Tear Sheet
AnthropicOfficialCreated by Kensho TechnologiesDistributed by Anthropic
- Skill
- Content generator
- Business and productivity
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The Tear Sheet Generator creates professional, standardized company one-pagers for four distinct financial audiences: Equity Research, Investment Banking/M&A, Corporate Development, and Sales/Business Development. By leveraging S&P Global's Kensho LLM-ready API, the skill pulls live financial data, market metrics, and business intelligence to produce a formatted Word document. It enforces strict visual and data integrity standards, ensuring that every document—regardless of the target audience—adheres to professional banking design conventions, including specific typography, table layouts, and mandatory footer disclaimers.
What it does
- Fetches live financial, valuation, and business data from S&P Capital IQ.
- Calculates derived financial metrics like margins, growth rates, and efficiency ratios.
- Generates professional Word documents with consistent branding and layout.
- Tailors content and depth based on the selected audience (e.g., thesis-driven for analysts vs. strategic-fit for Corp Dev).
- Handles both public and private company data profiles.
- Enforces data integrity through automated arithmetic validation and intermediate file logging.
When to use it
- When you need a professional company snapshot for meeting preparation or investment analysis.
- When preparing M&A target profiles or equity research summaries.
- When you require a concise, data-backed document for sales or business development outreach.
- When you need to standardize company reporting across different internal teams.
Advantages
- Ensures professional, consistent formatting across all generated documents.
- Reduces manual data entry and calculation errors through automated processing.
- Provides audience-specific insights rather than generic company summaries.
- Maintains a clear audit trail of data through intermediate file storage.
- Supports both public and private company analysis.
Usage examples
- “Generate a tear sheet for Nvidia for an Equity Research audience.”
- The agent will query S&P Capital IQ for Nvidia's financials, market data, and consensus estimates, then compile a one-page, thesis-oriented document formatted for an analyst.
- “Create a Corp Dev target profile for a private software company named Acme Analytics.”
- The agent will gather business overview, ownership, and available financial data to produce a 1-2 page strategic fit analysis focused on integration and acquisition value.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/anthropics/tear-sheet/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip tear-sheet.zip -d .agents/skills
Documentation by Kensho Technologies
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.
Colors:
Primary (header banner background, section header text): #1F3864
Accent (signature section highlights): #2E75B6
Table header row fill: #D6E4F0
Table alternating row fill: #F2F2F2
Table borders: #CCCCCC
Header banner text: #FFFFFF
Typography (sizes in half-points for docx-js):
Font family: Arial
Company name: 18pt bold (size: 36)
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: noneandshading: noneon 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 usedoc.addParagraph()with a separate horizontal rule element. Do not usethematicBreak. 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)
Cell padding: top/bottom 40 DXA, left/right 80 DXA
Right-align all numeric columns
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.
const docx = require("docx");
const {
Document, Paragraph, TextRun, Table, TableRow, TableCell,
WidthType, AlignmentType, BorderStyle, ShadingType,
Header, Footer, PageNumber, HeadingLevel, TableLayoutType,
convertInchesToTwip
} = docx;
// ── Color constants ──
const COLORS = {
PRIMARY: "1F3864",
ACCENT: "2E75B6",
TABLE_HEADER_FILL: "D6E4F0",
TABLE_ALT_ROW: "F2F2F2",
TABLE_BORDER: "CCCCCC",
HEADER_TEXT: "FFFFFF",
FOOTER_TEXT: "666666",
};
const FONT = "Arial";
// ── 1. createHeaderBanner ──
// Returns an array of docx elements: [banner paragraph, key-value table]
function createHeaderBanner(companyName, leftFields, rightFields) {
// leftFields / rightFields: arrays of { label: string, value: string }
const banner = new Paragraph({
children: [
new TextRun({
text: companyName,
bold: true,
size: 36, // 18pt
color: COLORS.HEADER_TEXT,
font: FONT,
}),
],
shading: { type: ShadingType.CLEAR, color: "auto", fill: COLORS.PRIMARY },
spacing: { after: 0 },
alignment: AlignmentType.LEFT,
});
function buildCellParagraphs(fields) {
return fields.map(
(f) =>
new Paragraph({
children: [
new TextRun({ text: f.label + " ", bold: true, size: 18, font: FONT }),
new TextRun({ text: f.value, size: 18, font: FONT }),
],
spacing: { after: 40 },
})
);
}
const noBorder = { style: BorderStyle.NONE, size: 0, color: "FFFFFF" };
const noBorders = { top: noBorder, bottom: noBorder, left: noBorder, right: noBorder };
const noShading = { type: ShadingType.CLEAR, color: "auto", fill: "FFFFFF" };
const kvTable = new Table({
rows: [
new TableRow({
children: [
new TableCell({
children: buildCellParagraphs(leftFields),
width: { size: 50, type: WidthType.PERCENTAGE },
borders: noBorders,
shading: noShading,
}),
new TableCell({
children: buildCellParagraphs(rightFields),
width: { size: 50, type: WidthType.PERCENTAGE },
borders: noBorders,
shading: noShading,
}),
],
}),
],
width: { size: 100, type: WidthType.PERCENTAGE },
});
return [banner, kvTable];
}
// ── 2. createSectionHeader ──
// Returns a single Paragraph with bottom border rule
function createSectionHeader(text) {
return new Paragraph({
children: [
new TextRun({
text: text,
bold: true,
size: 22, // 11pt
color: COLORS.PRIMARY,
font: FONT,
}),
],
spacing: { before: 240, after: 0 }, // 12pt before, 0pt after
border: {
bottom: { style: BorderStyle.SINGLE, size: 1, color: COLORS.TABLE_BORDER },
},
});
}
// ── 3. createTable ──
// headers: string[], rows: string[][], options: { accentHeader?, fontSize? }
function createTable(headers, rows, options = {}) {
const fontSize = options.fontSize || 17; // 8.5pt default
const headerFill = options.accentHeader ? COLORS.ACCENT : COLORS.TABLE_HEADER_FILL;
const headerTextColor = options.accentHeader ? COLORS.HEADER_TEXT : "000000";
const cellBorders = {
top: { style: BorderStyle.SINGLE, size: 1, color: COLORS.TABLE_BORDER },
bottom: { style: BorderStyle.SINGLE, size: 1, color: COLORS.TABLE_BORDER },
left: { style: BorderStyle.SINGLE, size: 1, color: COLORS.TABLE_BORDER },
right: { style: BorderStyle.SINGLE, size: 1, color: COLORS.TABLE_BORDER },
};
const cellMargins = { top: 40, bottom: 40, left: 80, right: 80 };
function isNumeric(val) {
if (typeof val !== "string") return false;
const cleaned = val.replace(/[,$%()]/g, "").trim();
return cleaned !== "" && !isNaN(cleaned);
}
// Header row
const headerRow = new TableRow({
children: headers.map(
(h) =>
new TableCell({
children: [
new Paragraph({
children: [
new TextRun({
text: h,
bold: true,
size: fontSize,
color: headerTextColor,
font: FONT,
}),
],
}),
],
shading: { type: ShadingType.CLEAR, color: "auto", fill: headerFill },
borders: cellBorders,
margins: cellMargins,
})
),
});
// Data rows with alternating shading
const dataRows = rows.map((row, rowIdx) => {
const fill = rowIdx % 2 === 1 ? COLORS.TABLE_ALT_ROW : "FFFFFF";
return new TableRow({
children: row.map((cell, colIdx) => {
const align = colIdx > 0 && isNumeric(cell)
? AlignmentType.RIGHT
: AlignmentType.LEFT;
return new TableCell({
children: [
new Paragraph({
children: [
new TextRun({ text: cell, size: fontSize, font: FONT }),
],
alignment: align,
}),
],
shading: { type: ShadingType.CLEAR, color: "auto", fill: fill },
borders: cellBorders,
margins: cellMargins,
});
}),
});
});
return new Table({
rows: [headerRow, ...dataRows],
width: { size: 100, type: WidthType.PERCENTAGE },
});
}
// ── 4. createBulletList ──
// items: string[], style: "synthesis" | "informational"
function createBulletList(items, style = "synthesis") {
const indent =
style === "synthesis"
? { left: 360, hanging: 180 } // 360 DXA left, hanging indent for bullet
: { left: 180 }; // 180 DXA, no hanging
return items.map(
(item) =>
new Paragraph({
children: [
new TextRun({ text: "• ", font: FONT, size: 18 }),
new TextRun({ text: item, font: FONT, size: 18 }),
],
indent: indent,
spacing: { after: 60 },
})
);
}
// ── 5. createFooter ──
// date: string (e.g., "February 23, 2026")
function createFooter(date) {
return new Footer({
children: [
new Paragraph({
children: [
new TextRun({
text: `Data: S&P Capital IQ via Kensho | Analysis: AI-generated | ${date}`,
italics: true,
size: 14, // 7pt
color: COLORS.FOOTER_TEXT,
font: FONT,
}),
],
alignment: AlignmentType.CENTER,
}),
new Paragraph({
children: [
new TextRun({
text: "For informational purposes only. Not investment advice.",
italics: true,
size: 14,
color: COLORS.FOOTER_TEXT,
font: FONT,
}),
],
alignment: AlignmentType.CENTER,
}),
],
});
}Usage in generated scripts:
Copy all functions and constants above into the generated Node.js script
Call
createHeaderBanner(...)instead of manually building banner paragraphs and tablesCall
createSectionHeader(...)for every section title — never manually set paragraph bordersCall
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 startersCall
createBulletList(items, "informational")for relationship entriesPass
createFooter(date)to the Document constructor'sfooters.defaultproperty
What these functions eliminate:
Black background tables (enforces
ShadingType.CLEAReverywhere)Separate horizontal rule paragraphs under section headers (enforces
border.bottomon 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.mdIB / M&A →
references/ib-ma.mdCorp Dev →
references/corp-dev.mdSales / 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:
Skip: stock price, 52-week range, beta, stock performance, consensus estimates, trading comps
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:
Margins: Gross Margin %, EBITDA Margin %, FCF Margin %, Operating Margin %
Growth rates: YoY revenue growth, YoY segment revenue growth, YoY EPS growth
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
Example rows:
metric,value,formula,components
gross_margin_fy2024,72.4%,gross_profit/revenue,"9524/13159"
revenue_growth_fy2024,12.3%,(current-prior)/prior,"13159/11716"
net_debt_fy2024,2150,total_debt-cash,"4200-2050"Step 3c: Verify Data Files
Before generating the document, verify that all intermediate files are present and populated.
Read each intermediate file via separate read operations and print a verification summary:
=== Tear Sheet Data Verification ===
company-profile.txt: ✓ (12 fields)
financials.csv: ✓ (36 rows)
segments.csv: ✓ (8 rows)
valuation.csv: ✓ (5 rows)
calculations.csv: ✓ (18 rows)
earnings.txt: ✓ (populated)
relationships.txt: ⚠ MISSING
peer-comps.csv: ✓ (12 rows)
================================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.
Output filename: [CompanyName]_TearSheet_[Audience]_[YYYYMMDD].docx
Example: Nvidia_TearSheet_CorpDev_20260220.docx
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.
File schemas:
| File | Format | Columns / Structure | Used By |
|---|---|---|---|
/tmp/tear-sheet/company-profile.txt | Key-value text | name, ticker, exchange, HQ, sector, industry, founded, employees, market_cap, enterprise_value, stock_price, 52wk_high, 52wk_low, shares_outstanding, beta, ownership | All |
/tmp/tear-sheet/financials.csv | CSV | period,line_item,value,source | All |
/tmp/tear-sheet/segments.csv | CSV | period,segment_name,revenue,source | ER, IB, CD |
/tmp/tear-sheet/valuation.csv | CSV | metric,trailing,forward,source | ER, IB, CD |
/tmp/tear-sheet/consensus.csv | CSV | metric,fy_year,value,source | ER |
/tmp/tear-sheet/earnings.txt | Structured text | Quarter, date, key quotes, guidance, key drivers | ER, IB, Sales |
/tmp/tear-sheet/relationships.txt | Structured text | 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.
Files
- ATTRIBUTION.mdAdded by AutoGineer1.1 KiB
- LICENSE11.1 KiB
- SKILL.md30.5 KiB
- references/corp-dev.md14.0 KiB
- references/equity-research.md9.5 KiB
- references/ib-ma.md11.4 KiB
- references/sales-bd.md9.5 KiB
references/corp-dev.md
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.
7. Ownership Snapshot (data permitting — omit if tools return nothing)
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:
Key risks: Customer concentration, key-person dependency, technology debt indicators
Integration complexity: Geography (multi-country = harder), employee count, number of products
Synergy signals: Shared customers, complementary products, overlapping technology vendors
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
Valuation Context prose (section 6) — keep peer comp table, cut interpretive paragraph below it
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.
Requirements and compatibility
Written for: Claude Code, Claude apps
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
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
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Attribution and licence
- Created by
- Kensho Technologies
- Publisher
- Anthropic (Official)
- Distributed by
- Anthropic
- Source
- anthropics/financial-services · plugins/partner-built/spglobal/skills/tear-sheet · commit 6056506
- Licence
- Apache License 2.0 (redistribution allowed)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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