Agent skill

Cap Table Waterfall

by davepoon in davepoon/buildwithclaude

Model cap table dilution, SAFE conversion, and exit waterfall across scenarios.

MITAuto-check passedBusiness, Finance & HR

Install Cap Table Waterfall

skills CLI
$ npx skills add davepoon/buildwithclaude --skill cap-table-waterfall -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davepoon/buildwithclaude cap-table-waterfall --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davepoon/buildwithclaude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/venture-capital-intelligence/skills/cap-table-waterfall .claude/skills/cap-table-waterfall && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cap-table-waterfall
GitHub stars
3.6k
Token cost
~1.1k tokens
SKILL.md length
298 words
Files
4 (incl. scripts)
Skills in repo
245
Repo updated
First seen
Licence
MIT

At a glance

Model cap table dilution, SAFE conversion, and exit waterfall across scenarios.

  • Works in 5 steps: COLLECT CAP TABLE STRUCTURE → CLAUDE: PREPARE INPUTS (OCF-COMPATIBLE) → PYTHON: COMPUTE DILUTION AND SAFE… → …
  • Tasks that involve Financial modeling
  • SKILL.md covers STEP 1 — COLLECT CAP TABLE…, STEP 2 — CLAUDE: PREPARE…, STEP 3 — PYTHON: COMPUTE… and STEP 4 — PYTHON: RUN EXIT…, plus 2 more sections
  • Runs Python scripts from its folder; calls python

What it does

Cap Table Waterfall is an agent skill 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…

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `scripts/captable_calc.py`, `scripts/waterfall_calc.py` and `scripts/waterfall_formatter.py`).

It sits in Business, Finance & HR, covering Financial modeling and Fundraising and pitch decks. It works with Python. The repository describes itself as: A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins, and Marketplace collections to extend Claude Code, Claude Desktop, Agent SDK and OpenClaw. The licence is MIT.

When your agent uses it

  • Tasks that involve Financial modeling
  • Tasks that involve Fundraising and pitch decks

Example prompts

  • “/venture-capital-intelligence:cap-table-waterfall”
  • “model my cap table”
  • “simulate dilution”
  • “/cap-table-waterfall”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. COLLECT CAP TABLE STRUCTURE
  2. CLAUDE: PREPARE INPUTS (OCF-COMPATIBLE)
  3. PYTHON: COMPUTE DILUTION AND SAFE CONVERSION
  4. PYTHON: RUN EXIT WATERFALL
  5. PYTHON: FORMAT FINAL REPORT

What it can do on your machine

Read from SKILL.md and the folder at commit 10bfc43. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cap Table Waterfall loads about 1.1k tokens when it runs. Until then it costs about 167 tokens; SKILL.md has 298 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~167
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from davepoon/buildwithclaude at commit 10bfc43, republished under its MIT licence (© davepoon). 298 words, ~1,131 tokens.

Download SKILL.mdSave it as .claude/skills/cap-table-waterfall/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
cap-table-waterfall
description
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.
category
business-finance
platform
claude-code
requires
python3

Venture Capital Intelligence — Cap Table & Waterfall Agent

You are a VC fund attorney and cap table specialist. You model equity ownership across funding rounds, compute SAFE conversions at the next priced round, and run exit waterfalls under multiple scenarios.

Data standard: Uses Open Cap Format (OCF) — the industry JSON schema backed by Carta, Cooley, and NVCA.

Pipeline: Claude collects structure → Python computes dilution + conversion → Claude interprets → Python models waterfall → Python formats report


STEP 1 — COLLECT CAP TABLE STRUCTURE

Ask for or extract:

Current Ownership:

  • Founders: name, shares, type (common)
  • Investors: name, shares/amount, type (common/preferred/SAFE/note)
  • Employee option pool: total authorized, granted, remaining
  • Any existing SAFEs or convertible notes

For each SAFE/Note:

  • Principal amount ($)
  • Valuation cap ($)
  • Discount rate (%)
  • Type: post-money SAFE / pre-money SAFE / convertible note

Proposed financing (if modeling a new round):

  • New round type (Series A, Seed, etc.)
  • Pre-money valuation ($)
  • New money raised ($)
  • New option pool (% of post-money)

Exit scenarios:

  • Scenario A exit price ($)
  • Scenario B exit price ($)
  • Scenario C exit price ($)

Liquidation terms (if priced round exists):

  • Preference type: non-participating / participating
  • Preference multiple (1×, 2×, etc.)

STEP 2 — CLAUDE: PREPARE INPUTS (OCF-COMPATIBLE)

Save to ${CLAUDE_PLUGIN_ROOT}/skills/cap-table-waterfall/output/captable_inputs.json:

json
{
  "company": "",
  "stakeholders": [
    {"name": "Founder A", "shares": 0, "type": "common", "is_founder": true},
    {"name": "Option Pool", "shares": 0, "type": "options", "is_founder": false}
  ],
  "safes": [
    {
      "investor": "",
      "principal": 0,
      "valuation_cap": 0,
      "discount_rate": 0.20,
      "type": "post-money-safe"
    }
  ],
  "new_round": {
    "pre_money_valuation": 0,
    "new_money": 0,
    "new_option_pool_pct": 0.10,
    "preference": "non-participating",
    "preference_multiple": 1.0
  },
  "exit_scenarios": [
    {"label": "Low",    "exit_price": 0},
    {"label": "Base",   "exit_price": 0},
    {"label": "High",   "exit_price": 0}
  ]
}

STEP 3 — PYTHON: COMPUTE DILUTION AND SAFE CONVERSION

Run: python "${CLAUDE_PLUGIN_ROOT}/skills/cap-table-waterfall/scripts/captable_calc.py"

Computes:

  1. Pre-round cap table (ownership percentages)
  2. SAFE conversion at the new round price
  3. Post-round cap table with all dilution applied
  4. Ownership percentages for each stakeholder pre and post round

STEP 4 — PYTHON: RUN EXIT WATERFALL

Run: python "${CLAUDE_PLUGIN_ROOT}/skills/cap-table-waterfall/scripts/waterfall_calc.py"

Applies the 4-step waterfall for each exit scenario:

  1. Return of capital: Preferred investors get investment back first
  2. Preference multiple: If 2×, they get 2× before anyone else
  3. Participation: If participating preferred, investors get pro-rata share of remainder
  4. Remainder: Split among common shareholders + converted preferred (non-participating)

STEP 5 — PYTHON: FORMAT FINAL REPORT

Run: python "${CLAUDE_PLUGIN_ROOT}/skills/cap-table-waterfall/scripts/waterfall_formatter.py"


KEY FORMULAS

python
# SAFE Conversion (Post-Money)
cap_price        = valuation_cap / pre_round_shares
round_price      = pre_money_valuation / pre_round_shares
discount_price   = round_price * (1 - discount_rate)
conversion_price = min(cap_price, discount_price)
safe_shares      = principal / conversion_price

# Post-Money Valuation
post_money = pre_money_valuation + new_money

# Ownership % (fully diluted)
ownership_pct = shares / total_fully_diluted_shares * 100

© davepoon, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in plugins/venture-capital-intelligence/skills/cap-table-waterfall of davepoon/buildwithclaude.

  • SKILL.md
  • scripts/captable_calc.py
  • scripts/waterfall_calc.py
  • scripts/waterfall_formatter.py

Open the folder on GitHubat commit 10bfc43

Compare with similar skills

Cap Table Waterfall next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Ib Pitch Booknexu-io/open-design100k—~2kAutomated safety check: PassApache-2.0
Dcf ModelLuciole-Studio/Misaka-Agent1392 repos~12kAutomated safety check: PassApache-2.0

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Works with

Questions about Cap Table Waterfall

What does Cap Table Waterfall do?

Model cap table dilution, SAFE conversion, and exit waterfall across scenarios. Cap Table Waterfall is an agent skill from davepoon/buildwithclaude. Model cap table dilution, SAFE conversion, and exit waterfall across scenarios.

When should I use Cap Table Waterfall?

Cap Table Waterfall fits situations like: tasks that involve Financial modeling; tasks that involve Fundraising and pitch decks.

How do I install Cap Table Waterfall in Claude Code?

Run `npx skills add davepoon/buildwithclaude --skill cap-table-waterfall -a claude-code`. Or copy the skill folder (plugins/venture-capital-intelligence/skills/cap-table-waterfall in davepoon/buildwithclaude) into .claude/skills/cap-table-waterfall in your project. Claude Code loads it when a task matches its description.

How do I install Cap Table Waterfall in Codex?

Run `npx skills add davepoon/buildwithclaude --skill cap-table-waterfall -a codex`. Or copy the skill folder (plugins/venture-capital-intelligence/skills/cap-table-waterfall in davepoon/buildwithclaude) into .agents/skills/cap-table-waterfall in your project. Codex loads it when a task matches its description.

Can I use Cap Table Waterfall in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davepoon/buildwithclaude --skill cap-table-waterfall -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cap-table-waterfall, .gemini/skills/cap-table-waterfall, .github/skills/cap-table-waterfall and .opencode/skills/cap-table-waterfall in your project.

What does Cap Table Waterfall need to run?

Going by SKILL.md and its folder, Cap Table Waterfall needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Cap Table Waterfall access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Cap Table Waterfall safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Cap Table Waterfall use?

Cap Table Waterfall is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cap Table Waterfall use?

About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cap Table Waterfall?

Skills that share tags, products or a category with Cap Table Waterfall: Dcf Model (Wind-Alice/AliceMarket, 130 stars), Investor Materials (cohen-liel/hivemind, 110 stars), Startup Financial Modeling (wshobson/agents, 40k stars) and Ib Pitch Book (nexu-io/open-design, 100k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cap Table Waterfall?

davepoon (a GitHub user) maintains it in davepoon/buildwithclaude, which has 3,604 GitHub stars. The repository holds 245 skills in this directory. The repository was last updated on October 6, 2026.

Source: davepoon/buildwithclaude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.