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Startup Analysis

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himself65
startup-analysis

Analyze a startup from three perspectives: VC investor, job applicant, and CEO/founder. Use this skill whenever the user wants to evaluate a startup, assess whether to invest in or join a startup, do due diligence, evaluate a job offer from a startup, understand a startup's competitive position, or assess company health and trajectory. Triggers: "analyze this startup", "should I join [company]", "is [company] a good investment", "evaluate [company]", "due diligence on [company]", "what do you think of [startup]", "should I take this startup job offer", "how healthy is [company]", "startup assessment", "company analysis", "is [company] worth joining", "what's the outlook for [company]", "research [company] for me", any mention of evaluating or assessing a startup or tech company from investment, career, or strategic perspectives — provide all three perspectives by default.

Overview

Publisherhimself65
Repositoryfinance-skills
Skill namestartup-analysis
Stars
3.3K
Forks
378
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by himself65 on GitHub. Read the source before you install it.

Installation

Install the Startup Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/himself65/finance-skills.git /tmp/finance-skills
mkdir -p .claude/skills
cp -r /tmp/finance-skills/plugins/startup-tools/skills/startup-analysis .claude/skills/startup-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Startup Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Startup Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Startup Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Startup Analysis

Produces a multi-perspective analysis of a startup, examining it through three lenses that each reveal different aspects of company health and potential:

  1. VC Investor Lens — Is this a good investment? Market size, unit economics, growth trajectory, team quality, defensibility
  2. Job Applicant Lens — Should I work here? Equity value, runway risk, culture signals, career growth, compensation fairness
  3. CEO/Founder Lens — How healthy is this company? Product-market fit, burn efficiency, competitive moat, organizational health

Each perspective surfaces insights the others miss. A company can be a great investment but a terrible place to work (or vice versa). The goal is to give the user a 360-degree view so they can make informed decisions.


Step 1: Gather Information

Before analyzing, collect as much public information as possible about the startup. Use web search, the company's website, Crunchbase data, press coverage, and any other available sources.

Key data to gather:

CategoryWhat to find
BasicsFounded year, HQ location, employee count, what the product does
FundingTotal raised, last round (size, date, valuation if known), key investors
ProductWhat they sell, who buys it, pricing model, key competitors
TractionUsers, revenue (if public), growth signals, notable customers
TeamFounders' backgrounds, key hires, LinkedIn headcount trends
MarketIndustry, market size estimates, tailwinds/headwinds
NewsRecent press, product launches, partnerships, layoffs, pivots

If certain data isn't publicly available (e.g., revenue for private companies), note the gap and infer what you can from indirect signals (hiring pace, customer logos, web traffic proxies, job postings).

When information is insufficient

Many startups — especially early-stage or niche ones — have limited public presence. If web search does not return enough information to produce a meaningful analysis (e.g., you can't determine what the company does, who founded it, or how it's funded), ask the user to provide the company's website URL before proceeding. The company website is often the single most information-dense source, and reading it directly (about page, pricing page, team page, blog) can fill most gaps.

You can also ask the user for:

  • The company's website or landing page URL
  • A Crunchbase, LinkedIn, or PitchBook link
  • Any pitch deck, job listing, or press article they have
  • Specific context they already know (e.g., "they just raised a Series A from Sequoia")

It is better to ask for a URL and produce an accurate analysis than to guess and produce a misleading one.


Step 2: Determine Which Perspectives to Cover

By default, produce all three perspectives. If the user specifies a particular angle (e.g., "I'm considering joining them" or "should I invest"), emphasize that perspective but still include the others as context — they often reveal relevant information.

User's situationPrimary perspectiveStill include
Considering investingVC InvestorJob Applicant (talent signal), CEO (operational health)
Considering a job offerJob ApplicantVC Investor (funding runway), CEO (strategic direction)
Running the company / advisoryCEO/FounderVC Investor (how investors see you), Job Applicant (talent attractiveness)
General curiosity / researchAll equally

Step 3: Analyze from Each Perspective

Read the relevant reference files for the detailed framework for each perspective. These contain the specific criteria, metrics, and red/green flags to evaluate.

VC Investor Analysis

Read references/vc-framework.md for the full evaluation framework.

Core areas to assess:

  • Market opportunity — TAM/SAM/SOM, market timing, secular trends
  • Product & traction — Product-market fit signals, growth metrics, retention
  • Unit economics — CAC, LTV, margins, burn multiple, path to profitability
  • Team — Founder-market fit, technical depth, hiring ability
  • Defensibility — Moats (network effects, switching costs, data, brand, regulatory)
  • Deal terms context — Stage-appropriate valuation, comparable exits

Produce a clear Investment Thesis (bull case) and Key Risks (bear case). End with a verdict: Strong Pass / Lean Pass / Lean Invest / Strong Invest, with reasoning.

Job Applicant Analysis

Read references/job-applicant-framework.md for the full evaluation framework.

Core areas to assess:

  • Financial stability — Runway, burn rate, funding trajectory, revenue health
  • Equity value — Option/equity package analysis, dilution risk, liquidation preferences, realistic exit scenarios
  • Career growth — Role scope, learning opportunity, resume value, mentorship
  • Culture & work-life — Glassdoor signals, employee tenure data, leadership style
  • Product & market risk — Is PMF real? What happens if the startup fails?
  • Red flags — High turnover, constant pivots, vague metrics, founders cashing out

Produce a clear Why Join (pros) and Watch Out For (risks). End with a verdict: Strong Pass / Lean Pass / Lean Join / Strong Join, with reasoning.

CEO/Founder Analysis

Read references/ceo-framework.md for the full evaluation framework.

Core areas to assess:

  • Product-market fit — Retention curves, organic growth, Sean Ellis test proxy
  • Growth efficiency — Burn multiple, CAC payback, magic number
  • Competitive position — Moat strength, competitive dynamics, market share trajectory
  • Organizational health — Hiring pipeline, attrition, team capability gaps
  • Fundraising readiness — Metrics vs. benchmarks for next round, investor narrative
  • Strategic risks — Platform dependency, customer concentration, regulatory exposure

Produce a clear Strengths to Double Down On and Urgent Areas to Address. End with a health grade: Critical / Struggling / Stable / Strong / Exceptional, with reasoning.


Step 4: Synthesize Cross-Perspective Insights

After the three analyses, add a synthesis section that highlights:

  1. Where perspectives agree — If all three lenses flag the same strength or weakness, it's probably real
  2. Where perspectives diverge — A company can be VC-attractive (huge market) but employee-risky (high burn, low runway). Call these out.
  3. The bottom line — One paragraph summary: what kind of company is this, what's its most likely trajectory, and what should the user do based on their stated (or implied) situation

Step 5: Present the Report

Structure the output as a clean, scannable report:

# [Company Name] — Startup Analysis

## Summary
[2-3 sentence overview with key verdict]

## VC Investor Perspective
### Market Opportunity
### Product & Traction
### Unit Economics (if available)
### Team
### Defensibility
### Investment Verdict: [Strong Pass / Lean Pass / Lean Invest / Strong Invest]
[Reasoning]

## Job Applicant Perspective
### Financial Stability
### Equity Value Assessment
### Career Growth Potential
### Culture & Work-Life Signals
### Risk Factors
### Employment Verdict: [Strong Pass / Lean Pass / Lean Join / Strong Join]
[Reasoning]

## CEO/Founder Perspective
### Product-Market Fit Assessment
### Growth Efficiency
### Competitive Position
### Organizational Health
### Strategic Risks
### Health Grade: [Critical / Struggling / Stable / Strong / Exceptional]
[Reasoning]

## Cross-Perspective Synthesis
### Points of Agreement
### Points of Divergence
### Bottom Line

Adapt section depth to available data — if financials are completely opaque, say so and focus on what's observable. Don't fabricate metrics, but do make informed inferences and state your confidence level.


Reference Files

  • references/vc-framework.md — VC due diligence checklist with metrics, benchmarks, and red/green flags
  • references/job-applicant-framework.md — Job seeker evaluation framework with equity analysis and culture assessment
  • references/ceo-framework.md — CEO self-assessment framework with operational metrics and strategic analysis

Read these when you need the detailed criteria and benchmarks for each perspective.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Startup Analysis AI skill do?

Analyze a startup from three perspectives: VC investor, job applicant, and CEO/founder. Use this skill whenever the user wants to evaluate a startup, assess whether to invest in or join a startup, do due diligence, evaluate a job offer from a startup, understand a startup's competitive position, or assess company health and trajectory. Triggers: "analyze this startup", "should I join [company]", "is [company] a good investment", "evaluate [company]", "due diligence on [company]", "what do you think of [startup]", "should I take this startup job offer", "how healthy is [company]", "startup a...

Why use Startup Analysis on TypingMind?

Because you install it once and use it with any model. Startup Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Startup Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/himself65/finance-skills/tree/main/plugins/startup-tools/skills/startup-analysis. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Startup Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Startup Analysis?

As many as you like. As long as a model supports skills, you can use Startup Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Startup Analysis AI skill free?

Yes. It is published on GitHub by himself65 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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