startup-analysis

# startup-analysis

Multi-perspective startup analysis skill — evaluate any startup from VC investor, job applicant, and CEO/founder viewpoints.

## What it does

Produces a comprehensive startup analysis by examining the company through three distinct lenses:

- **VC Investor** — Market opportunity, unit economics, team quality, defensibility, investment verdict
- **Job Applicant** — Financial stability, equity value, career growth, culture signals, employment verdict
- **CEO/Founder** — Product-market fit, growth efficiency, competitive position, organizational health, health grade

Each perspective surfaces different insights. A company can be a great investment but a terrible place to work (or vice versa). The skill cross-references findings to highlight where perspectives agree and diverge.

**This skill uses web search** to gather public information about the startup before analysis.

## Triggers

- "analyze this startup", "evaluate [company]", "should I join [company]"
- "is [company] a good investment", "due diligence on [company]"
- "what do you think of [startup]", "research [company] for me"
- "startup assessment", "company analysis", "evaluate this company"
- Any mention of evaluating, analyzing, or assessing a startup from investment, career, or strategic perspectives

## Platform

Works on **Claude Code** and other CLI-based agents (web search required). May work on **Claude.ai** with reduced data gathering capability.

## Setup

```bash
# Choose finance-startup-tools when prompted.
npx plugins add himself65/finance-skills

# Or install just this skill
npx skills add himself65/finance-skills --skill startup-analysis
```

See the [main README](../../../../README.md) for more installation options.

## Reference files

- `references/vc-framework.md` — VC due diligence checklist with metrics and benchmarks
- `references/job-applicant-framework.md` — Job seeker evaluation framework with equity analysis
- `references/ceo-framework.md` — CEO self-assessment with operational metrics

# CEO / Founder Self-Assessment Framework

Detailed framework for a startup founder or CEO to assess their company's health, trajectory, and strategic position. This is the "view from inside" — honest self-assessment that surfaces what the founder might be too close to see.

---

## 1. Product-Market Fit Assessment

### Quantitative Signals

| Metric | Strong PMF | Moderate PMF | Weak PMF |
|--------|-----------|-------------|----------|
| Sean Ellis test (% "very disappointed" if product gone) | >40% | 25-40% | <25% |
| Monthly retention (B2B SaaS) | >95% | 90-95% | <90% |
| Monthly retention (consumer) | >30% (D30) | 15-30% | <15% |
| Net revenue retention | >120% | 100-120% | <100% |
| Organic acquisition % | >40% | 20-40% | <20% |
| Time to value | Hours/days | Weeks | Months |

### Qualitative Signals
- Are customers using the product without being asked/reminded?
- Are they pulling you into new use cases you didn't design for?
- Is word-of-mouth driving meaningful growth?
- Do customers complain more about missing features than about the core product?
- Would customers fight to keep the product if you tried to take it away?

### Pivot vs. Persevere

Consider pivoting when:
- 18+ months in with no clear retention or engagement improvement
- Multiple customer segments tried, none sticking
- The team is solving the problem better than anyone but nobody cares about the problem
- The market window has closed or shifted

Persevere when:
- Retention is strong but growth is slow (distribution problem, not product problem)
- A specific segment loves it even if the mass market doesn't
- Usage is increasing within existing accounts
- You're seeing increasing organic pull from a defined customer persona

---

## 2. Growth Efficiency

### Key Operating Metrics

| Metric | Formula | Excellent | Good | Concerning |
|--------|---------|-----------|------|------------|
| Burn multiple | Net burn / net new ARR | <1x | 1-2x | >2x |
| CAC payback | CAC / (monthly ARPU × gross margin) | <6 months | 6-12 months | >18 months |
| Magic number | Net new ARR / S&M spend (prior quarter) | >1.0 | 0.5-1.0 | <0.5 |
| Gross margin | (Revenue - COGS) / Revenue | >75% | 60-75% | <60% |
| Rule of 40 | Growth rate + profit margin | >40% | 20-40% | <20% |

### Runway Management

| Runway | Action |
|--------|--------|
| >24 months | Comfortable. Invest in growth. |
| 18-24 months | Start fundraising prep. |
| 12-18 months | Actively fundraising or cutting burn. |
| 6-12 months | Emergency mode. Cut to default alive. |
| <6 months | Survival mode. Consider bridge, acqui-hire, or wind-down. |

### Burn Efficiency Questions
- Could you get to profitability (or "default alive") by cutting to just the core team?
- What's the minimum viable burn rate to maintain the product and key relationships?
- Is the marginal dollar of spend generating more or less revenue than the last one?

---

## 3. Competitive Position

### Moat Assessment

For each potential moat, rate its current strength (0-5):

| Moat | Questions to ask yourself |
|------|--------------------------|
| Network effects | Does the product get better as more people use it? Is there a multi-sided network? |
| Switching costs | How hard is it for customers to leave? Have they integrated deeply? |
| Data advantage | Do you have proprietary data that improves the product and that competitors can't easily replicate? |
| Brand / community | Do customers identify with your brand? Is there a community that would be hard to replicate? |
| Economies of scale | Do your unit costs decrease meaningfully with scale? |
| Technology / IP | Do you have patents, trade secrets, or technical capabilities that are genuinely hard to replicate? |
| Regulatory | Do you have licenses, certifications, or regulatory relationships that create barriers? |

### Competitive Dynamics

- **Direct competitors:** Who's building the same thing? What's their differentiation?
- **Indirect competitors:** What do customers use instead of your product today (including doing nothing)?
- **Platform risk:** Are you building on top of a platform that could compete with you or cut you off?
- **Big tech risk:** Could a FAANG company build this as a feature? Would they?
- **Open source risk:** Could an open-source alternative emerge that's "good enough"?

---

## 4. Organizational Health

### Team Metrics

| Metric | Healthy | Warning |
|--------|---------|---------|
| Voluntary attrition (annual) | <15% | >20% |
| Offer acceptance rate | >70% | <50% |
| Time to fill key roles | <60 days | >90 days |
| eNPS (employee net promoter score) | >30 | <10 |
| Manager-to-IC ratio | 1:5 to 1:8 | <1:3 or >1:12 |

### Organizational Health Questions
- Do you have the team to execute the next 12-month plan?
- What are the 3 most critical hires you need to make?
- Is there a single-point-of-failure person (if they leave, you're in serious trouble)?
- Are decisions being made at the right level, or is everything bottlenecked at founders?
- Is the team aligned on what success looks like this quarter?

### Culture Assessment
- Do people disagree openly in meetings, or is conflict avoided?
- Is information flowing freely, or are there silos?
- Do people voluntarily recommend working here to friends?
- Are people excited about the product and mission, or just collecting a paycheck?

---

## 5. Fundraising Readiness

### Benchmarks by Stage

| Round | Typical ARR | Growth rate | Other expectations |
|-------|------------|-------------|-------------------|
| Seed | Pre-revenue or <$500K | Strong user/engagement growth | Compelling team + market thesis |
| Series A | $1-3M ARR | >3x YoY | Clear PMF, repeatable sales motion |
| Series B | $5-15M ARR | >2.5x YoY | Unit economics working, scalable GTM |
| Series C | $20-50M ARR | >2x YoY | Path to profitability visible, market leadership |

### Fundraising Readiness Checklist
- [ ] Metrics trending in the right direction (not just a good month)
- [ ] Clear narrative: problem → solution → traction → market → team → ask
- [ ] Data room prepared: financials, cap table, key metrics dashboard, customer references
- [ ] Target investor list with warm intros identified
- [ ] Board alignment on timing and terms expectations
- [ ] 6+ months of runway remaining when starting the process

### Investor Narrative
- What's the big vision that makes this a $1B+ company?
- What's the specific milestone this funding will help you hit?
- Why is now the right time to raise?
- What's your unfair advantage that makes you the team to win this market?

---

## 6. Strategic Risk Register

### Risk Categories

| Risk type | Examples | Mitigation |
|-----------|---------|------------|
| Customer concentration | >30% revenue from one customer | Diversify aggressively |
| Platform dependency | Built on another company's API/platform | Build abstraction layers, diversify platforms |
| Key person risk | Single engineer owns critical system | Cross-train, document, hire redundancy |
| Regulatory | New laws could ban or restrict the product | Engage lobbyists, build compliance early |
| Market timing | Ahead of or behind the market | Adjust GTM, consider pivoting market segment |
| Technology shift | New technology makes your approach obsolete | R&D investment, stay close to cutting edge |
| Funding | Can't raise next round | Get to default alive, explore bridge/debt |

### Health Grade Framework

| Grade | Criteria |
|-------|---------|
| **Exceptional** | Strong PMF, efficient growth, clear moat, great team, well-funded. Rare. |
| **Strong** | Good PMF, growing well, defensible position, minor gaps. Well-positioned for next round. |
| **Stable** | PMF found but growth could be better, some efficiency concerns, adequate runway. Needs focus. |
| **Struggling** | Unclear PMF or declining metrics, burn concerns, competitive pressure. Needs significant changes. |
| **Critical** | No PMF, <6 months runway, team attrition, no clear path forward. Pivot, bridge, or wind down. |

# 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

| Signal | Green | Yellow | Red |
|--------|-------|--------|-----|
| Last funding round | <12 months ago, healthy amount | 12-18 months ago | >18 months ago with no revenue growth |
| Runway | 18+ months | 12-18 months | <12 months |
| Investor quality | Top-tier VCs (a16z, Sequoia, etc.) | Mid-tier or strategic investors | Unknown angels, no institutional backing |
| Revenue trend | Growing >50% YoY | Growing but slowing | Flat or declining |
| Burn trajectory | Decreasing burn multiple | Stable | Increasing 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

| Term | What it means for you |
|------|----------------------|
| Stock options (ISO/NSO) | Right to buy shares at a set price (strike price). Worthless if company value < strike + preferences |
| RSUs | Actual shares granted. More valuable than options but rare at early-stage startups |
| Strike price / 409A | The "buy" price for options. Lower = more potential upside |
| Vesting schedule | Typically 4 years with 1-year cliff. You own nothing until the cliff |
| Preference stack | Investors get paid first in an exit. If they have 2x preferences and the company sells for 2x invested capital, common shareholders (you) get $0 |
| Dilution | Your % shrinks with each funding round. Expect 15-25% dilution per round |
| Exercise window | How 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

| Factor | How to think about it |
|--------|----------------------|
| Cash below market | Expect 10-30% below big-tech base salary; more than that is a red flag |
| Equity as gap-filler | Equity should more than compensate for the cash gap in an expected-value sense |
| Total comp comparison | Compare total expected comp (cash + equity expected value) against FAANG/big-tech offers |
| Startup risk premium | You should expect meaningfully higher total comp potential to justify the risk, illiquidity, and extra work |

---

## 3. Career Growth Assessment

### Signals of Good Growth Potential

| Signal | What to look for |
|--------|-----------------|
| Role scope | Will you own significant areas, or be a cog? Early employees get outsized scope |
| Learning velocity | Are you working with people better than you in key areas? |
| Resume value | Is this company/brand recognizable? Will it open doors? |
| Title trajectory | Startups often offer faster title progression, but titles mean less |
| Mentorship | Is there someone senior in your function? Or are you building from scratch? |
| Network | Will 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

| Signal | How to check |
|--------|-------------|
| Product quality | Try the product yourself. Is it good? Would you use it? |
| Customer sentiment | Check G2, Capterra, Product Hunt, Twitter/X, Reddit |
| Competitor landscape | Who else does this? Is the market crowded or greenfield? |
| Platform dependency | Does the product depend on a platform that could cut them off or compete? |
| Technical risk | Is 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:

| Area | Weight |
|------|--------|
| Financial stability | 25% |
| Equity upside potential | 20% |
| Career growth | 25% |
| Culture & work-life | 15% |
| Product & market risk | 15% |

### Verdict Scale

| Verdict | Meaning |
|---------|---------|
| **Strong Join** | Compelling across most dimensions — take this job |
| **Lean Join** | Good opportunity with manageable risks, worth considering |
| **Lean Pass** | Meaningful concerns; only join if you have a specific reason (learning, network, passion for the problem) |
| **Strong Pass** | Significant financial risk, poor equity setup, or cultural red flags — look elsewhere |

# VC Investor Due Diligence Framework

Detailed evaluation criteria for assessing a startup as a potential venture investment. Organized by stage — earlier stages weight team and market heavier, later stages weight metrics and unit economics heavier.

---

## 1. Market Opportunity

### TAM / SAM / SOM

| Term | Definition | What good looks like |
|------|-----------|---------------------|
| TAM | Total addressable market | $1B+ for venture-scale returns |
| SAM | Serviceable addressable market | $100M+ realistic near-term |
| SOM | Serviceable obtainable market | Credible path to $10M+ ARR |

**How to estimate:** Use top-down (industry reports, public comp revenue) AND bottom-up (# of potential customers × average deal size). If these converge, the estimate is more credible.

### Market Timing

- **Why now?** — What changed (technology, regulation, behavior, cost curve) that makes this possible today but not 5 years ago?
- **Secular tailwinds** — Is the market growing regardless of this company? (e.g., cloud migration, AI adoption, remote work)
- **Headwinds** — Regulatory risk, platform dependency, cyclical exposure

### Green Flags
- Market growing >20% annually
- Clear "why now" with structural shifts
- Multiple adjacent markets to expand into
- Winner-take-most dynamics

### Red Flags
- Market is shrinking or saturated
- "If only X% of a huge market" reasoning (lazy TAM)
- Heavy regulatory uncertainty with no clear path
- Market exists only because of a temporary condition

---

## 2. Product & Traction

### Product-Market Fit Signals

| Signal | Strong PMF | Weak PMF |
|--------|-----------|----------|
| Organic growth | >40% of new users from word-of-mouth | Almost all paid acquisition |
| Retention (D30) | >40% for consumer, >80% for B2B SaaS | Rapid dropoff after onboarding |
| NPS | >50 | <20 |
| Usage frequency | Daily/weekly active use | Monthly or declining |
| Customer pull | Customers asking for features, integrating deeply | Need heavy sales/success effort to retain |

### Growth Metrics by Stage

| Stage | Key metric | Good benchmark |
|-------|-----------|----------------|
| Pre-seed / Seed | User growth rate | >15% MoM |
| Series A | Revenue growth | >3x YoY, $1-3M ARR |
| Series B | Revenue growth + efficiency | >2.5x YoY, $5-15M ARR, improving unit economics |
| Series C+ | Path to profitability | >$20M ARR, positive unit economics, clear path to FCF |

### Engagement Depth
- How much of the product do users actually use?
- What's the "aha moment" and how quickly do users reach it?
- Is usage expanding within accounts (land-and-expand)?

---

## 3. Unit Economics

### Key Metrics

| Metric | Formula | Good benchmark |
|--------|---------|----------------|
| CAC | Total S&M spend / new customers | Payback <12 months (SaaS), <6 months (consumer) |
| LTV | ARPU × gross margin × (1/churn rate) | LTV:CAC > 3:1 |
| Gross margin | (Revenue - COGS) / Revenue | >60% for SaaS, >40% for marketplace |
| Burn multiple | Net burn / net new ARR | <2x (efficient), <1.5x (excellent) |
| Net dollar retention | Expansion + retained revenue / prior period revenue | >110% for B2B SaaS, >100% for SMB |
| Rule of 40 | Revenue growth % + profit margin % | >40% |

### Burn & Runway

- **Monthly burn rate** — How fast are they spending?
- **Runway** — Months of cash left at current burn
- **Burn trajectory** — Is burn accelerating or decelerating?
- **Good benchmark:** 18-24 months runway post-raise; <12 months is danger zone

---

## 4. Team Assessment

### Founder Evaluation

| Criteria | What to assess |
|----------|---------------|
| Founder-market fit | Do they have unfair insight into this problem? Domain expertise, lived experience, or unique technical capability |
| Technical depth | Can the team build the product without outsourcing core IP? |
| Execution speed | Velocity of shipping — how much have they built with how little? |
| Resilience | Have they navigated adversity before? How do they handle setbacks? |
| Storytelling | Can they recruit, fundraise, and sell with conviction? |
| Coachability | Do they take feedback? Do they learn fast? |

### Team Composition

- **CTO / technical co-founder** — Essential for technical products; red flag if all business people
- **Full-stack founding team** — Ideally covers product, engineering, and distribution
- **Early hires** — Quality of first 10-20 hires signals judgment and network
- **Advisor/board quality** — Who's helping them? Domain experts or just check-writers?

### Red Flags
- Solo non-technical founder building a technical product
- Founder team that hasn't worked together before (for first-time founders)
- High executive turnover early on
- Founders with pattern of starting and quickly abandoning companies

---

## 5. Defensibility & Moats

| Moat type | Description | Strength | Example |
|-----------|-------------|----------|---------|
| Network effects | Product gets better with more users | Very strong | Marketplace, social network |
| Switching costs | Painful to leave once adopted | Strong | Enterprise SaaS with deep integrations |
| Data moat | Proprietary data that improves the product | Strong | Training data, usage data, customer data |
| Brand / community | Trust and loyalty that's hard to replicate | Moderate | Developer tools with strong community |
| Economies of scale | Cost advantages from size | Moderate | Infrastructure, logistics |
| Regulatory / IP | Patents, licenses, regulatory approval | Variable | Biotech, fintech, defense |
| Speed / execution | Simply moving faster than competition | Weak (temporary) | Only valuable if converting to durable moat |

### Competitive Dynamics
- Who are the direct competitors? Indirect competitors?
- What happens if a FAANG/big tech company enters this space?
- Is there a platform risk (building on top of someone else's platform)?

---

## 6. Investment Verdict Framework

### Scoring

Rate each area 1-5:

| Area | Weight (Seed) | Weight (Series A+) |
|------|--------------|-------------------|
| Market | 30% | 20% |
| Team | 30% | 20% |
| Product/Traction | 20% | 30% |
| Unit Economics | 10% | 20% |
| Defensibility | 10% | 10% |

### Verdict Scale

| Verdict | Meaning |
|---------|---------|
| **Strong Invest** | Exceptional across most dimensions, clear path to venture-scale returns |
| **Lean Invest** | Good opportunity with manageable risks, worth deeper diligence |
| **Lean Pass** | Interesting but significant concerns in 1-2 critical areas |
| **Strong Pass** | Fundamental issues in market, team, or business model |

---
name: startup-analysis
description: >
  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.
---

# 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:**

| Category | What to find |
|----------|-------------|
| **Basics** | Founded year, HQ location, employee count, what the product does |
| **Funding** | Total raised, last round (size, date, valuation if known), key investors |
| **Product** | What they sell, who buys it, pricing model, key competitors |
| **Traction** | Users, revenue (if public), growth signals, notable customers |
| **Team** | Founders' backgrounds, key hires, LinkedIn headcount trends |
| **Market** | Industry, market size estimates, tailwinds/headwinds |
| **News** | Recent 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 situation | Primary perspective | Still include |
|-----------------|-------------------|---------------|
| Considering investing | VC Investor | Job Applicant (talent signal), CEO (operational health) |
| Considering a job offer | Job Applicant | VC Investor (funding runway), CEO (strategic direction) |
| Running the company / advisory | CEO/Founder | VC Investor (how investors see you), Job Applicant (talent attractiveness) |
| General curiosity / research | All 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.