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Startup Financial Modeling

Checked
wshobson·vlatest·data·MIT

Generate startup financial models including projections, cap tables, and fundraising scenarios based on provided assumptions.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add wshobson/agents --skill startup-financial-modeling -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

wshobson

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned wshobson/agents at 46891e7e60.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
2 files, 464 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The startup-financial-modeling skill enables AI agents to build and analyze financial models tailored for startups. It supports forecasting revenue, calculating break-even points, projecting cash flow, and evaluating key performance indicators (KPIs) relevant to early-stage businesses.

When to use it

  • Preparing a pitch deck for investors by including detailed financial projections.
  • Estimating the viability of a new business idea based on market size and cost assumptions.
  • Planning budget allocations and fundraising needs for the next fiscal quarter.

Key capabilities

  • Revenue forecasting based on user-defined growth rates and market assumptions.
  • Break-even analysis to determine when a startup becomes profitable.
  • Cash flow projection across multiple time horizons (e.g., 12, 24, or 36 months).
  • Integration with common financial metrics like CAC, LTV, and burn rate.

Example prompts

  • "Build a 3-year financial model for a SaaS startup with $500K in initial funding and 20% monthly growth."
  • "Calculate the break-even point for a new e-commerce business with fixed costs of $10,000/month and variable costs at 40% of revenue."
  • "Project cash flow for a hardware startup over the next 18 months, assuming $2M in Series A funding and 15% monthly sales growth."

Tips & gotchas

  • Ensure input data is realistic and aligned with industry benchmarks to avoid overly optimistic projections.
  • This skill assumes basic financial knowledge; complex modeling may require manual adjustments or additional tools.