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Startup Analysis

Alex YangCommunityCreated by Alex Yang

  • Skill
  • Research and analysis
  • Business and productivity
  • MIT
  • No issues found

From the author

Analyze a startup from three perspectives — VC investor, job applicant, and CEO/founder — covering market, traction, unit economics, team, defensibility, runway, equity value, culture, and competitive position, with a verdict for each. Use this skill whenever the user wants to evaluate a startup or private tech company: due diligence, whether to invest in it or join it, weighing a startup job offer, company health, outlook, or competitive position, or open-ended asks such as "what do you think of [company]" or "research [company] for me".
— the description by Alex Yang

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Startup Analysis provides a structured, multi-lens evaluation of private tech companies. By synthesizing data from public sources, it generates a report that examines a company's health and potential through three distinct viewpoints: the VC investor (focusing on market and economics), the job applicant (focusing on career risk and equity), and the CEO (focusing on operational efficiency and strategy). This approach ensures users understand not just the company's viability, but how it aligns with their specific goals, whether they are looking to invest, join, or lead.

What it does

  • Gathers and synthesizes public data on startups including funding, traction, and team.
  • Evaluates companies from a VC investor perspective to assess market opportunity and defensibility.
  • Analyzes companies from a job applicant perspective to assess equity value and career risk.
  • Assesses companies from a CEO perspective to identify operational strengths and strategic gaps.
  • Provides a cross-perspective synthesis to highlight where different lenses agree or diverge.
  • Delivers a structured report with clear verdicts for each perspective.

When to use it

  • When performing due diligence on a potential investment target.
  • When weighing a job offer from a startup to understand the risks and potential upside.
  • When a founder needs an objective, third-party style assessment of their own company's health.
  • When conducting general research on a private tech company's competitive position.

Advantages

  • Provides a balanced view by separating investor, employee, and founder interests.
  • Helps identify hidden risks like high burn rates or poor equity structures.
  • Standardizes the evaluation process using clear metrics and frameworks.
  • Encourages critical thinking by forcing the user to consider multiple stakeholder viewpoints.

Usage examples

“What do you think of Acme Corp as a place to work?”
The agent will research Acme Corp and provide a report focusing on the job applicant lens, including equity risks, culture, and runway, while providing context from the investor and CEO perspectives.
“Research the startup 'Nebula AI' for me.”
The agent will conduct a comprehensive 360-degree analysis of Nebula AI, covering market, traction, team, and providing verdicts for investment, employment, and operational health.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/himself65/startup-analysis/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip startup-analysis.zip -d .agents/skills

Documentation by Alex Yang

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

Write it as a scannable report titled [Company Name] — Startup Analysis:

  • Summary — a short overview that states the three verdicts up front.

  • One section per perspective, in the order that fits the user's situation from Step 2. Each covers the core areas from Step 3 with the evidence behind every judgment, and ends with its verdict on the scale defined there — Investment Verdict (Strong Pass / Lean Pass / Lean Invest / Strong Invest), Employment Verdict (Strong Pass / Lean Pass / Lean Join / Strong Join), or Health Grade (Critical / Struggling / Stable / Strong / Exceptional) — followed by the reasoning.

  • Cross-perspective synthesis — where the lenses agree, where they diverge, and the bottom line.

Scale each section to the evidence: where financials or other areas are opaque, say so in a line and spend the space on what's observable, rather than filling a heading for its own sake. Don't fabricate metrics; 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.

Files

references/job-applicant-framework.md

Job Applicant Startup Evaluation Framework

Detailed framework for evaluating whether to join a startup as an employee. The core question: is the risk/reward tradeoff worth it compared to a safer, better-paying job at an established company?


1. Financial Stability Assessment

Runway & Funding
SignalGreenYellowRed
Last funding round<12 months ago, healthy amount12-18 months ago>18 months ago with no revenue growth
Runway18+ months12-18 months<12 months
Investor qualityTop-tier VCs (a16z, Sequoia, etc.)Mid-tier or strategic investorsUnknown angels, no institutional backing
Revenue trendGrowing >50% YoYGrowing but slowingFlat or declining
Burn trajectoryDecreasing burn multipleStableIncreasing burn, no revenue growth
How to research
  • Crunchbase / PitchBook — Funding history, investors, valuation

  • LinkedIn headcount — Is the team growing, flat, or shrinking?

  • Job postings — Lots of openings = growth; few = maintenance mode; mass closings = trouble

  • News — Recent layoffs, pivots, leadership changes

  • Glassdoor — Employee reviews, especially recent ones mentioning "runway" or "funding"

Questions to Ask in Interviews
  • "What's your current runway?" (they should answer openly; evasion is a red flag)

  • "When do you plan to raise next, and how's that process going?"

  • "What's your revenue trajectory looking like?"

  • "Has there been any restructuring or layoffs in the past year?"


2. Equity & Compensation Analysis

Understanding Your Equity
TermWhat it means for you
Stock options (ISO/NSO)Right to buy shares at a set price (strike price). Worthless if company value < strike + preferences
RSUsActual shares granted. More valuable than options but rare at early-stage startups
Strike price / 409AThe "buy" price for options. Lower = more potential upside
Vesting scheduleTypically 4 years with 1-year cliff. You own nothing until the cliff
Preference stackInvestors get paid first in an exit. If they have 2x preferences and the company sells for 2x invested capital, common shareholders (you) get $0
DilutionYour % shrinks with each funding round. Expect 15-25% dilution per round
Exercise windowHow long after leaving you can buy vested options. 90 days is standard but brutal — you may have to pay $50K+ to exercise
Equity Valuation Reality Check

To estimate what your equity might actually be worth:

  1. Start with the last 409A valuation (ask for it)

  2. Estimate realistic exit scenarios — Most startups don't exit at unicorn valuations. Model: acquisition at 2-5x last round, IPO at 5-10x, and failure (0)

  3. Apply the preference stack — Subtract total investor preferences before calculating common share value

  4. Apply dilution — Assume 2-3 more rounds of 20% dilution each

  5. Probability-weight — ~70-80% of VC-backed startups fail. Even "good" ones often exit below the preference stack

Compensation Benchmarking
FactorHow to think about it
Cash below marketExpect 10-30% below big-tech base salary; more than that is a red flag
Equity as gap-fillerEquity should more than compensate for the cash gap in an expected-value sense
Total comp comparisonCompare total expected comp (cash + equity expected value) against FAANG/big-tech offers
Startup risk premiumYou should expect meaningfully higher total comp potential to justify the risk, illiquidity, and extra work

3. Career Growth Assessment

Signals of Good Growth Potential
SignalWhat to look for
Role scopeWill you own significant areas, or be a cog? Early employees get outsized scope
Learning velocityAre you working with people better than you in key areas?
Resume valueIs this company/brand recognizable? Will it open doors?
Title trajectoryStartups often offer faster title progression, but titles mean less
MentorshipIs there someone senior in your function? Or are you building from scratch?
NetworkWill you meet investors, operators, and experts you wouldn't otherwise?
When Startup Experience Is Most Valuable
  • Early in career (first 5-7 years): maximum learning, acceptable risk

  • When switching functions: startups let you wear many hats

  • When building founder skills: closest thing to founding without the risk

  • When the startup's domain aligns with your long-term career direction

When It's Less Valuable
  • Deep specialization needed: big companies have more depth

  • Financial obligations (mortgage, family): startup risk may not be appropriate

  • Late career with established reputation: incremental resume value is lower


4. Culture & Work-Life Signals

Positive Signals
  • Founders are transparent about challenges, not just hype

  • Employee tenure is reasonable (2+ years for early employees)

  • Clear values that show up in decision-making, not just a poster

  • Engineers/ICs have voice in product direction

  • Reasonable on-call and work hours expectations

Red Flags
  • Glassdoor reviews consistently mention burnout, toxicity, or chaos

  • "We're a family" language combined with 60+ hour expectations

  • High turnover in leadership positions

  • Founders talk about "crushing it" but can't articulate product strategy

  • No clear onboarding process or role definition

  • "We work hard and play hard" as a substitute for compensation

Questions to Ask
  • "What does a typical week look like for someone in this role?"

  • "Tell me about someone who was recently promoted — what did they do?"

  • "What's the biggest challenge the team is facing right now?"

  • "How does the company handle disagreements between founders/leadership?"

  • "What's the on-call rotation like?" (for engineering)


5. Product & Market Risk

Assessing from the Outside
SignalHow to check
Product qualityTry the product yourself. Is it good? Would you use it?
Customer sentimentCheck G2, Capterra, Product Hunt, Twitter/X, Reddit
Competitor landscapeWho else does this? Is the market crowded or greenfield?
Platform dependencyDoes the product depend on a platform that could cut them off or compete?
Technical riskIs the product technically hard (moat) or could it be replicated quickly?
What Happens If It Fails?

Think about your personal downside:

  • How long would it take to find a new job in your function/market?

  • Have you burned cash on exercising options that are now worthless?

  • Have you maintained your skills and network for a smooth transition?

  • Is the experience itself valuable on your resume regardless of outcome?


6. Verdict Framework

Scoring

Rate each area 1-5:

AreaWeight
Financial stability25%
Equity upside potential20%
Career growth25%
Culture & work-life15%
Product & market risk15%
Verdict Scale
VerdictMeaning
Strong JoinCompelling across most dimensions — take this job
Lean JoinGood opportunity with manageable risks, worth considering
Lean PassMeaningful concerns; only join if you have a specific reason (learning, network, passion for the problem)
Strong PassSignificant financial risk, poor equity setup, or cultural red flags — look elsewhere

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

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Attribution and licence

Created by
Alex Yang
Publisher
Alex Yang (Community)
Source
himself65/finance-skills · plugins/startup-tools/skills/startup-analysis · commit a085078
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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