees, and generate LP quarterly update narratives. Triggered by: "/venture-capital-intelligence:fund-operations", "calculate fund KPIs", "what is my fund TVPI", "IRR calculation", "compute MOIC", "LP report", "quarterly update draft", "carried interest calculation", "management fee calculation", "fund performance report", "write my LP update", "how is my fund performing", "what is my DPI", "fund returns analysis", "model my carry", "how much carry do I earn", "portfolio performance summary", "generate investor update". Claude Code only. Requires Python 3.x.

2,707 stars

Best use case

fund-operations is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Compute fund KPIs (TVPI, DPI, IRR, MOIC), model carried interest and management fees, and generate LP quarterly update narratives. Triggered by: "/venture-capital-intelligence:fund-operations", "calculate fund KPIs", "what is my fund TVPI", "IRR calculation", "compute MOIC", "LP report", "quarterly update draft", "carried interest calculation", "management fee calculation", "fund performance report", "write my LP update", "how is my fund performing", "what is my DPI", "fund returns analysis", "model my carry", "how much carry do I earn", "portfolio performance summary", "generate investor update". Claude Code only. Requires Python 3.x.

Teams using fund-operations should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/fund-operations/SKILL.md --create-dirs "https://raw.githubusercontent.com/davepoon/buildwithclaude/main/plugins/venture-capital-intelligence/skills/fund-operations/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/fund-operations/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How fund-operations Compares

Feature / Agentfund-operationsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Compute fund KPIs (TVPI, DPI, IRR, MOIC), model carried interest and management fees, and generate LP quarterly update narratives. Triggered by: "/venture-capital-intelligence:fund-operations", "calculate fund KPIs", "what is my fund TVPI", "IRR calculation", "compute MOIC", "LP report", "quarterly update draft", "carried interest calculation", "management fee calculation", "fund performance report", "write my LP update", "how is my fund performing", "what is my DPI", "fund returns analysis", "model my carry", "how much carry do I earn", "portfolio performance summary", "generate investor update". Claude Code only. Requires Python 3.x.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Venture Capital Intelligence — Fund Operations Agent

You are a fund administrator and CFO for a venture capital fund. You compute LP-grade fund metrics, model carried interest and management fees, and draft LP quarterly narratives.

**Pipeline:** Claude collects fund data → Python computes KPIs and economics → Claude writes LP narrative → Python formats report

---

## STEP 1 — COLLECT FUND DATA

Ask for or extract:

**Fund basics:**
- Fund name
- Fund size (committed capital $)
- Vintage year (year of first close)
- Fund life (years, default 10)
- Management fee % (default 2%)
- Carry % (default 20%)
- Hurdle rate % (default 8%)

**Portfolio companies:**
For each investment:
```
Company name | Invested amount | Current fair value | Realized proceeds | Investment date | Status (active/exited)
```

**Cash flows (for IRR):**
- Capital call dates and amounts
- Distribution dates and amounts

---

## STEP 2 — CLAUDE: PREPARE FUND INPUTS

Save to `${CLAUDE_PLUGIN_ROOT}/skills/fund-operations/output/fund_inputs.json`:

```json
{
  "fund_name": "",
  "committed_capital": 0,
  "vintage_year": 2020,
  "current_year": 2025,
  "management_fee_pct": 0.02,
  "carry_pct": 0.20,
  "hurdle_rate": 0.08,
  "fund_life_years": 10,
  "investments": [
    {
      "company": "",
      "invested": 0,
      "current_fmv": 0,
      "realized": 0,
      "investment_date": "YYYY-MM",
      "status": "active"
    }
  ],
  "cash_flows": [
    {"date": "YYYY-MM", "amount": 0, "type": "call"}
  ]
}
```

---

## STEP 3 — PYTHON: COMPUTE FUND KPIs AND ECONOMICS

Run: `python "${CLAUDE_PLUGIN_ROOT}/skills/fund-operations/scripts/fund_kpi_calc.py"`

Computes:
- **TVPI** = (Realized + Unrealized FMV) / Total Invested
- **DPI** = Realized / Total Invested
- **RVPI** = Unrealized FMV / Total Invested
- **IRR** = Annualized return on capital calls and distributions
- **MOIC** per company and fund-level
- **Management fee** total paid to date
- **Carry** earned / projected at current valuations
- **J-curve position** (are we in the valley? turning up?)

Writes `fund_output.json`.

---

## STEP 4 — CLAUDE: WRITE LP QUARTERLY NARRATIVE

Using fund_output.json, write a 300-word LP quarterly update in the tone of a professional fund manager:

**Structure:**
1. **Opening** (1 sentence): Quarter summary in one line
2. **Portfolio highlights** (2–3 bullets): Top performing companies, key milestones
3. **Fund metrics** (reference numbers): TVPI, DPI, top MOIC companies
4. **Market context** (1 paragraph): Macro conditions affecting portfolio and new investments
5. **New investments** (if any): Brief description of new deals
6. **Exits/realizations** (if any): What was returned to LPs and why
7. **Outlook** (1 paragraph): Forward-looking, honest, no hype

**Tone:** Professional, honest, direct. LPs are sophisticated. Never say "exciting" or "pleased to announce." Say what happened and what it means.

---

## STEP 5 — PYTHON: FORMAT FINAL REPORT

Run: `python "${CLAUDE_PLUGIN_ROOT}/skills/fund-operations/scripts/fund_formatter.py"`

---

## KEY FORMULAS

```
TVPI = (Sum(Realized) + Sum(Current FMV)) / Sum(Invested)
DPI  = Sum(Realized) / Sum(Invested)
RVPI = Sum(Current FMV) / Sum(Invested)
MOIC per company = (Realized + Current FMV) / Invested

Management Fee (investment period, yrs 1-5):
  Annual fee = committed_capital × management_fee_pct

Carried Interest (European waterfall):
  1. LPs get all capital back
  2. LPs get preferred return (hurdle rate × capital × years)
  3. GP catch-up (until GP has 20% of total profits)
  4. 80/20 split of remaining profits

J-Curve: Fund is typically negative TVPI in years 1-3 (fees + no exits),
  turns positive at year 4-6 as portfolio matures.
```

Related Skills

soft-screening-startup

2707
from davepoon/buildwithclaude

Activate for ANY startup evaluation, investment screening, or company assessment. Triggers include: "evaluate this startup", "screen this company", "should I invest in X", "is this a good investment", "what do you think about this company", "review this startup", "score this company", "rate this pitch", "assess this founder", "quick take on X", "is X worth investing in", "pass or decline on X", "what's your verdict on X", "first look at this company", "quick screen on X", "what's your take on this founder", "is this fundable", "would a VC invest in this". Also triggers when a user pastes a company description, funding ask, or founder background and asks for an opinion. Works on claude.ai and Claude Code. For hard-mode deterministic scoring with Python audit trail, use /venture-capital-intelligence:hard-screening-startup.

market-size

2707
from davepoon/buildwithclaude

Run TAM/SAM/SOM market sizing with top-down and bottom-up methods, competitive landscape, and tech stack analysis. Triggered by: "/venture-capital-intelligence:market-size", "size this market", "what is the TAM for X", "market sizing analysis", "competitive landscape for X", "who are the competitors", "TAM SAM SOM for X", "market opportunity analysis", "how big is this market", "is this market big enough", "what's the addressable market", "total addressable market for X", "how large is the opportunity", "market research for X", "how saturated is this market", "market size estimate", "go-to-market sizing", "what is the serviceable market". Claude Code only. Requires Python 3.x. Uses web search for market data.

hard-screening-startup

2707
from davepoon/buildwithclaude

Deterministic Python-scored startup screening with full audit trail. Use when you need a reproducible, weighted-score verdict on a startup — not just a qualitative opinion. Triggered by: "/venture-capital-intelligence:hard-screening-startup", "hard screen this startup", "run a hard screen on X", "score this startup with Python", "give me an auditable screen", "run a scored evaluation on X", "give me a weighted score for this startup", "screen with numbers", "objective startup score", "reproducible screen", "investment scorecard for X", "score this company out of 100", "run the full screen on X". Claude Code only. Requires Python 3.x. For conversational soft-mode screening, use /venture-capital-intelligence:soft-screening-startup.

financial-model

2707
from davepoon/buildwithclaude

Run deterministic financial models for startup valuation and SaaS health analysis. Triggered by: "/venture-capital-intelligence:financial-model", "run a financial model on X", "DCF this company", "model the financials", "calculate runway", "what is the valuation", "SaaS metrics model", "LTV CAC analysis", "unit economics", "burn rate analysis", "comparable valuation", "how long is my runway", "what's my burn multiple", "revenue projection for X", "model the ARR growth", "what is the pre-money valuation", "comps analysis", "NRR and churn model", "how healthy are these SaaS metrics". Claude Code only. Requires Python 3.x. Accepts user-supplied numbers or searches for publicly available data.

explain-equity-terms

2707
from davepoon/buildwithclaude

Activate for ANY equity, legal, or term sheet question related to startup investing or fundraising. Triggers include: "what is a SAFE", "explain this term sheet", "what does pro-rata mean", "what is liquidation preference", "explain anti-dilution", "ISO vs NSO", "what is a 83(b) election", "what is carried interest", "explain drag-along", "what is a valuation cap", "what does MFN mean", "explain convertible note vs SAFE", "what is a down round", "explain vesting cliff", "what does fully diluted mean", "term sheet question", "equity question", "what does this clause mean". Also triggers when a user pastes legal text from a term sheet, SAFE, or subscription agreement and asks what it means. Works on claude.ai and Claude Code.

deal-sourcing-signals

2707
from davepoon/buildwithclaude

Scan a company or sector for deal-sourcing signals across 6 dimensions. Triggered by: "/venture-capital-intelligence:deal-sourcing-signals", "scan signals for X", "what signals is X showing", "deal sourcing scan", "hiring signals for X", "is X raising soon", "monitor this company", "company signal scan", "sourcing brief for X", "what is X up to", "is X growing", "track this company", "deal signal report for X", "is this company fundraising", "what are the momentum signals for X", "find signals on X", "is X worth tracking". Claude Code only. Requires Python 3.x. Uses web search for live signal data.

cap-table-waterfall

2707
from davepoon/buildwithclaude

Model cap table dilution, SAFE conversion, and exit waterfall across scenarios. Triggered by: "/venture-capital-intelligence:cap-table-waterfall", "model my cap table", "simulate dilution", "SAFE conversion math", "exit waterfall", "how much do I own after Series A", "liquidation waterfall", "cap table scenario", "what happens to equity at exit", "model the waterfall", "how much equity do I have left", "what is my ownership after funding", "run dilution scenarios", "model a new round", "what happens at acquisition", "cap table after SAFE conversion", "pari passu waterfall", "preference stack analysis". Claude Code only. Requires Python 3.x.

analyze-pitch-deck

2707
from davepoon/buildwithclaude

Activate for ANY pitch deck analysis, feedback, or review request. Triggers include: "analyze this deck", "review my pitch deck", "critique my pitch", "feedback on my slides", "is my deck investor ready", "what's wrong with my pitch", "how would a VC react to this deck", "score my pitch deck", "rate my slides", "improve my deck", "what slides am I missing", "is this pitch compelling". Also triggers when a user pastes slide content, describes their deck structure, or shares a company narrative and asks for investor feedback. Works on claude.ai and Claude Code.

public-plugin-builder

2707
from davepoon/buildwithclaude

Activate when the user wants to build a Claude plugin, create a Claude skill, make a Claude agent, structure a Claude Code plugin, says "build a plugin", "create a skill", "new claude skill", "new agent", "help me make a plugin", "plugin builder", "claude plugin helper", "how do I build a Claude skill", "I want to create a Claude plugin", "plugin building", or asks how to structure a Claude Code plugin or publish to the Claude marketplace. Works on both claude.ai (generates files as code blocks) and Claude Code (writes and pushes files).

server-components

2707
from davepoon/buildwithclaude

This skill should be used when the user asks about "Server Components", "Client Components", "'use client' directive", "when to use server vs client", "RSC patterns", "component composition", "data fetching in components", or needs guidance on React Server Components architecture in Next.js.

server-actions

2707
from davepoon/buildwithclaude

This skill should be used when the user asks about "Server Actions", "form handling in Next.js", "mutations", "useFormState", "useFormStatus", "revalidatePath", "revalidateTag", or needs guidance on data mutations and form submissions in Next.js App Router.

route-handlers

2707
from davepoon/buildwithclaude

This skill should be used when the user asks to "create an API route", "add an endpoint", "build a REST API", "handle POST requests", "create route handlers", "stream responses", or needs guidance on Next.js API development in the App Router.