initiate

name	initiate
description	Initiate coverage — generate both research note (HTML) and Excel model (.xlsx)
argument-hint	TICKER

Initiate coverage on the company specified by the user: $ARGUMENTS

Before starting, read data-access.md for data access methods and design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.

This is the capstone skill that produces both a research note (styled HTML) and an Excel model (React artifact with SheetJS) from a single comprehensive data gathering pass.

Strategy

Rather than running /research-note and /build-model independently (which would duplicate data gathering), this skill gathers a superset of data once, then renders both outputs.

Phase 1 — Company Setup

Look up the company by ticker using discover_companies. Capture:

• company_id
• latest_calendar_quarter — anchor for all period calculations (see data-access.md Section 1.5)
• latest_fiscal_quarter
• Firm name for report attribution (default: "Daloopa") — see data-access.md Section 4.5

Get market data using the 3-step resolution: (1) MCP market data tools if available, (2) web search, (3) sensible defaults (see data-access.md Section 2):

• Current price, market cap, shares outstanding, beta
• Trading multiples (P/E, EV/EBITDA, P/S, P/B)
• Risk-free rate (for DCF)

Initialize context: context = {company_name, ticker, date, price, market_cap, firm_name, ...}

Phase 2 — Comprehensive Data Gathering

Calculate 8-16 quarters backward from latest_calendar_quarter. Pull:

Income Statement — search and pull all available:

• Revenue / Net Sales
• Cost of Revenue / COGS
• Gross Profit
• Research & Development
• Selling, General & Administrative
• Total Operating Expenses
• Operating Income
• Interest Expense / Income
• Pre-tax Income
• Tax Expense
• Net Income
• Diluted EPS
• Diluted Shares Outstanding
• EBITDA (or compute from Op Income + D&A, label "(calc.)")
• D&A

Balance Sheet — search and pull all available:

• Cash and Equivalents
• Short-term Investments
• Accounts Receivable
• Inventory
• Total Current Assets
• PP&E (net)
• Goodwill
• Total Assets
• Accounts Payable
• Short-term Debt
• Long-term Debt
• Total Liabilities
• Total Equity

Cash Flow — search and pull all available:

• Operating Cash Flow
• Capital Expenditures
• Depreciation & Amortization
• Acquisitions
• Dividends Paid
• Share Repurchases
• Free Cash Flow (compute if not direct: OCF - CapEx, label "(calc.)")

Segments:

• Revenue by segment
• Operating income by segment (if available)

Geographic:

• Revenue by geography

KPIs:

• All company-specific operating metrics (subscribers, units, ARPU, retention, etc.)

Guidance:

• All guidance series and corresponding actuals

Share Activity:

• Share count, buyback amounts

For every value returned by get_company_fundamentals, record its fundamental_id (the id field). Store each data point as {value, fundamental_id} so citations can be rendered in both outputs.

Compute margins, YoY growth rates, and ratios for each quarter.

Cost Structure & Margin Analysis

After the core financial pull:

• COGS driver identification: Search for cost-related series ("cost of goods", "materials", "manufacturing", "input cost"). Identify 3-5 biggest cost line items and their trends.
• OpEx breakdown: Pull R&D and SG&A separately. Compute R&D % of revenue and SG&A % of revenue trends.
• Margin driver analysis: For each major margin (gross, operating, net), identify what's driving expansion or compression — pricing power, cost leverage, mix shift, or one-time items.

Phase 3 — Industry-Specific Deep Dive

Determine the company's sector and apply the relevant analysis template:

• Manufacturing/Industrial: Bookings & backlog, book-to-bill ratio, pipeline by geography, capacity utilization
• SaaS/Technology: ARR/MRR trajectory, net retention rate, customer cohort analysis, RPO/deferred revenue trends
• Retail/Consumer: Same-store sales, store count trajectory, traffic vs ticket decomposition, inventory health
• Financials/Banks: NIM trajectory, provision trends, loan growth by category, capital ratios (CET1, TCE)
• Healthcare/Pharma: Pipeline summary (drug, indication, phase, milestone), product revenue breakdown, patent cliff timeline
• Energy: Production volumes, realized pricing vs benchmark, proved reserves, breakeven analysis

Search for relevant series using discover_company_series with sector-appropriate keywords. Pull available data and build the narrative.

Build context.industry_deep_dive (string) — sector-specific analysis narrative with Daloopa citations, organized by the relevant template above.

Phase 4 — Peer Analysis

Identify 5-8 comparable companies. Get peer trading multiples using the 3-step resolution: (1) MCP market data tools if available, (2) web search, (3) sensible defaults (see data-access.md Section 2). If consensus forward estimates are available (data-access.md Section 3), include NTM estimates. Pull peer fundamentals from Daloopa where available (revenue growth, margins).

Build context.comps and context.comps_table.

Phase 5 — Projections

Build forward estimates using the following methodology:

• Revenue: Start with latest guidance (if available), then decay to long-term growth rate (industry average or historical trend). Apply quarterly seasonality patterns from trailing data.
• Gross Margin: Mean-revert to trailing 8-quarter average, with adjustment for recent trends or guidance commentary.
• Operating Expenses: Project as % of revenue, trending toward trailing averages. R&D and SG&A may have different trajectories.
• CapEx: Project as % of revenue based on trailing 4-8 quarter average and guidance.
• D&A: Project based on trailing average as % of revenue or PP&E.
• Tax Rate: Use trailing effective tax rate or guidance.
• Share Count: Project dilution/buyback based on trailing trends and guidance.
• Working Capital: Project DSO, DIO, DPO based on trailing averages.

Calculate all quarterly projections, then sum to annual. Project 4-8 quarters forward. Describe methodology inline and perform calculations directly.

Phase 6 — DCF Valuation

Calculate:

• WACC: Use CAPM for cost of equity (Rf + Beta × ERP, where ERP = 6.0%). Cost of debt = Interest Expense / Total Debt. WACC = (E/V × Re) + (D/V × Rd × (1 - Tax Rate)).
• 5-year FCF projections: Annualize from quarterly projections (FCF = Op Cash Flow - CapEx).
• Terminal Value: Use perpetuity growth at 2.5-3.0%.
• Implied Share Price: (PV of FCFs + Terminal Value - Net Debt) / Shares Outstanding
• Sensitivity Matrix: WACC (7 values: -3% to +3% from base) × Terminal Growth (6 values: 1.5% to 4.0%).

Build context.dcf and context.dcf_summary (set context.has_dcf = true).

Phase 7 — Qualitative Research + News & Catalysts

SEC Filing Research

Search SEC filings across multiple queries:

• "risk" / "uncertainty" / "challenge" for risk factors
• "growth" / "opportunity" / "expansion" for growth drivers
• "competition" / "market share" for competitive dynamics
• "outlook" / "guidance" for management's forward view
• Company-specific strategic topics (e.g., "AI", "cloud", etc.)

Extract and organize into:

• context.risks — ranked list of risks with impact/probability
• context.investment_thesis — variant perception, thesis pillars, catalysts
• context.company_description — 2-3 sentence business description

News & Catalysts via WebSearch

Run 4 WebSearch queries to gather recent external context:

1. "{TICKER} {company_name} news {year}" — recent headlines and developments
2. "{TICKER} analyst upgrade downgrade price target" — sell-side sentiment shifts
3. "{TICKER} catalysts risks" — forward-looking events and risk factors
4. "{company_name} industry outlook {sector}" — macro and industry trends

Organize results into:

• context.news_timeline (string) — 6-10 key events from the last 6-12 months in reverse chronological order. Each event: date, headline, 1-sentence impact, sentiment tag (Positive / Negative / Mixed / Upcoming). Format as a numbered list.

• context.forward_catalysts (string) — Organized by timeframe:

  • Near-term (0-3 months, HIGH priority): earnings dates, product launches, regulatory decisions
  • Medium-term (3-12 months, MEDIUM priority): strategic milestones, contract renewals, industry events
  • Long-term (1-3 years, LOW priority): secular trends, market expansion, competitive dynamics

• context.policy_backdrop (string) — Macro/regulatory context affecting the company. Tariffs, regulation, interest rates, sector-specific policy. Leave empty string if not material.

Phase 8 — Guidance Track Record

Search for guidance series ("guidance", "outlook", "forecast", "estimate", "target"). Pull guidance and corresponding actuals. Apply +1 quarter offset rule for quarterly guidance, same-year rule for annual guidance from Q1/Q2/Q3, next-year rule for annual guidance from Q4. Compute beat/miss rates and patterns. Build context.guidance and context.guidance_table (set context.has_guidance = true/false).

Phase 9 — What You Need to Believe

Build falsifiable bull/bear beliefs:

Bull Beliefs (To Go Long)

Write 4-6 numbered beliefs, each with:

• One bold statement (the belief itself)
• 2-3 sentences of evidence with Daloopa citations supporting why this could be true
• Each belief must be falsifiable — testable with observable data within 6 months

Example format: "1. Revenue growth re-accelerates to 15%+ as AI monetization scales. Cloud segment grew $X.Xbn last quarter, up X% YoY, with management noting..."

Bear Beliefs (To Go Short)

Same format — 4-6 numbered falsifiable beliefs with evidence for the downside case.

Valuation Math

For each side:

• Bull target: forward multiple × forward earnings estimate = price target. Show the math.
• Bear target: same structure with bear-case multiple and earnings.

Risk/Reward Assessment

• Compare bull upside % vs bear downside % from current price
• If asymmetry is significant (e.g., 30% upside vs 40% downside), flag it explicitly
• State which side has the better risk/reward and why

Build context.bull_beliefs, context.bull_target, context.bear_beliefs, context.bear_target, context.risk_reward_assessment.

Phase 10 — Capital Allocation

Pull buyback, dividend, share count, FCF data. Compute shareholder yield, FCF payout ratio, net leverage. Build context.capital_allocation_commentary.

Phase 11 — Synthesis + Tensions + Monitoring

This is the most judgment-intensive step. Be honest and critical — the reader is a professional investor who needs your real assessment, not a balanced summary.

Core Synthesis

Write:

• Executive Summary: 3-4 sentence TL;DR covering current state, key thesis, valuation view. Include a clear directional view — is this stock attractive, fairly valued, or overvalued at the current price?
• Variant Perception: What does the market think vs what do you see in the data? Where is the consensus wrong? If you agree with consensus, say that too — but explain what could change.
• Key Findings: Top 3-5 most notable data points or trends — prioritize what changes the investment thesis, not just what's interesting
• Red Flags & Concerns: Any quality-of-earnings issues, sustainability questions, or risks the market may be underpricing
• Build context.executive_summary, context.variant_perception

Five Key Tensions

Identify the 5 most critical bull/bear debates for this stock. Each tension is a single line that frames both sides. Alternate between bullish-leaning and bearish-leaning tensions. Every tension must reference a specific data point from the analysis.

Format as a numbered list:

1. "[Bullish factor] vs [Bearish factor]" — cite the specific metric
2. "[Bearish factor] vs [Bullish factor]" — cite the specific metric ...etc.

Build context.five_key_tensions (string).

Monitoring Framework

Build two monitoring lists for ongoing tracking:

Quantitative Monitors — 5-7 specific metrics with explicit thresholds:

• Format: "Metric: current value → bull threshold / bear threshold"
• Example: "Gross Margin: 45.2% → above 46% confirms pricing power / below 43% signals cost pressure"

Qualitative Monitors — 5-7 factors to watch:

• Management tone shifts on earnings calls
• Competitive dynamics (new entrants, pricing pressure)
• Regulatory developments
• Customer concentration changes
• Capital allocation pivots

Build context.monitoring_quantitative and context.monitoring_qualitative (strings, numbered lists).

Structured Tables

Build structured tables for both outputs:

• context.key_metrics_table — [{metric, value, vs_prior}] for the exec summary table
• context.financials_table — [{metric, q1, q2, ...}] for the financial analysis section
• context.segments_table, context.geo_table, context.shares_outstanding_table
• context.opex_breakdown_table — [{metric, q1, q2, ...}] for R&D, SG&A, % of revenue rows
• context.guidance_table, context.comps_table, etc.

Phase 12 — Render Research Note (HTML)

Using the HTML Report Template from design-system.md, generate a styled HTML report with full CSS inlined. The report should include:

Header Section:

• Company name and ticker
• Report date and firm attribution
• Five Key Tensions (numbered list)

Section 1: Executive Summary

• Key metrics table
• Executive summary narrative
• Variant perception

Section 2: Company Overview

• Business description
• Investment thesis

Section 3: Recent News & Catalysts

• News timeline
• Forward catalysts
• Policy backdrop

Section 4: Financial Analysis

• Financials table (8-16 quarters)
• Cost structure & margin analysis
• OpEx breakdown table
• Segment and geographic tables
• Share count table

Section 5: Industry-Specific Analysis

• Industry deep dive narrative

Section 6: Guidance Track Record

• Guidance table and beat/miss analysis (if available)

Section 7: What You Need to Believe

• Bull beliefs with valuation target
• Bear beliefs with valuation target
• Risk/reward assessment

Section 8: Catalysts

• Forward catalysts
• Policy backdrop

Section 9: Capital Allocation

• Capital allocation commentary

Section 10: Valuation

• DCF summary and sensitivity (if available)
• Comps commentary (if available)

Section 11: Risks

• Risks summary

Section 12: Monitoring Framework

• Quantitative monitors
• Qualitative monitors

Appendix:

• Additional context or data

Context Key Checklist

Verify these keys exist before rendering (set empty string if data unavailable):

Cover & Summary: company_name, ticker, date, price, market_cap, five_key_tensions, executive_summary, key_metrics_table

Thesis & Overview: investment_thesis, variant_perception, company_description

News: news_timeline

Financials: financials_table, cost_margin_analysis, opex_breakdown_table, segments_table, geo_table, shares_outstanding_table

Industry: industry_deep_dive

Guidance: has_guidance, guidance_track_record

What You Need to Believe: bull_beliefs, bull_target, bear_beliefs, bear_target, risk_reward_assessment

Catalysts: forward_catalysts, policy_backdrop

Capital Allocation: capital_allocation_commentary

Valuation: has_dcf, dcf_summary, has_comps, comps_commentary

Risks: risks_summary

Monitoring: monitoring_quantitative, monitoring_qualitative

Appendix: appendix_content

Citation enforcement: Every financial figure from Daloopa in the HTML report must use citation format: [$X.XX million](https://daloopa.com/src/{fundamental_id}). If a number came from get_company_fundamentals, it must have a citation link. No exceptions.

Phase 13 — Render Excel Model

Generate a React artifact that builds the .xlsx file using SheetJS (xlsx library). The artifact should:

1. Create 8 tabs with the following structure:

Tab 1: Income Statement

• Rows: Revenue, COGS, Gross Profit, R&D, SG&A, Total OpEx, Op Income, Interest, Pre-Tax Income, Tax, Net Income, Diluted EPS, Shares
• Columns: Historical periods (8-16Q) + Projected periods (4-8Q)
• Sub-rows: YoY growth %, margin % where applicable
• Header: Company name, ticker, report date
• Formatting: Numbers with commas/decimals, percentages, bold headers, frozen panes

Tab 2: Balance Sheet

• Rows: Assets section (Cash, Investments, AR, Inventory, Current Assets, PP&E, Goodwill, Total Assets), Liabilities section (AP, ST Debt, LT Debt, Total Liabilities, Equity)
• Columns: Historical + Projected periods
• Sub-rows: % of Total Assets for key line items
• Same formatting standards

Tab 3: Cash Flow

• Rows: Op Cash Flow, CapEx, Free Cash Flow, Acquisitions, Dividends, Buybacks, Net Change in Cash
• Columns: Historical + Projected periods
• Sub-rows: FCF yield %, CapEx as % Revenue
• Same formatting standards

Tab 4: Segments

• Rows: Revenue by segment, Op Income by segment (if available)
• Columns: Historical + Projected periods
• Sub-rows: Segment as % of total, segment growth rates
• Same formatting standards

Tab 5: KPIs

• Rows: All company-specific operating metrics discovered
• Columns: Historical + Projected periods
• Sub-rows: YoY growth or relevant unit economics
• Same formatting standards

Tab 6: Projections

• Editable assumption inputs (yellow highlighting): Revenue growth %, Gross margin %, Op margin %, CapEx % revenue, Tax rate %, Buyback rate QoQ
• Calculated outputs: Projected P&L, BS, CF driven by assumptions
• Commentary box explaining methodology
• Same formatting standards

Tab 7: DCF

• Inputs: WACC, Terminal Growth, Risk-Free Rate, ERP, Beta, Cost of Debt
• FCF Projection (5 years annualized)
• Terminal Value calculation
• PV calculations
• Enterprise Value → Equity Value → Implied Share Price
• Sensitivity table: WACC (rows) × Terminal Growth (cols) showing implied price
• Color scale: green (upside) to red (downside) vs current price
• Same formatting standards

Tab 8: Summary

• Company overview (name, ticker, sector, description)
• Current market data (price, market cap, shares, beta)
• Valuation summary: DCF implied price, peer-implied range, current price, upside/downside %
• Peer trading multiples table
• Key model outputs: Trailing revenue, Projected revenue growth, Trailing/Projected margins
• Same formatting standards

2. Apply design-system.md formatting conventions:

• Number format: $X.Xbn for large numbers, X.X% for percentages, X.Xx for multiples
• Color palette: Navy #1B2A4A (headers), Steel Blue #4A6FA5 (sub-headers), Gold #C5A55A (highlights), Green #27AE60 (positive), Red #C0392B (negative)
• Bold headers, frozen top row and left column
• Yellow fill (#FFEB3B) for editable input cells

3. Include a download button that triggers the .xlsx file download with filename: {TICKER}_model.xlsx

Output

Present both deliverables to the user:

Research Note (HTML):

• Present the styled HTML report directly in the response
• Tell the user to save the HTML and open in browser for full formatting

Excel Model (React Artifact):

• Present the React artifact with SheetJS
• Tell the user to click the download button to save the .xlsx file
• Note that yellow cells in the Projections tab are editable inputs

Summary:

• 3-4 sentence executive summary
• Key valuation range (DCF implied price + comps range)
• Top 3 findings
• Bull upside % vs bear downside % risk/reward assessment

All financial figures must use Daloopa citation format: $X.XX million