Startup Analysis
Alex YangCommunityCreated by Alex Yang
- Skill
- Research and analysis
- Business and productivity
- MIT
- No issues found
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
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/himself65/startup-analysis/downloadUnzip 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:
VC Investor Lens — Is this a good investment? Market size, unit economics, growth trajectory, team quality, defensibility
Job Applicant Lens — Should I work here? Equity value, runway risk, culture signals, career growth, compensation fairness
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:
Where perspectives agree — If all three lenses flag the same strength or weakness, it's probably real
Where perspectives diverge — A company can be VC-attractive (huge market) but employee-risky (high burn, low runway). Call these out.
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 flagsreferences/job-applicant-framework.md— Job seeker evaluation framework with equity analysis and culture assessmentreferences/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
- ATTRIBUTION.mdAdded by AutoGineer891 B
- LICENSELicence file added by AutoGineer1.0 KiB
- README.md2.0 KiB
- SKILL.md8.6 KiB
- references/ceo-framework.md7.8 KiB
- references/job-applicant-framework.md7.4 KiB
- references/vc-framework.md6.4 KiB
references/ceo-framework.md
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. |
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
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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)
- Synced
AutoGineer is not affiliated with or endorsed by Alex Yang.
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