plugins/startup-tools/skills/startup-analysis/SKILL.md
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.
npx skillsauth add himself65/finance-skills startup-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Produces a multi-perspective analysis of a startup, examining it through three lenses that each reveal different aspects of company health and potential:
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.
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).
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:
It is better to ask for a URL and produce an accurate analysis than to guess and produce a misleading one.
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 | — |
Read the relevant reference files for the detailed framework for each perspective. These contain the specific criteria, metrics, and red/green flags to evaluate.
Read references/vc-framework.md for the full evaluation framework.
Core areas to assess:
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.
Read references/job-applicant-framework.md for the full evaluation framework.
Core areas to assess:
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.
Read references/ceo-framework.md for the full evaluation framework.
Core areas to assess:
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.
After the three analyses, add a synthesis section that highlights:
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.
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 analysisRead these when you need the detailed criteria and benchmarks for each perspective.
tools
Generic read-only fallback for any source opencli covers but this repo has no dedicated reader for — Yahoo Finance, Bloomberg, Reuters, Barchart, Eastmoney, Xueqiu, Sinafinance, Reddit, HackerNews, Substack, Medium, Weibo, Bilibili, Xiaohongshu, Zhihu, arXiv, Google Scholar, Apple Podcasts, Xiaoyuzhou, Spotify, YouTube, Weixin, Amazon, and more. Triggers: "use opencli to read", "grab the frontpage from hackernews", "read reddit r/wallstreetbets", "fetch Eastmoney hot stocks", "pull Xueqiu feed", "get Bloomberg markets headlines", "search arXiv for", any request to read from a site where a specialized skill does not exist but opencli does. FALLBACK — prefer twitter-reader, linkedin-reader, discord-reader, telegram-reader, or yc-reader when the source matches. READ-ONLY — never invoke write operations.
development
Look up Y Combinator companies, batches, and startup ecosystem data using the yc-oss API (read-only). Use this skill whenever the user wants to research YC-backed startups, find companies in a specific batch or industry, check which YC companies are hiring, explore top YC companies, or analyze startup trends by sector or tag. Triggers include: "YC companies in fintech", "who's in the latest YC batch", "YC startups hiring", "top Y Combinator companies", "find YC companies tagged AI", "W25 batch", "S24 companies", "YC stats", "Y Combinator portfolio", "startup research", "which YC companies do X", "venture research on YC", any mention of Y Combinator, YC batch, or YC-backed companies in the context of startup research, venture analysis, or market intelligence. This is a read-only data source — the API is a static JSON dataset updated daily.
tools
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my bookmarks", "who follows", "look up @user", "what's trending about", "market sentiment on Twitter", "what are people saying about AAPL", "recent tweets from @elonmusk", "show me @user's posts", "fintwit", any mention of Twitter/X in context of reading financial news or market research. This skill is READ-ONLY — it does NOT support posting, liking, retweeting, or any write operations.
tools
Query Funda AI financial data via two surfaces: the MCP server at https://funda.ai/api/mcp for analyst-grade research synthesis (DCF, comps, earnings previews/recaps, sector deep-dives, SEC filings, transcripts, supply-chain mapping, ownership flow, macro framing) via the agent_chat tool — OR the REST API at https://api.funda.ai/v1 with FUNDA_API_KEY for raw data (real-time quotes, intraday candles, EOD prices, financial statements, options chains/greeks/GEX, supply-chain KG, social sentiment, news, calendars, FRED, ESG, congressional trades, AI hiring signals). Triggers: "funda", "funda.ai", real-time quote, stock price, intraday, balance sheet, income statement, options chain, DCF, comps, earnings preview/recap, analyst estimates, 10-K/10-Q/8-K, transcript, ownership flow, gamma exposure, supply chain, sector deep-dive, congressional trades, FRED. Prefer MCP for synthesis/analysis questions; use REST for raw structured data the MCP declines.