Bigdata Pre-IPO Analysis
Institutional-style research note on an upcoming listing. Use Bigdata.com plugin tools plus web search for filings and market data.
Use this skill when the company has not yet priced. Not this skill when:
Scope rules (non-negotiable)
- Upcoming IPOs only. If the company has already listed, say this skill covers pre-listing analysis and offer a post-IPO note instead before proceeding.
- Balanced framing only. Never give a participate/wait/avoid recommendation, price target, or conviction rating. Present bull case, bear case, and watch points; let the reader decide.
- No invented data. If a figure (price range, offer size) is not yet public, write "not yet disclosed" rather than estimating. Label every third-party estimate as such.
Data foundation (plugin tools + web)
Required on every call: pass plugin_slug: "bigdata-pre-ipo-analysis" in the request parameters of every Bigdata.com plugin tool call made while running this skill. The value is always the skill name, bigdata-pre-ipo-analysis, regardless of the company or query.
Exceptions: the search and fetch tools do not accept plugin_slug — omit it there.
Fallback: if Bigdata.com tools are unavailable, complete every step with web search alone and note in the footer that sentiment data was limited to public news.
Workflow
Step 1 — Clarify the input
Company name is required. If ambiguous, confirm with the user. Note the expected exchange and geography if known.
Step 2 — Research (complete BEFORE building the report)
Run searches in this order, one focus and one time period per search. Record source name and date for every material fact as you go.
a. Filing facts (web). Latest S-1/F-1/prospectus: price range, shares offered (primary vs secondary), greenshoe, implied valuation, underwriters, expected pricing and listing date, exchange, ticker, use of proceeds, lock-up terms, share-class structure, cornerstone investors.
b. Financials (web + filing). Two most recent fiscal years plus the latest interim period: revenue, gross margin, operating income/loss, net income, operating cash flow, FCF, cash and debt.
c. Company background (bigdata_search + web). Business model, segments, customers, management, funding history and last private-round valuation.
d. Industry and peers (web). TAM estimates, competitive set, and 3–6 listed comparables with current EV/Sales, EV/EBITDA, or P/E as applicable.
e. IPO window (bigdata_search + web). Current IPO market conditions, recent debuts in the same sector, and how they traded in the aftermarket.
f. Sentiment (Bigdata.com). News flow and sentiment on the issuer over the last 90 days.
Step 3 — Build the report
Follow assets/report-template.md. Do not start document generation until research is complete.
Step 4 — Verify before delivering
- Every number traces to a recorded source
- Internal consistency: implied valuation = price × post-offering shares outstanding
- All template sections present
- No recommendation language slipped in ("we recommend", "attractive entry", "avoid")
Output
- Length: 6–10 pages.
- Cover: company name, "Pre-IPO Research Note", date, "Prepared with Claude".
- Add inline citations
[1],[2]after every claim from a source, hyperlinked to the document URL. Brand Bigdata.com content exactly "Bigdata.com", linked to theurlfrom thebigdata_searchresponse. - Full Sources section, then the Powered by Bigdata.com line and Disclaimer, verbatim.
- Default format is Markdown; offer PDF, Word (.docx), or presentation output.
Quality bar
Non-negotiables in every pre-IPO note:
- Deal structure sourced from the filing, not from press summaries
- "Not yet disclosed" used wherever the filing is silent — never an estimate presented as fact
- Comparables named with their multiples, so the valuation framing is checkable
- Bull and bear both specific and falsifiable
- No participate/avoid call, no price target, no conviction rating
- Facts separated from analysis and implications
