Generate professional company tear sheets complete with live financials, ownership details, and market data sourced directly from S&P Global. You receive a polished Word document ready for client meetings, eliminating manual data entry for equity research, M&A targeting, or sales preparation. Use this whenever you need a concise company snapshot to support investment decisions or client pitches.
name: tear-sheet
description: “Generate professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or ticker. Also trigger when users ask for equity research summaries, M&A company profiles, corporate development target profiles, sales/BD meeting prep documents, or any concise single-company financial summary. This skill supports four audience types: equity research, investment banking/M&A, corporate development, and sales/business development. If the user doesn’t specify an audience, ask. Works for both public and private companies.”
Financial Tear Sheet Generator
Generate audience-specific company tear sheets by pulling live data from S&P Capital IQ via the S&P Global MCP tools and formatting the result as a professional Word document.
Style Configuration
These are sensible defaults. To customize for your firm’s brand, modify this section — common changes include swapping the color palette, changing the font (Calibri is standard at many banks), and updating the disclaimer text.
Section headers: 11pt bold (size: 22), Primary color
Body text: 9pt (size: 18)
Table text: 8.5pt (size: 17)
Footer/disclaimer: 7pt italic (size: 14)
Per-template overrides are specified in each reference file’s Formatting Notes.
Company Header Banner:
The header is a navy (#1F3864) banner spanning the full page width with company name in white.
Below the banner, key-value pairs MUST be rendered in a two-column borderless table spanning the full page width. Left column: company identifiers (ticker, HQ, founded, employees, sector). Right column: financial identifiers (market cap, EV, stock price, shares outstanding). Each cell contains a bold label and regular-weight value on the same line (e.g., “Market Cap $124.7B”). Do not left-justify all fields in a single column — this wastes horizontal space and looks unprofessional. The two-column spread is the single most important visual signal that distinguishes a professional tear sheet from a default document.
Implementation: Create a 2-column table with borders: none and shading: none on all cells. Set column widths to 50% each. Place left-column fields (ticker, HQ, founded, employees) as separate paragraphs in the left cell. Place right-column fields (market cap, EV, stock price, shares outstanding) in the right cell. Each field is a single paragraph: bold run for the label, regular run for the value.
The specific fields in each column vary by audience — see the reference file’s header spec. The principle is always: spread across the page, not clumped left.
Do not use a bordered table for the header key-value block. Bordered tables are reserved for financial data only.
Key metrics in the header (market cap, EV, stock price) should be displayed as inline key-value pairs, not in a separate bordered table.
Section Headers:
Each section header gets a horizontal rule (thin line, #CCCCCC, 0.5pt) directly beneath it to create clean visual separation between sections.
Render the rule as a bottom border on the header paragraph itself — do not insert a separate paragraph element for the rule. A separate paragraph adds its own before/after spacing and causes excessive whitespace below section titles.
Implementation: In docx-js, apply a bottom border to the section header paragraph via paragraph.borders.bottom = { style: BorderStyle.SINGLE, size: 1, color: "CCCCCC" }. Do not use doc.addParagraph() with a separate horizontal rule element. Do not use thematicBreak. The border must be on the heading paragraph itself with 0pt spacing after, so the rule sits tight against the header text.
Spacing: 12pt before the header paragraph, 0pt after the header paragraph, 4pt before the next content element.
Bullet Formatting:
Use a single bullet character (•) for all bulleted content across all tear sheet types. Do not mix •, -, ▸, or numbered lists within or across tear sheets.
Synthesis/analysis bullets (Earnings Highlights, Strategic Fit, Integration Considerations, Conversation Starters): indented block-style formatting with left indent 360 DXA (0.25”) and a hanging indent for the bullet character. These should be visually offset from body text — they’re interpretive content and should look distinct from data tables and prose paragraphs.
Informational bullets within relationship sections: standard body indent (180 DXA), no hanging indent.
Do not apply left-border accents to any bullet sections. Left-border styling renders inconsistently in docx-js and creates visual artifacts. Use indentation and text size differentiation to distinguish signature sections instead.
Tables (financial data only):
Header row: Table Header Fill (#D6E4F0) with bold dark text
Body rows: alternating white / Table Alternating Fill (#F2F2F2)
Borders: Table Border color (#CCCCCC), thin (BorderStyle.SINGLE, size 1)
Always use ShadingType.CLEAR (never SOLID — SOLID causes black backgrounds)
Layout:
US Letter portrait, 0.75” margins (1080 DXA all sides)
Number formatting:
Currency: USD. Use millions unless company revenue > $50B (then billions, one decimal). Label units in column headers (e.g., “Revenue ($M)”), not in individual cells.
Table cells: plain numbers with commas, no dollar signs. Example: a revenue cell shows “4,916” not “$4,916”. The column header carries the unit.
Fiscal years: actual years (FY2022, FY2023, FY2024), never relative labels (FY-2, FY-1).
Negatives: parentheses, e.g., (2.3%)
Percentages: one decimal place
Large numbers: commas as thousands separators
Footer (document footer, not inline):
Place the source attribution and disclaimer in the actual document footer (repeated on every page), not as inline body text at the bottom. The footer is exactly two lines, centered, on every page:
Line 1: “Data: S&P Capital IQ via Kensho | Analysis: AI-generated | [Month Day, Year]”
Line 2: “For informational purposes only. Not investment advice.”
Style: 7pt italic, centered, #666666 text color
This footer text must be identical across all tear sheet types for the same company. Do not vary the wording by audience.
This footer is required on every tear sheet, every audience type, every page. Do not omit it.
Component Functions
You MUST use these exact functions to create document elements. Do NOT write custom docx-js styling code. Copy these functions into your generated Node script and call them. The Style Configuration prose above remains as documentation; these functions are the enforcement mechanism.
Copy all functions and constants above into the generated Node.js script
Call createHeaderBanner(...) instead of manually building banner paragraphs and tables
Call createSectionHeader(...) for every section title — never manually set paragraph borders
Call createTable(...) for all tabular data — financial summaries, trading comps, M&A activity, relationship tables, funding history, etc. Pass { accentHeader: true } for M&A activity tables (IB/M&A template). For non-numeric tables (e.g., relationships, ownership), the function still works correctly — it only right-aligns cells that contain numeric values.
Call createBulletList(items, "synthesis") for earnings highlights, strategic fit, integration considerations, and conversation starters
Call createBulletList(items, "informational") for relationship entries
Pass createFooter(date) to the Document constructor’s footers.default property
What these functions eliminate:
Black background tables (enforces ShadingType.CLEAR everywhere)
Separate horizontal rule paragraphs under section headers (enforces border.bottom on the paragraph itself)
Bordered key-value tables in headers (enforces borders: none)
Inconsistent bullet styles (enforces • character only)
Missing footers (provides the exact footer structure)
Workflow
Step 1: Identify Inputs
Gather up to four things before proceeding:
Company — name or ticker. If only a ticker, resolve the full company name with an initial query (e.g., use the company info tool).
Audience — one of four types:
Equity Research — for buy-side/sell-side analysts evaluating an investment
IB / M&A — for bankers profiling a company in transaction context
Corp Dev — for internal strategic teams evaluating an acquisition target
Sales / BD — for commercial teams preparing for a client meeting
Comparable companies (optional) — if the user has specific comps in mind, note them. Otherwise the skill will identify peers from S&P Global data. This matters for Equity Research, IB/M&A, and Corp Dev tear sheets.
Page length preference (optional) — defaults vary by audience (see below), but the user can override.
If the user doesn’t specify an audience, ask.
Step 2: Read the Audience-Specific Reference
Read the corresponding reference file from this skill’s directory:
Equity Research → references/equity-research.md
IB / M&A → references/ib-ma.md
Corp Dev → references/corp-dev.md
Sales / BD → references/sales-bd.md
Each reference defines sections, a query plan, formatting guidance, and page length defaults.
Step 3: Pull Data via S&P Global MCP
First: Create the intermediate file directory:
mkdir -p /tmp/tear-sheet/
Use the S&P Global MCP tools (also known as the Kensho LLM-ready API). Claude will have access to structured tools for financial data, company information, market data, consensus estimates, earnings transcripts, M&A transactions, and business relationships. The query plans in each reference file describe what data to retrieve for each section — map these to the appropriate S&P Global tools available in the conversation.
After each query step, immediately write the retrieved data to the intermediate file(s) specified in the reference file’s query plan. Do not defer writes — data written to disk is protected from context degradation in long conversations.
Query strategy:
Each reference file includes a query plan with 4-6 data retrieval steps. These are starting points, not rigid constraints. Prioritize data completeness over minimizing calls:
Always pull 4 fiscal years of financial data, even though only 3 years are displayed. The fourth (earliest) year is needed to compute YoY revenue growth for the first displayed year. Without it, the earliest year’s growth rate will show “N/A” — which looks like missing data, not a design choice.
Execute the query plan as written, using whichever S&P Global tools match the data needed.
If a tool call returns incomplete results, try alternative tools or narrower queries. For example, if company summary doesn’t include segment detail, try the segments tool directly.
If a data point isn’t returned after a targeted retry, move on — label it “N/A” or “Not disclosed.”
Never fabricate data. If the tools don’t return a number, do not estimate from training knowledge.
User-specified comps: If the user provided comparable companies, query financials and multiples for each comp explicitly. If no comps were provided, use whatever peer data the tools return, or identify peers from the company’s sector using the competitors tool.
Optional context from the user: Listen for additional context the user provides naturally. If they mention who the acquirer is (“we’re looking at this for our platform”), what they sell (“we sell data analytics to banks”), or who the likely buyers are (“this would be interesting to Salesforce or Microsoft”), incorporate that context into the relevant synthesis sections (Strategic Fit, Conversation Starters, Deal Angle). Don’t prompt for this information — just use it if offered.
Private company handling:
CIQ includes private company data, so query the same way. However, expect sparser results. When generating for a private company:
Lean into: business overview, relationships, ownership structure, whatever financials are available
Note “Private Company” prominently in the header
Step 3b: Calculate Derived Metrics
After all data collection is complete and intermediate files are written, compute all derived metrics in a single dedicated pass. This is a calculation-only step — no new MCP queries.
Read all intermediate files back into context, then compute:
Efficiency ratios: FCF Conversion (FCF/EBITDA), R&D as % of Revenue, Capex as % of Revenue
Capital structure: Net Debt (Total Debt − Cash & Equivalents), Net Debt / EBITDA
Segment mix: Each segment’s revenue as % of consolidated total revenue (use consolidated revenue as denominator per Data Integrity Rule 8)
Validation (moved from Arithmetic Validation): During this calculation pass, enforce all arithmetic checks:
Margin calculations: Verify EBITDA Margin = EBITDA / Revenue, Gross Margin = Gross Profit / Revenue, etc. If the computed margin doesn’t match the raw numbers, use the computation from raw components.
Growth rates: Verify YoY growth = (Current − Prior) / Prior. Don’t rely on pre-computed growth rates if you have the underlying values.
Segment totals: If showing revenue by segment, verify segments sum to total revenue (within rounding tolerance). If they don’t, omit the total row rather than publishing inconsistent math.
Percentage columns: Verify ”% of Total” columns sum to ~100%.
Valuation cross-checks: If you show both EV and EV/Revenue, verify EV / Revenue ≈ the stated multiple.
If a validation fails: attempt recalculation from raw data. If still inconsistent, flag the metric as “N/A” rather than publishing incorrect numbers. Quiet math errors in a tear sheet destroy credibility.
Write results to /tmp/tear-sheet/calculations.csv with columns: metric,value,formula,components
Soft gate: If any file expected for the current audience type is missing or empty, print a warning but continue. The tear sheet handles missing data gracefully with “N/A” and section skipping. However, the warning ensures visibility into what data was lost.
Critical rule: The files — not your memory of earlier conversation — are the single source of truth for every number in the document. When generating the DOCX in Step 4, read values from the intermediate files. Do not rely on conversation context for financial data.
Step 4: Format as DOCX
Read /mnt/skills/public/docx/SKILL.md for docx creation mechanics (docx-js via Node). Apply the Style Configuration above plus the section-specific formatting in the reference file.
Page length defaults (user can override):
Equity Research: 1 page (density is the convention)
IB / M&A: 1-2 pages
Corp Dev: 1-2 pages
Sales / BD: 1-2 pages
If content exceeds the target, each reference file specifies which sections to cut first.
Save to /mnt/user-data/outputs/ and present to the user.
Data Integrity Rules
These override everything else:
S&P Global tools are the only source for financial data. Do not fill gaps with training knowledge — it may be stale or wrong.
Label what you can’t find. Use “N/A” or “Not disclosed” rather than omitting a row silently.
Dates matter. Note the fiscal year end or reporting period. Don’t assume calendar year = fiscal year. Market data (stock prices, market cap) should include an “as of” date.
Don’t mix reporting periods. If you have FY2023 revenue and LTM EBITDA, label them distinctly.
Prefer MCP-returned fields over manual computation. If the S&P Global tools return a pre-computed field (e.g., net debt, EBITDA, FCF), use that value directly rather than computing it from components. Only compute derived metrics manually when the tools do not return the field. This reduces discrepancies.
Ensure consistency across tear sheet types. If generating multiple tear sheets for the same company (e.g., equity research and IB/M&A in the same session), the same underlying data points must produce identical values across all outputs. Net debt, revenue, EBITDA, margins, and growth rates must match exactly. Do not re-query or re-compute independently per report — reuse the same retrieved values.
Never downgrade known transaction values. If the M&A tools return a deal value for a transaction, that value must appear in the output. Do not replace a known deal value with “Undisclosed.” Use “Undisclosed” only when the tools genuinely return no value for a transaction.
Use consolidated revenue as the denominator for segment percentages. When computing ”% of Total” for segment tables, divide each segment’s revenue by consolidated total revenue (as reported on the income statement), not by the sum of segment revenues. The sum of segments often exceeds consolidated revenue due to intersegment eliminations. Using consolidated revenue ensures percentages align with the total revenue figure shown elsewhere in the document.
Always include forward (NTM) multiples when available. If the tools return both trailing and forward valuation multiples, both must appear in the output. Forward multiples are the primary valuation reference for equity research, IB/M&A, and corp dev audiences. Never show only trailing multiples when forward data is available.
No S&P Global tool returns executive or management data. Do not populate management names, titles, or biographical details from training data — this violates Rule 1 and produces stale information. If a management section appears in a template, omit it entirely. Ownership structure (institutional holders, insider %, PE sponsor) may be included only if returned by the tools — gate with “data permitting.”
Intermediate File Rule
All data retrieved from MCP tools must be persisted to structured intermediate files before document generation. These files — not conversation context — are the single source of truth for every number in the document.
Setup: At the start of Step 3, create the working directory:
mkdir -p /tmp/tear-sheet/
Write-after-query mandate: After each MCP query step completes, immediately write the retrieved data to the appropriate intermediate file(s). Do not wait until all queries finish. Each reference file’s query plan specifies which file(s) to write after each step.
Customers, suppliers, partners, competitors — each with descriptors
IB, CD, Sales
/tmp/tear-sheet/peer-comps.csv
CSV
ticker,metric,value,source
ER, IB, CD
/tmp/tear-sheet/ma-activity.csv
CSV
date,target,deal_value,type,rationale,source
IB, CD
/tmp/tear-sheet/calculations.csv
CSV
metric,value,formula,components
All (written in Step 3b)
Abbreviations: ER = Equity Research, IB = IB/M&A, CD = Corp Dev, Sales = Sales/BD.
Not every audience type uses every file — the reference files define which query steps apply. Files not relevant to the current audience type need not be created.
Raw values only. Intermediate files store raw values as returned by the tools. Do not pre-compute margins, growth rates, or other derived metrics in these files — that happens in Step 3b.
Page budget enforcement: Each reference file specifies a default page length and a numbered cut order. If the rendered document exceeds the target, apply cuts in the order specified — do not attempt to shrink font sizes or margins below the template minimums. The cut order is a strict priority stack: cut section 1 completely before touching section 2.
Content Quality Rules
Rewrite every narrative section for the audience. The CIQ company summary is an input, not an output. Each audience type needs a different description: concise and thesis-oriented for equity research, pitchbook prose for IB, product-focused for Corp Dev, plain language for Sales/BD. Never paste the CIQ summary verbatim into any tear sheet.
Differentiate earnings highlights by audience. The same earnings call produces different takeaways for different readers. Equity research wants segment-level performance and consensus beat/miss. IB wants margin trajectory and strategic commentary. Sales/BD wants strategic themes that create conversation angles. Do not reuse the same bullets across tear sheet types.
Synthesis sections are the differentiator. Strategic Fit Analysis, Integration Considerations, Conversation Starters, and Business Overview paragraphs are where the tear sheet earns its value. These sections require analytical reasoning that connects data points into a narrative — listing company names without context is not synthesis.
Flag pending divestitures in segment tables. If a company has announced a pending divestiture of a segment or business unit, add a footnote or parenthetical to the segment table noting the pending transaction (e.g., “Mobility* — *Pending divestiture, expected mid-2026”). For Corp Dev and IB/M&A tear sheets, include a one-line note below the segment table showing pro-forma revenue and revenue mix excluding the divested segment. This helps the reader evaluate the “go-forward” business without doing the math themselves.
Arithmetic Validation
→ Arithmetic validation is now enforced in Step 3b (Calculate Derived Metrics). All margin calculations, growth rates, segment totals, percentage columns, and valuation cross-checks are validated during the dedicated calculation pass, before document generation begins. See Step 3b for the full validation checklist.
Corporate Development Tear Sheet
Purpose
A target evaluation profile for an internal Corp Dev team assessing a potential acquisition. Unlike the IB/M&A profile (which tells a strategic story for a pitch), this is an analytical document focused on strategic fit: how the target's products, customers, technology, and operations overlap with or complement the acquirer's. The Corp Dev audience already knows their own company — they need to understand the target through the lens of "should we buy this, and what would integration look like?"
Default page length: 1-2 pages. Corp Dev teams are comfortable with denser profiles and won't penalize a second page if the content is substantive.
Query Plan
Start with these queries. Break apart and follow up if results are incomplete.
Query 1 — Target profile:
"[Company] business description products services technology platform headquarters founded employees sector industry"
→ Header, Business & Product Overview
→ Immediately write to /tmp/tear-sheet/company-profile.txt
Query 2 — Financials:
"[Company] annual income statement revenue gross profit EBITDA operating income net income capex free cash flow R&D expense total debt cash and equivalents last 4 fiscal years"
→ Financial Summary (pull 4 years; display 3; use the earliest year only for YoY growth computation. R&D is especially important for Corp Dev — they want to understand the target's investment in IP)
→ Immediately write raw values to /tmp/tear-sheet/financials.csv
Query 3 — Segments + customers:
"[Company] revenue by segment business unit last 2 fiscal years key customers end markets customer concentration"
→ Revenue Mix (need 2 years for YoY growth), Customer Analysis
→ Immediately write segment data to /tmp/tear-sheet/segments.csv (skip if no segment data returned)
Query 4 — Relationships + competitive landscape:
"[Company] key customers suppliers partners competitors business relationships technology vendors"
→ Strategic Fit Analysis, Ecosystem Map
→ Immediately write to /tmp/tear-sheet/relationships.txt
Query 5 — Valuation + peers:
If user provided specific comps:
"[Comp company] enterprise value EV/Revenue EV/EBITDA revenue growth EBITDA margin"
Otherwise:
Use the competitors tool to identify 3-5 public peers, then pull EV/Revenue (NTM), EV/EBITDA (NTM), revenue growth %, and EBITDA margin % for each.
Also: "[Company] enterprise value market capitalization valuation multiples"
→ Valuation Context
→ Immediately write company multiples to /tmp/tear-sheet/valuation.csv
→ Immediately write peer data to /tmp/tear-sheet/peer-comps.csv
Query 6 — Ownership (data permitting):
"[Company] ownership structure investors institutional ownership insider ownership"
→ Ownership snapshot (no intermediate file — included in company-profile.txt if available)
Sections
Listed in priority order. See "Page Budget & Cut Order" below for explicit cut guidance.
1. Company Header
Similar to IB/M&A but adds a "Strategic Relevance" tagline.
Field
Notes
Company name
Large, bold
Ticker & Exchange
If public; omit for private
HQ Location
Founded / Employees
Enterprise Value
Market cap for public; latest valuation for private
Ownership
Public / PE-backed / Founder-led / etc.
Strategic Relevance
One sentence: why this target is attractive to an acquirer (synthesized from data)
The "Strategic Relevance" line is unique to Corp Dev. Write from a neutral analytical perspective, not from the target's marketing language. Frame what an acquirer gets — not what the target is. Good: "Dominant position in commodity price benchmarks with regulatory moat and 70%+ gross margins — a capital-light, high-barrier data asset." Bad: "The world's leading provider of financial data and analytics." The former tells a corp dev team why this is attractive; the latter is a press release.
2. Business & Product Overview
Do not paste the CIQ company summary. Rewrite in 4-6 sentences (one paragraph, not two) with a product and technology focus — this audience evaluates acquisitions, not investments:
Core products/services and what problem they solve
Technology or platform architecture (at a high level)
Key differentiators and competitive moat
Customer segments — who buys this and why
Current strategic direction
Write with an acquirer's lens. The reader is thinking: "How would this fit with what we already have?" The description should make it easy to spot overlaps and complements.
3. Revenue Mix & Customer Profile
Two sub-sections:
a) Revenue by Segment (if available):
Segment
Revenue ($M)
% of Total
YoY Growth
b) Customer Analysis:
Below the segment table (or in place of it if segments aren't available), write a qualitative paragraph covering:
Customer concentration: are the top 5 customers >30% of revenue? (Critical for acquisition risk)
Customer type: enterprise vs. SMB vs. consumer
Contract structure: subscription vs. transactional vs. license (if known)
Geographic mix
Customer concentration is the single most important signal here — if the tools return any data on top customers or revenue concentration, highlight it prominently. If data is sparse, write what you can infer from the business description and relationships. Keep this to 2-3 sentences — it's context for the segment table, not a standalone analysis.
4. Strategic Fit Analysis
This is the signature section of the Corp Dev tear sheet. It is required — do not skip or compress it. It uses the Business Relationships data from S&P Capital IQ to map overlaps and complements.
Organize as three buckets. Each bucket must be 2-3 sentences of analytical reasoning, not a list of company names. Listing "Customers: Microsoft, JPMorgan, Google" without context is useless. Instead, explain what the overlap or complement means for an acquisition.
Customer Overlap: Do the target's customers also buy from the acquirer (or the acquirer's industry)? Shared customers = easier cross-sell, but also risk of channel conflict. Name shared relationships and explain the implications.
Technology / Product Complement: Does the target fill a gap in the acquirer's portfolio? What does their tech stack look like? Who are their technology vendors? If they're already using the acquirer's technology, explain why that's a strong integration signal.
Competitive Displacement: Is the target a competitor, or does acquiring them remove a competitor from the market? Name the target's key competitors and explain how the competitive landscape would change post-acquisition.
This section requires synthesis — combine relationship data with the business overview to draw connections. If the user has told you who the acquirer is, tailor to that acquirer. If not, write it generically but still analytically.
Length discipline: The 2-3 sentence target per bucket above is a hard constraint, not a suggestion. Each bullet should front-load the insight, then support with one specific data point. The actual outputs frequently balloon to 5-7 sentences per bullet — this is the primary driver of page 3 spillover. If you find yourself writing more than 3 sentences, move the excess detail to Integration Considerations.
5. Financial Summary (3-Year)
Similar to IB/M&A but with added emphasis on R&D and capital efficiency.
Metric ($M)
FY20XX
FY20XX
FY20XX
Revenue
Revenue Growth %
Gross Margin %
EBITDA
EBITDA Margin %
R&D Expense
R&D as % of Revenue
Capex
Free Cash Flow
FCF Conversion (FCF/EBITDA)
R&D intensity signals how much of the target's value is in IP vs. services. FCF conversion signals integration complexity — high-capex businesses are harder to integrate. If R&D expense isn't separately reported, note "Not separately disclosed" in the row rather than "N/A" — this itself is informative (suggests R&D may be embedded in COGS or SG&A).
Capital Structure (compact sub-table below the financial summary):
Metric
Value
Total Debt
$XXM
Cash & Equivalents
$XXM
Net Debt
$XXM
Net Debt / EBITDA
X.Xx
Frame for acquisition context: below the table, include one sentence interpreting leverage (e.g., "Net debt of $X represents Y.Yx EBITDA leverage, which is manageable for an investment-grade acquirer but would compound leverage in an LBO scenario."). Pull from the balance sheet data already retrieved.
6. Valuation Context
This section is required for public companies. Corp Dev teams need market context to frame a potential bid. If the tools return valuation multiples, this section must appear. Do not cut it for space — cut Ownership Snapshot (Section 7) first.
Not a formal valuation — Corp Dev teams do their own DCFs. This provides market context.
a) Trading multiples (if public):
Peer context is essential, not optional. If the user provided comps, show each in its own column. If no comps were provided, use the competitors tool to identify 3-5 public peers, then pull EV/Revenue (NTM), EV/EBITDA (NTM), revenue growth %, and EBITDA margin % for each.
Metric
[Company]
[Peer 1]
[Peer 2]
[Peer 3]
Peer Median
EV/Revenue (NTM)
EV/EBITDA (NTM)
Revenue Growth %
EBITDA Margin %
A company's multiples in isolation tell a corp dev team nothing — they need relative context to assess whether the target is cheap or rich vs. the peer set. This is the minimum viable valuation context for a target profile.
If peer multiples are unavailable from the tools, show the company's own multiples and list selected peer names below the table for the reader's reference.
b) Precedent transactions (data permitting):
If the M&A tools return recent transactions involving the company's peers or within the same sub-sector, display them:
Date
Target
Acquirer
EV ($M)
EV/Rev
EV/EBITDA
Frame as context: "Recent transactions in [sub-sector] have valued targets at X–Yx revenue."
If precedent transaction data is not available from the tools, note "Precedent transaction data not available from data source" rather than omitting silently. Do not fabricate precedent multiples.
For private companies, skip trading multiples. Precedent transactions (data permitting) are still useful.
If the tools return ownership data, include a compact block: founder/family control %, PE sponsor details, institutional concentration. Ownership structure directly impacts deal complexity and is relevant for integration considerations.
Do not include a Management Team table. No S&P Global tool returns executive data — see Data Integrity Rule 10. Management names from training data will be stale.
8. Integration Considerations
Required section — do not cut. This is the analytical capstone of the Corp Dev tear sheet. Synthesized observations drawn from everything above. 3-4 substantive bullets:
Open questions: What would a corp dev team need to diligence before making a bid? Focus on concrete, actionable diligence items — not open-ended strategic questions. Good examples: regulatory approval timeline and jurisdictions, change-of-control provisions in key contracts, key-person retention risk (especially founders/CTOs), customer contract transferability, IP ownership structure, outstanding litigation. Bad examples: "How defensible is X?" or "What is the long-term market opportunity?" — these are analyst questions, not diligence items.
Label clearly as analytical observations, not facts from the data source.
Page Budget & Cut Order
Target: 2 pages. Corp Dev profiles can fill both pages with substantive content, but must not spill to a third unless the user explicitly requests a longer format. If content exceeds 2 pages, cut in this order (cut each completely before moving to the next):
Ownership Snapshot (section 7) — omit entirely
Customer Analysis prose under Revenue Mix (section 3) — reduce to 2 sentences max
Precedent Transactions (section 6b) — keep the "not available" note, remove if space-critical
Capital Structure prose — keep table, cut interpretive paragraph below it
Strategic Fit Analysis (section 4) — compress each bullet to 2-3 sentences max (do not remove the section)
Never cut: Business & Product Overview (2), Financial Summary (5 core table), Integration Considerations (8).
Formatting Notes
Strategic Fit Analysis is the centerpiece. Give it distinctive formatting:
Bump text to 9.5pt (size: 19) — slightly larger than standard body text. This section should look like the most important content on the page.
Use the standard indented block-style bullets from the global style config (360 DXA left indent).
Do not apply left-border accents — they render inconsistently in docx-js.
Financial Summary should include R&D and FCF conversion prominently.
Valuation Context with peer comps is required for public companies — do not cut before Ownership Snapshot.
For private targets, the profile leans heavily on qualitative sections (Business Overview, Strategic Fit, Relationships) — this is expected and still highly valuable.
Tone: analytical and evaluative, not promotional. This isn't a pitch — it's an assessment.
Two-page discipline: Before rendering, mentally estimate page count. The combination of Strategic Fit (3 long bullets) + Integration Considerations (4 bullets) alone can consume a full page — if so, compress Strategic Fit bullets first.
Equity Research Tear Sheet
Purpose
A dense snapshot for buy-side or sell-side analysts evaluating an investment. Emphasis on valuation, forward estimates, financial trajectory, and analyst consensus. Everything supports or challenges an investment thesis.
Default page length: 1 page. Equity research tear sheets are conventionally single-page — density is the point. If the user requests more space, extend to 2 pages.
Query Plan
Start with these queries. If results are incomplete, break into narrower follow-ups.
Query 1 — Profile + market data:
"[Company] company overview sector industry market capitalization enterprise value stock price 52-week high low shares outstanding beta"
→ Header, Business Description
→ Immediately write to /tmp/tear-sheet/company-profile.txt
Query 2 — Historical financials:
"[Company] annual income statement revenue gross profit EBITDA net income EPS free cash flow total debt cash and equivalents last 4 fiscal years"
→ Financial Summary (pull 4 years; display 3; use the earliest year only for YoY growth computation)
→ Immediately write raw values to /tmp/tear-sheet/financials.csv
Query 2b — Segments (if available):
"[Company] revenue by segment business unit last 2 fiscal years"
→ Revenue & Segment Breakdown (need 2 years for YoY growth). If segment data is unavailable, skip this section — do not leave a blank table.
→ Immediately write to /tmp/tear-sheet/segments.csv (skip if no segment data returned)
Query 4 — Earnings:
"[Company] most recent earnings call key takeaways guidance"
→ Earnings Highlights
→ Immediately write to /tmp/tear-sheet/earnings.txt
Query 5 — Stock performance:
"[Company] stock price return 1 month 3 month 6 month 1 year YTD performance"
→ Stock Performance (no intermediate file — data goes directly into document)
Query 6 (if user provided comps):
"[Comp company] market cap EV/Revenue EV/EBITDA revenue growth" — repeat for each comp
→ Peer context for Valuation Snapshot
→ Immediately write to /tmp/tear-sheet/peer-comps.csv
Sections
Listed in priority order. If constrained to one page, cut from the bottom.
1. Company Header
Compact key-value block rendered as a two-column borderless table per the global style config.
Left column: Ticker (exchange), sector / industry, HQ
Right column: Stock price, 52-week range, market cap, EV, shares outstanding, beta
2. Business Description
2-3 tight sentences. Rewrite in your own words for an analyst audience — do not paste the CIQ company summary verbatim. The CIQ summary is an input; the output should be concise and thesis-oriented.
For well-known, widely covered companies, assume the analyst already knows the basic business. Lead with what's changing — strategic pivots, portfolio reshaping, new growth vectors — not a Wikipedia-style overview. For example, for a Fortune 500 company, don't spend a sentence on "provides financial data to institutions." Instead: "Reshaping its portfolio toward higher-margin data and analytics businesses, with a pending Mobility spin-off and aggressive AI investment through its Kensho subsidiary."
For lesser-known companies, a brief "what they do" sentence is appropriate before pivoting to the thesis-relevant dynamics.
3. Valuation Snapshot
Centerpiece of the equity tear sheet.
Metric
Trailing
Forward (NTM)
P/E
EV/EBITDA
EV/Revenue
P/FCF
Dividend Yield
Forward multiples are mandatory when available from the tools. Showing only trailing multiples when forward data exists is a significant gap — analysts value companies on forward earnings. If forward multiples aren't available, show trailing only and note "Fwd estimates N/A."
If the user provided comparable companies, add columns for each comp (or a "Peer Median" column if 3+ comps). If no user comps, and the tools return peer data, include a Peer Median column. If neither, show the company's multiples only.
4. Consensus Estimates
What the Street expects — a key differentiator for this tear sheet type.
Data availability note: The depth of consensus data varies by company and coverage. Include whatever the tools return — analyst count, price target, Buy/Hold/Sell distribution — but do not fabricate or estimate any consensus figure. For thinly covered companies, this section may contain only revenue and EPS estimates, which is still valuable.
Metric
FY[year] Est.
FY[year+1] Est.
Revenue
EPS (normalized)
EBITDA
Use normalized/adjusted EPS where available — GAAP EPS can be distorted by one-time items and is less useful for forward estimates.
Below the main estimates table, include a compact analyst consensus block (if data is available from the tools):
Analyst Consensus
Mean Price Target
$XXX
# of Estimates
XX
Buy / Hold / Sell
XX / XX / XX
If price target or recommendation data is unavailable, omit the analyst consensus block rather than showing empty rows. Do not fabricate these figures.
If consensus data isn't available at all, skip this entire section and note "Consensus estimates not available." Do not estimate.
5. Financial Summary (3-Year)
Dense single table using actual fiscal year labels.
Metric ($M)
FY20XX
FY20XX
FY20XX
Revenue
Revenue Growth %
Gross Margin %
EBITDA
EBITDA Margin %
Net Income
EPS (Diluted)
Free Cash Flow
Net Debt
Compute derived metrics (growth %, margins) from raw data rather than querying separately.
Capital Structure (separate compact sub-table below the Financial Summary):
Do NOT append these rows to the 3-year Financial Summary table — blank cells in prior-year columns look like missing data. Instead, render as a separate 2-column sub-table (Metric | Value) directly below, showing only the most recent fiscal year:
Metric
FY[latest]
Total Debt
$XXM
Cash & Equivalents
$XXM
Net Debt
$XXM
This matches the capital structure format used in Corp Dev and IB/M&A tear sheets. Keep it tight — no extra spacing between the Financial Summary and this sub-table.
6. Revenue & Segment Breakdown
If segment data is available from the tools, include a compact segment revenue table. This is essential context for equity research — analysts need to see which business lines are driving growth.
Segment
Revenue ($M)
% of Total
YoY Growth
[Segment A]
[Segment B]
Keep this compact for the one-pager: table only, no qualitative paragraph. If segment data is unavailable, skip this section entirely — do not include a blank or placeholder table.
7. Recent Earnings Highlights
Include the quarter and date (e.g., "Q3 FY2025 — October 2025"). 3-4 bullets with an investment lens — this audience wants segment-level specifics, not strategic themes:
Lead with guidance if provided. If management issued forward guidance, make it the first bullet with a bold Guidance: prefix (e.g., "Guidance: FY2026 EPS of $19.40–$19.65, implying 9–10% growth; organic revenue growth of 6–8%."). Guidance is the single most actionable forward-looking data point for an analyst — do not bury it among operating highlights.
Beat/miss context (data permitting): If consensus estimate data is available for the reported period, frame the headline result bullet as a beat/miss: "Revenue of $X beat/missed consensus of $Y by Z%." If consensus data for the reported period is not available from the tools, describe results in absolute terms and growth rates only — do not fabricate consensus figures.
Then:
Segment-level performance: which business lines accelerated or decelerated
Margin trajectory: any commentary on cost structure or profitability trends
Attribute to management: "Management highlighted…" or "CFO noted…" rather than declarative claims. This section should feel like an earnings recap, not a press release summary.
8. Key Operating Metrics
2-3 sector-relevant KPIs if available from the data (subscriber count, same-store sales, NIM, etc.). If nothing sector-specific, compute ROE and ROIC from the financials already retrieved. Optional — drop if space is tight.
9. Stock Performance (cut first)
Period return table. Low analytical value for this audience — cut this before anything else.
Period
Return
1 Month
3 Month
YTD
1 Year
Formatting Notes
This is the densest tear sheet type. It should feel noticeably more compressed than the other templates.
Financial Summary table: 8pt text (size: 16), row height 240 DXA. Tightest spacing of any template.
Valuation Snapshot and Consensus Estimates: 8.5pt text, occupy the visual center — analysts scan these first.
Body text: 8.5pt (size: 17) — smaller than the global 9pt default. Every half-point matters on a one-pager.
Section spacing: minimize. 6pt before section headers (not the global 12pt), 2pt after rules.
Bold any metric showing a notable inflection (growth turning positive, margin expansion/compression).
Prioritize information over whitespace at every turn.
Investment Banking / M&A Tear Sheet
Purpose
A company profile for transaction context — potential target, acquirer, or pitchbook inclusion. Emphasis on strategic positioning, segment detail, business relationships, and M&A activity. Valuation framed in transaction multiples, not investment thesis.
Default page length: 1-2 pages. IB company profiles routinely spill to a second page, especially when segment and M&A data is rich.
Query Plan
Start with these queries. Break apart and follow up if results are incomplete.
Query 1 — Profile + identification:
"[Company] business description headquarters founded employees sector industry ownership structure major shareholders"
→ Header, Business Overview
→ Immediately write to /tmp/tear-sheet/company-profile.txt
Query 2 — Segments + financials:
"[Company] revenue by segment business unit last 2 fiscal years AND annual income statement revenue gross profit EBITDA operating income net income capex free cash flow total debt cash and equivalents last 4 fiscal years"
→ Segment Breakdown (need 2 years to compute YoY growth), Financial Summary (pull 4 years; display 3; use the earliest year only for YoY growth computation)
→ Immediately write raw financials to /tmp/tear-sheet/financials.csv
→ Immediately write segment data to /tmp/tear-sheet/segments.csv (skip if no segment data returned)
Query 3 — Valuation + comps:
If the user provided specific comparable companies, query each:
"[Comp company] enterprise value EV/Revenue EV/EBITDA revenue growth EBITDA margin"
Otherwise:
Use the competitors tool to identify 3-5 public peers, then pull EV/Revenue (NTM), EV/EBITDA (NTM), revenue growth %, and EBITDA margin % for each.
Also: "[Company] enterprise value market capitalization EV/Revenue EV/EBITDA valuation multiples"
→ Header (EV/market cap), Trading Comps
→ Immediately write company multiples to /tmp/tear-sheet/valuation.csv
→ Immediately write peer data to /tmp/tear-sheet/peer-comps.csv
Query 4 — M&A activity:
"[Company] acquisitions divestitures completed transactions last 5 years deal value"
→ Company's own deals
→ Immediately write to /tmp/tear-sheet/ma-activity.csv
Query 5 — Comparable transactions (data permitting):
Use the specific industry from Query 1 results (e.g., "cloud observability software M&A transactions" not "technology M&A"). If the user specified comps, also try: "[comp company] acquisition deal multiples."
→ Comparable Transactions
→ Append comparable transactions to /tmp/tear-sheet/ma-activity.csv (add type=precedent to distinguish from company's own deals)
Query 6 — Relationships + ownership:
"[Company] key customers suppliers partners business relationships institutional ownership insider ownership"
→ Business Relationships, Ownership (data permitting)
→ Immediately write to /tmp/tear-sheet/relationships.txt
Sections
Listed in priority order. See "Page Budget & Cut Order" below for explicit cut guidance.
1. Company Header
Key-value block with transaction-relevant identifiers.
Field
Notes
Company name
Large, bold
Ticker & Exchange
If public; omit for private
HQ Location
City, State/Country
Founded
Year
Employees
Approximate headcount
Market Cap / Valuation
Market cap if public; latest known valuation if private
Enterprise Value
Ownership
Public / PE-backed (name sponsor) / Family / Other
For private companies: note "Private Company" prominently; skip ticker, exchange.
2. Business Overview
This is a pitchbook paragraph, not a CIQ summary. Do not paste the company description from the data tools. Rewrite in 4-6 sentences using pitchbook prose:
Characterize the revenue model (recurring vs. transactional, subscription vs. license)
Name the customer base at scale ("serves 80% of Fortune 500 banks")
Identify competitive moats by name ("proprietary dataset of X", "only provider with Y")
Frame growth vectors that would matter to a buyer or seller
The tone should be confident and specific. A banker reading this paragraph should immediately understand the company's strategic positioning.
3. Revenue & Segment Breakdown
Revenue by business unit or product line.
Segment
Revenue ($M)
% of Total
YoY Growth
[Segment A]
[Segment B]
Total
100%
If segment data isn't available: Replace the table with 2-3 sentences describing the revenue mix qualitatively (e.g., "Revenue is primarily derived from subscription licenses (~70%) and professional services (~30%)."). A blank table looks broken — a qualitative description still conveys useful information.
4. Financial Summary (3-Year + LTM)
Actual fiscal years as column headers. If LTM (last twelve months) data is available, add an LTM column to the right of the most recent fiscal year. Label it "LTM [quarter end date]" (e.g., "LTM Q3 2025"). Bankers work off LTM for valuation cross-checks — a fiscal-year-only view can be 6+ months stale.
Metric ($M)
FY20XX
FY20XX
FY20XX
LTM [date]
Revenue
Revenue Growth %
Gross Profit
Gross Margin %
EBITDA
EBITDA Margin %
Operating Income
Net Income
Capex
Free Cash Flow
FCF Margin %
In M&A context, margins and FCF conversion matter as much as absolute scale — a buyer is evaluating efficiency and cash generation potential.
Capital Structure (compact sub-table below the financial summary):
Metric
Value
Total Debt
$XXM
Cash & Equivalents
$XXM
Net Debt
$XXM
Net Debt / EBITDA
X.Xx
S&P Credit Rating
XX (if available)
Pull from the balance sheet data already retrieved. This is standard in any banker's company profile — total debt, leverage ratio, and credit rating tell a buyer what the financing picture looks like. If credit rating is unavailable, omit that row.
5. Trading Comps
Company multiples and operating metrics — bankers use these together, not multiples in isolation.
Forward multiples are mandatory when available. The table must include NTM multiples if the tools return them. Showing only trailing multiples when forward data exists is a significant gap — bankers price deals on forward earnings.
Peer columns are expected. If the user provided comps, each gets its own column. If not, use the competitors tool to identify 3-5 public peers, pull their multiples and operating metrics, and include them. A company-only trading comps table without peer context is incomplete for any banking use case.
Metric
[Company]
[Comp 1]
[Comp 2]
[Comp 3]
Peer Median
EV/Revenue (NTM)
EV/EBITDA (NTM)
Revenue Growth %
EBITDA Margin %
If only the company's own multiples are available after attempting peer queries, show those and list selected peer names below the table.
For private companies, skip this section.
6. M&A Activity
Two parts. Deal values are expected in this section — bankers notice when they're missing.
Hard rule: If the M&A tools return a transaction value, it must appear in the output. Never downgrade a known deal value to "Undisclosed" — this is a data integrity violation. Use "Undisclosed" only when the tools genuinely return no value for a transaction.
a) Company's Own Transactions:
The table must include a dedicated Deal Value column. Do not merge deal values into a Notes or Rationale column — bankers scan for numbers, and a dedicated column enables that.
Date
Target / Divested
Deal Value ($M)
Type
Rationale
Acquisition / Divestiture
If none found: "No disclosed transactions in the last 5 years."
b) Comparable Sector Transactions (data permitting):
Use the specific industry identified earlier (e.g., "cloud infrastructure software M&A" not "technology M&A"). If the user specified comps, also look for transactions involving those specific companies.
Date
Target
Acquirer
EV ($M)
EV/Rev
EV/EBITDA
If not available from the tools: "Comparable transaction data not available from data source." Do not fabricate precedent multiples.
7. Key Business Relationships
Leverages S&P Capital IQ relationship data. Group by type:
Customers: Top 3-5 named clients
Suppliers: Key vendors and technology providers
Partners: Strategic alliances, distribution, JVs
Competitors: Key competitive names
For each entry, include the relationship type and a parenthetical descriptor explaining the nature of the relationship (e.g., "AWS — cloud infrastructure (primary hosting provider)", "JPMorgan — customer (enterprise analytics platform)"). A name alone without context isn't useful. Give this section breathing room — it's strategically valuable and most competing tear sheets lack it.
If the tools return institutional ownership, insider ownership percentage, or top holders, include a compact block:
Top institutional holders (if available): list top 3-5 by ownership %.
Insider ownership: aggregate percentage.
For PE-backed companies, name the sponsor, acquisition year, and ownership stake. Ownership structure directly affects deal complexity — a widely held public company, a founder-controlled company, and a PE-backed company each require fundamentally different deal approaches.
If ownership data is not returned by the tools, omit this section entirely rather than showing placeholders.
Do not include a Management Team table. No S&P Global tool returns executive data — see Data Integrity Rule 10. Management names from training data will be stale.
Page Budget & Cut Order
Target: 2 pages maximum. IB profiles can use both pages fully, but must not spill to a third. If content exceeds 2 pages, cut in this order (cut each completely before moving to the next):
Business Relationships (section 7) — compress to top 3 competitors + top 2 each of suppliers/partners/customers, drop descriptors to parenthetical only
Capital Structure (section 4) — merge Net Debt/EBITDA into Financial Summary as a single row
Trading Comparables (section 5) — reduce to 3 peers
Never cut: Business Overview (2), Revenue & Segment Breakdown (3), Financial Summary (4 core), M&A Activity company transactions (6a).
Formatting Notes
Business Overview and Segment Breakdown get the most visual weight.
M&A Activity is the signature section: Use Accent color (#2E75B6) fill with white bold text for M&A table headers — this is the only table that uses a different header color from the standard #D6E4F0. It should catch the eye on a scan.
Business Relationships: give breathing room when space permits. 6pt between each relationship group, full descriptors on each entry. But if hitting page 3, compress per the cut order above — this section is high-value but also the most compressible.
For private companies, the header, business overview, financials, and relationships form the core; other sections may be sparse.
Two-page discipline: Before rendering, mentally estimate page count. If Business Relationships + M&A Activity together will exceed one full page, start cutting per the cut order.
Sales / Business Development Tear Sheet
Purpose
A briefing document to prepare a sales or BD team for a client meeting. Emphasis on understanding the prospect's business, what leadership is publicly prioritizing, and identifying angles to connect your product/service to their needs. Financials are simplified to scale and trajectory.
This is the most narrative-driven tear sheet type. It reads like a briefing memo, not a data sheet.
Default page length: 1-2 pages. No strict convention — prioritize readability over compression.
Query Plan
Start with these queries. Follow up if results are incomplete.
Query 1 — Company profile + financials:
"[Company] business description overview products services headquarters employees sector industry revenue gross margin last 2 fiscal years"
→ Header, Company Overview, Financial Snapshot
→ Immediately write to /tmp/tear-sheet/company-profile.txt
→ Immediately write raw financials to /tmp/tear-sheet/financials.csv
Query 2 — Strategy + earnings:
"[Company] most recent earnings call strategic priorities CEO commentary guidance key initiatives"
→ Strategic Priorities
→ Immediately write to /tmp/tear-sheet/earnings.txt
Three queries is usually sufficient. For well-known companies, these return rich results. For smaller or private companies, Queries 2 and 3 may be sparse — that's fine. The qualitative sections still deliver value because Claude synthesizes whatever is available into useful framing.
Sections
Listed in priority order. Cut from the bottom if space is constrained.
1. Company Header
Streamlined — identification only, no valuation metrics.
Field
Notes
Company name
Large, bold
Ticker & Exchange
If public; omit for private
HQ
City, State/Country
Industry / Sector
Employees
Annual Revenue (latest)
Round to nearest $B or $M
Market Cap
If public; omit for private
FY Revenue Guidance
If available from earnings data; e.g., "6–8% organic growth"
FY EPS or EPS Guidance
If public company; pull from earnings.txt
Key Financial Metric
Adj. EPS, EBITDA margin, or similar — one headline number
Forward guidance and EPS data come from Query 2 (earnings) — source from earnings.txt when populating the header, not just company-profile.txt.
One horizontal band at the top. No enterprise value, no beta — this audience doesn't need them.
2. Company Overview
The most important section. A sales rep should read this and walk into a meeting with a solid grasp of the prospect.
Do not paste the CIQ company summary. It reads like an SEC filing and will lose a non-finance audience. Rewrite in 3-5 sentences of plain language:
What the company does (no investor jargon — say "sells" not "monetizes", say "yearly revenue" not "top-line CAGR")
Who their customers are
How they make money
Where they operate
What makes them distinctive
Write in prose paragraphs. A non-finance person should understand every sentence.
3. Strategic Priorities & Management Commentary
What is leadership focused on right now? If you know what the CEO is talking about, you can align your pitch.
This is NOT an earnings recap. Do not reuse the same bullets as the equity research tear sheet. Extract 3-5 strategic themes with thematic labels and supporting data points:
AI/Data Monetization: Management is investing aggressively in AI capabilities, allocating $X to R&D in FY2024 and launching three new AI-powered products.
Margin Expansion: CEO cited operational efficiency as a top priority, targeting 200bps of operating margin improvement through automation.
International Growth: Opening new offices in EMEA; Europe now represents 25% of revenue, up from 18%.
Each bullet should answer: "What does this company care about right now, and what evidence supports it?" A sales rep should read these and immediately see angles to connect their product.
If earnings call data isn't available (common for private companies), replace with "Recent Developments" pulling from whatever news or announcements the tools return.
4. Financial Snapshot
Simplified. Single compact table — just scale, direction, and one profitability signal. A sales rep needs to know three things: how big is this company, is it growing, and is it healthy.
Metric
FY[prior year]
FY[latest]
YoY Change
Revenue
+X%
Gross Margin %
+X.Xpp
Employees
Three rows maximum. No EBITDA, no EV multiples, no balance sheet, no net income. Gross margin (not EBITDA, not net income) is the right single profitability metric for a sales audience — it's intuitive ("how much they keep after direct costs") and signals business health without requiring finance literacy. If the rep needs deeper financials, they can request the equity research version.
For private companies, this table may have only revenue and employees — two data points showing scale and growth are enough for a sales meeting.
5. Key Relationships & Ecosystem
Helps reps understand the prospect's world and identify angles.
Four labeled lists, 3-5 names each with one-line descriptors:
Customers: Who they sell to. Helps understand their go-to-market and shared target customers.
Example: "JPMorgan Chase — customer (enterprise analytics platform deployment)"
Vendors / Technology: What they buy. Identifies displacement or integration opportunities.
Example: "AWS — vendor (primary cloud infrastructure); Snowflake — vendor (data warehouse)"
Partners: Who they work with. Co-sell angles, mutual connections.
Example: "Deloitte — partner (implementation for enterprise clients)"
Competitors: Who they compete against. Positioning context.
Example: "Bloomberg — competitor (financial data terminal)"
Every entry needs a parenthetical descriptor so the rep understands what the relationship means, not just who.
If relationship data isn't available, note "Relationship data not available" and move on.
6. Recent News & Developments
3-5 bullets, each one sentence, most recent first. Include date if available. Lead with the latest earnings report — it's the most important recent event for a sales meeting and sets the context for everything else. Then: M&A, product launches, leadership changes, major wins.
Include upcoming catalysts at the end of the section with a "Coming Up:" label. Examples: upcoming earnings dates, pending divestitures, product launches, investor days, regulatory milestones. These create natural engagement windows for sales outreach and are often the best reason to reach out ("I noticed you have your Investor Day coming up in Q2..."). Pull from earnings call commentary and M&A data (pending transactions).
7. Conversation Starters (cut first)
2-3 suggested talking points synthesized from the data above. Each starter must reference a specific strategic priority from Section 3 — generic questions are useless. Frame as questions.
Tag each starter with a suggested persona — e.g., (CTO), (CFO), (CDO), (Head of Data), (VP Engineering), (Head of Procurement). A rep meeting with a CTO needs a different opener than one meeting with a CFO. If the user specified who they're meeting with, generate starters for that persona only.
Examples:
(CTO/CDO) "You mentioned [specific AI initiative from Section 3] on your last earnings call — how is that impacting your [relevant need]?"
(CFO/COO) "With your [margin expansion target from Section 3], are you evaluating tools that could accelerate that timeline?"
(VP Strategy/Corp Dev) "I noticed [Company] recently acquired [target] — does that change your approach to [capability]?"
If the user described what product/service they're selling, tailor these to connect the prospect's priorities to that offering. If not, keep them grounded in the prospect's strategic themes but generic in solution framing.
Validation test: Before finalizing each conversation starter, verify it contains at least one specific number, date, product name, or initiative name drawn from the tear sheet. A question that could apply to any company in the sector is not a good conversation starter. "How are you thinking about AI?" is generic. "Your CEO mentioned $1B in AI investment since 2018 and 20% adoption of the iLEVEL auto-ingestion feature — how is that changing your analysts' workflows?" is specific and demonstrates preparation.
This section is Claude's synthesis, not raw data from the tools. Label it clearly.
Formatting Notes
This should be the warmest, most readable tear sheet. Rigorous content, but the formatting should feel like a briefing memo, not a data terminal.
Body text: use the full 9pt (size: 18). No compression — readability over density.
Line spacing: 1.15x on body paragraphs (slightly more generous than default). This template is the one where whitespace is a feature, not waste.
Company Overview and Strategic Priorities should take ~40-50% of the page.
Financial Snapshot: visually compact, secondary prominence. Keep it small and clean.
Key Relationships: consider two-column layout (Customers + Vendors on left, Partners + Competitors on right) to save vertical space while keeping descriptors visible.
Conversation Starters: use the indented block-style bullets. These are the payoff of the document — they should stand out visually.
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