[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-openai-initiate":3,"mdc--eqs266-key":36,"related-org-openai-initiate":2919,"related-repo-openai-initiate":3124},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":25,"repoUrl":26,"updatedAt":27,"license":28,"forks":29,"topics":30,"repo":31,"sourceUrl":34,"mdContent":35},"initiate","generate research notes and financial models","Initiate coverage — generate both research note (HTML) and Excel model (.xlsx)",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"openai","OpenAI","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fopenai.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Research","research","tag",{"name":17,"slug":18,"type":15},"Financial Modeling","financial-modeling",{"name":20,"slug":21,"type":15},"Excel","excel",{"name":23,"slug":24,"type":15},"HTML","html",3992,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins","2026-06-30T19:00:57.102",null,465,[],{"repoUrl":26,"stars":25,"forks":29,"topics":32,"description":33},[],"OpenAI Plugins","https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins\u002Ftree\u002FHEAD\u002Fplugins\u002Fdaloopa\u002Fskills\u002Finitiate","---\nname: initiate\ndescription: Initiate coverage — generate both research note (HTML) and Excel model\n  (.xlsx)\n---\n\nInitiate coverage on the company named in the user's request. If no ticker or company is provided, ask for one before proceeding.\n\n**Before starting, read `..\u002Fdata-access.md` for data access methods and `..\u002Fdesign-system.md` for formatting conventions.** Follow the data access detection logic and design system throughout this skill.\n\nThis is the capstone skill that produces both a research note (styled HTML) and an Excel model (.xlsx) from a single comprehensive data gathering pass.\n\n## Strategy\nRather than running the research-note and build-model skills independently (which would duplicate data gathering), this skill gathers a superset of data once, then renders both outputs.\n\n## Phase 1 — Company Setup\nLook up the company by ticker using `discover_companies`. Capture:\n- `company_id`\n- `latest_calendar_quarter` — anchor for all period calculations (see `..\u002Fdata-access.md` Section 1.5)\n- `latest_fiscal_quarter`\n- Firm name for report attribution (default: \"Daloopa\") — see `..\u002Fdata-access.md` Section 4.5\n\nGet market data using the 3-step resolution: (1) MCP market data tools if available, (2) web search, (3) sensible defaults (see `..\u002Fdata-access.md` Section 2):\n- Current price, market cap, shares outstanding, beta\n- Trading multiples (P\u002FE, EV\u002FEBITDA, P\u002FS, P\u002FB)\n- Risk-free rate (for DCF)\n\nInitialize context: `context = {company_name, ticker, date, price, market_cap, firm_name, ...}`\n\n## Phase 2 — Comprehensive Data Gathering\nCalculate 8-16 quarters backward from `latest_calendar_quarter`. Pull:\n\n**Income Statement — search and pull all available:**\n- Revenue \u002F Net Sales\n- Cost of Revenue \u002F COGS\n- Gross Profit\n- Research & Development\n- Selling, General & Administrative\n- Total Operating Expenses\n- Operating Income\n- Interest Expense \u002F Income\n- Pre-tax Income\n- Tax Expense\n- Net Income\n- Diluted EPS\n- Diluted Shares Outstanding\n- EBITDA (or compute from Op Income + D&A, label \"(calc.)\")\n- D&A\n\n**Balance Sheet — search and pull all available:**\n- Cash and Equivalents\n- Short-term Investments\n- Accounts Receivable\n- Inventory\n- Total Current Assets\n- PP&E (net)\n- Goodwill\n- Total Assets\n- Accounts Payable\n- Short-term Debt\n- Long-term Debt\n- Total Liabilities\n- Total Equity\n\n**Cash Flow — search and pull all available:**\n- Operating Cash Flow\n- Capital Expenditures\n- Depreciation & Amortization\n- Acquisitions\n- Dividends Paid\n- Share Repurchases\n- Free Cash Flow (compute if not direct: OCF - CapEx, label \"(calc.)\")\n\n**Segments:**\n- Revenue by segment\n- Operating income by segment (if available)\n\n**Geographic:**\n- Revenue by geography\n\n**KPIs:**\n- All company-specific operating metrics (subscribers, units, ARPU, retention, etc.)\n\n**Guidance:**\n- All guidance series and corresponding actuals\n\n**Share Activity:**\n- Share count, buyback amounts\n\n**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.\n\nCompute margins, YoY growth rates, and ratios for each quarter.\n\n### Cost Structure & Margin Analysis\nAfter the core financial pull:\n- **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.\n- **OpEx breakdown**: Pull R&D and SG&A separately. Compute R&D % of revenue and SG&A % of revenue trends.\n- **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.\n\n## Phase 3 — Industry-Specific Deep Dive\nDetermine the company's sector and apply the relevant analysis template:\n\n- **Manufacturing\u002FIndustrial**: Bookings & backlog, book-to-bill ratio, pipeline by geography, capacity utilization\n- **SaaS\u002FTechnology**: ARR\u002FMRR trajectory, net retention rate, customer cohort analysis, RPO\u002Fdeferred revenue trends\n- **Retail\u002FConsumer**: Same-store sales, store count trajectory, traffic vs ticket decomposition, inventory health\n- **Financials\u002FBanks**: NIM trajectory, provision trends, loan growth by category, capital ratios (CET1, TCE)\n- **Healthcare\u002FPharma**: Pipeline summary (drug, indication, phase, milestone), product revenue breakdown, patent cliff timeline\n- **Energy**: Production volumes, realized pricing vs benchmark, proved reserves, breakeven analysis\n\nSearch for relevant series using `discover_company_series` with sector-appropriate keywords. Pull available data and build the narrative.\n\nBuild `context.industry_deep_dive` (string) — sector-specific analysis narrative with Daloopa citations, organized by the relevant template above.\n\n## Phase 4 — Peer Analysis\nIdentify 5-8 comparable companies.\nGet peer trading multiples using the 3-step resolution: (1) MCP market data tools if available, (2) web search, (3) sensible defaults (see `..\u002Fdata-access.md` Section 2).\nIf consensus forward estimates are available (`..\u002Fdata-access.md` Section 3), include NTM estimates.\nPull peer fundamentals from Daloopa where available (revenue growth, margins).\n\nBuild `context.comps` and `context.comps_table`.\n\n## Phase 5 — Projections\nBuild forward estimates using the following methodology:\n- **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.\n- **Gross Margin:** Mean-revert to trailing 8-quarter average, with adjustment for recent trends or guidance commentary.\n- **Operating Expenses:** Project as % of revenue, trending toward trailing averages. R&D and SG&A may have different trajectories.\n- **CapEx:** Project as % of revenue based on trailing 4-8 quarter average and guidance.\n- **D&A:** Project based on trailing average as % of revenue or PP&E.\n- **Tax Rate:** Use trailing effective tax rate or guidance.\n- **Share Count:** Project dilution\u002Fbuyback based on trailing trends and guidance.\n- **Working Capital:** Project DSO, DIO, DPO based on trailing averages.\n\nCalculate all quarterly projections, then sum to annual. Project 4-8 quarters forward. Describe methodology inline and perform calculations directly.\n\n## Phase 6 — DCF Valuation\nCalculate:\n- **WACC:** Use CAPM for cost of equity (Rf + Beta × ERP, where ERP = 6.0%). Cost of debt = Interest Expense \u002F Total Debt. WACC = (E\u002FV × Re) + (D\u002FV × Rd × (1 - Tax Rate)).\n- **5-year FCF projections:** Annualize from quarterly projections (FCF = Op Cash Flow - CapEx).\n- **Terminal Value:** Use perpetuity growth at 2.5-3.0%.\n- **Implied Share Price:** (PV of FCFs + Terminal Value - Net Debt) \u002F Shares Outstanding\n- **Sensitivity Matrix:** WACC (7 values: -3% to +3% from base) × Terminal Growth (6 values: 1.5% to 4.0%).\n\nBuild `context.dcf` and `context.dcf_summary` (set `context.has_dcf = true`).\n\n## Phase 7 — Qualitative Research + News & Catalysts\n\n### SEC Filing Research\nSearch SEC filings across multiple queries:\n- \"risk\" \u002F \"uncertainty\" \u002F \"challenge\" for risk factors\n- \"growth\" \u002F \"opportunity\" \u002F \"expansion\" for growth drivers\n- \"competition\" \u002F \"market share\" for competitive dynamics\n- \"outlook\" \u002F \"guidance\" for management's forward view\n- Company-specific strategic topics (e.g., \"AI\", \"cloud\", etc.)\n\nExtract and organize into:\n- `context.risks` — ranked list of risks with impact\u002Fprobability\n- `context.investment_thesis` — variant perception, thesis pillars, catalysts\n- `context.company_description` — 2-3 sentence business description\n\n### News & Catalysts via WebSearch\nRun 4 WebSearch queries to gather recent external context:\n1. `\"{TICKER} {company_name} news {year}\"` — recent headlines and developments\n2. `\"{TICKER} analyst upgrade downgrade price target\"` — sell-side sentiment shifts\n3. `\"{TICKER} catalysts risks\"` — forward-looking events and risk factors\n4. `\"{company_name} industry outlook {sector}\"` — macro and industry trends\n\nOrganize results into:\n- `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 \u002F Negative \u002F Mixed \u002F Upcoming). Format as a numbered list.\n\n- `context.forward_catalysts` (string) — Organized by timeframe:\n  - **Near-term (0-3 months, HIGH priority)**: earnings dates, product launches, regulatory decisions\n  - **Medium-term (3-12 months, MEDIUM priority)**: strategic milestones, contract renewals, industry events\n  - **Long-term (1-3 years, LOW priority)**: secular trends, market expansion, competitive dynamics\n\n- `context.policy_backdrop` (string) — Macro\u002Fregulatory context affecting the company. Tariffs, regulation, interest rates, sector-specific policy. Leave empty string if not material.\n\n## Phase 8 — Guidance Track Record\nSearch for guidance series (\"guidance\", \"outlook\", \"forecast\", \"estimate\", \"target\").\nPull guidance and corresponding actuals. Apply +1 quarter offset rule for quarterly guidance, same-year rule for annual guidance from Q1\u002FQ2\u002FQ3, next-year rule for annual guidance from Q4.\nCompute beat\u002Fmiss rates and patterns.\nBuild `context.guidance` and `context.guidance_table` (set `context.has_guidance = true\u002Ffalse`).\n\n## Phase 9 — What You Need to Believe\nBuild falsifiable bull\u002Fbear beliefs:\n\n### Bull Beliefs (To Go Long)\nWrite 4-6 numbered beliefs, each with:\n- One **bold statement** (the belief itself)\n- 2-3 sentences of **evidence** with Daloopa citations supporting why this could be true\n- Each belief must be **falsifiable** — testable with observable data within 6 months\n\nExample format: \"1. **Revenue growth re-accelerates to 15%+ as AI monetization scales.** Cloud segment grew [$X.Xbn](link) last quarter, up X% YoY, with management noting...\"\n\n### Bear Beliefs (To Go Short)\nSame format — 4-6 numbered falsifiable beliefs with evidence for the downside case.\n\n### Valuation Math\nFor each side:\n- Bull target: forward multiple × forward earnings estimate = price target. Show the math.\n- Bear target: same structure with bear-case multiple and earnings.\n\n### Risk\u002FReward Assessment\n- Compare bull upside % vs bear downside % from current price\n- If asymmetry is significant (e.g., 30% upside vs 40% downside), flag it explicitly\n- State which side has the better risk\u002Freward and why\n\nBuild `context.bull_beliefs`, `context.bull_target`, `context.bear_beliefs`, `context.bear_target`, `context.risk_reward_assessment`.\n\n## Phase 10 — Capital Allocation\nPull buyback, dividend, share count, FCF data.\nCompute shareholder yield, FCF payout ratio, net leverage.\nBuild `context.capital_allocation_commentary`.\n\n## Phase 11 — Synthesis + Tensions + Monitoring\nThis 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.\n\n### Core Synthesis\nWrite:\n- **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?\n- **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.\n- **Key Findings**: Top 3-5 most notable data points or trends — prioritize what changes the investment thesis, not just what's interesting\n- **Red Flags & Concerns**: Any quality-of-earnings issues, sustainability questions, or risks the market may be underpricing\n- Build `context.executive_summary`, `context.variant_perception`\n\n### Five Key Tensions\nIdentify the 5 most critical bull\u002Fbear 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.\n\nFormat as a numbered list:\n1. \"[Bullish factor] vs [Bearish factor]\" — cite the specific metric\n2. \"[Bearish factor] vs [Bullish factor]\" — cite the specific metric\n...etc.\n\nBuild `context.five_key_tensions` (string).\n\n### Monitoring Framework\nBuild two monitoring lists for ongoing tracking:\n\n**Quantitative Monitors** — 5-7 specific metrics with explicit thresholds:\n- Format: \"Metric: current value → bull threshold \u002F bear threshold\"\n- Example: \"Gross Margin: 45.2% → above 46% confirms pricing power \u002F below 43% signals cost pressure\"\n\n**Qualitative Monitors** — 5-7 factors to watch:\n- Management tone shifts on earnings calls\n- Competitive dynamics (new entrants, pricing pressure)\n- Regulatory developments\n- Customer concentration changes\n- Capital allocation pivots\n\nBuild `context.monitoring_quantitative` and `context.monitoring_qualitative` (strings, numbered lists).\n\n### Structured Tables\nBuild structured tables for both outputs:\n- `context.key_metrics_table` — [{metric, value, vs_prior}] for the exec summary table\n- `context.financials_table` — [{metric, q1, q2, ...}] for the financial analysis section\n- `context.segments_table`, `context.geo_table`, `context.shares_outstanding_table`\n- `context.opex_breakdown_table` — [{metric, q1, q2, ...}] for R&D, SG&A, % of revenue rows\n- `context.guidance_table`, `context.comps_table`, etc.\n\n## Phase 12 — Render Research Note (HTML)\n\nUsing the HTML Report Template from `..\u002Fdesign-system.md`, generate a styled HTML report with full CSS inlined. The report should include:\n\n**Header Section:**\n- Company name and ticker\n- Report date and firm attribution\n- Five Key Tensions (numbered list)\n\n**Section 1: Executive Summary**\n- Key metrics table\n- Executive summary narrative\n- Variant perception\n\n**Section 2: Company Overview**\n- Business description\n- Investment thesis\n\n**Section 3: Recent News & Catalysts**\n- News timeline\n- Forward catalysts\n- Policy backdrop\n\n**Section 4: Financial Analysis**\n- Financials table (8-16 quarters)\n- Cost structure & margin analysis\n- OpEx breakdown table\n- Segment and geographic tables\n- Share count table\n\n**Section 5: Industry-Specific Analysis**\n- Industry deep dive narrative\n\n**Section 6: Guidance Track Record**\n- Guidance table and beat\u002Fmiss analysis (if available)\n\n**Section 7: What You Need to Believe**\n- Bull beliefs with valuation target\n- Bear beliefs with valuation target\n- Risk\u002Freward assessment\n\n**Section 8: Catalysts**\n- Forward catalysts\n- Policy backdrop\n\n**Section 9: Capital Allocation**\n- Capital allocation commentary\n\n**Section 10: Valuation**\n- DCF summary and sensitivity (if available)\n- Comps commentary (if available)\n\n**Section 11: Risks**\n- Risks summary\n\n**Section 12: Monitoring Framework**\n- Quantitative monitors\n- Qualitative monitors\n\n**Appendix:**\n- Additional context or data\n\n### Context Key Checklist\nVerify these keys exist before rendering (set empty string if data unavailable):\n\n**Cover & Summary:**\n`company_name`, `ticker`, `date`, `price`, `market_cap`, `five_key_tensions`, `executive_summary`, `key_metrics_table`\n\n**Thesis & Overview:**\n`investment_thesis`, `variant_perception`, `company_description`\n\n**News:**\n`news_timeline`\n\n**Financials:**\n`financials_table`, `cost_margin_analysis`, `opex_breakdown_table`, `segments_table`, `geo_table`, `shares_outstanding_table`\n\n**Industry:**\n`industry_deep_dive`\n\n**Guidance:**\n`has_guidance`, `guidance_track_record`\n\n**What You Need to Believe:**\n`bull_beliefs`, `bull_target`, `bear_beliefs`, `bear_target`, `risk_reward_assessment`\n\n**Catalysts:**\n`forward_catalysts`, `policy_backdrop`\n\n**Capital Allocation:**\n`capital_allocation_commentary`\n\n**Valuation:**\n`has_dcf`, `dcf_summary`, `has_comps`, `comps_commentary`\n\n**Risks:**\n`risks_summary`\n\n**Monitoring:**\n`monitoring_quantitative`, `monitoring_qualitative`\n\n**Appendix:**\n`appendix_content`\n\n**Citation enforcement:** Every financial figure from Daloopa in the HTML report must use citation format: `[$X.XX million](https:\u002F\u002Fdaloopa.com\u002Fsrc\u002F{fundamental_id})`. If a number came from `get_company_fundamentals`, it must have a citation link. No exceptions.\n\n## Phase 13 — Render Excel Model\n\nGenerate the `.xlsx` file directly using the best available spreadsheet-generation workflow. For Codex, prefer bundled spreadsheet tooling or Python\u002Fopenpyxl when available. The workbook should:\n\n1. Create 8 tabs with the following structure:\n\n**Tab 1: Income Statement**\n- Rows: Revenue, COGS, Gross Profit, R&D, SG&A, Total OpEx, Op Income, Interest, Pre-Tax Income, Tax, Net Income, Diluted EPS, Shares\n- Columns: Historical periods (8-16Q) + Projected periods (4-8Q)\n- Sub-rows: YoY growth %, margin % where applicable\n- Header: Company name, ticker, report date\n- Formatting: Numbers with commas\u002Fdecimals, percentages, bold headers, frozen panes\n\n**Tab 2: Balance Sheet**\n- Rows: Assets section (Cash, Investments, AR, Inventory, Current Assets, PP&E, Goodwill, Total Assets), Liabilities section (AP, ST Debt, LT Debt, Total Liabilities, Equity)\n- Columns: Historical + Projected periods\n- Sub-rows: % of Total Assets for key line items\n- Same formatting standards\n\n**Tab 3: Cash Flow**\n- Rows: Op Cash Flow, CapEx, Free Cash Flow, Acquisitions, Dividends, Buybacks, Net Change in Cash\n- Columns: Historical + Projected periods\n- Sub-rows: FCF yield %, CapEx as % Revenue\n- Same formatting standards\n\n**Tab 4: Segments**\n- Rows: Revenue by segment, Op Income by segment (if available)\n- Columns: Historical + Projected periods\n- Sub-rows: Segment as % of total, segment growth rates\n- Same formatting standards\n\n**Tab 5: KPIs**\n- Rows: All company-specific operating metrics discovered\n- Columns: Historical + Projected periods\n- Sub-rows: YoY growth or relevant unit economics\n- Same formatting standards\n\n**Tab 6: Projections**\n- Editable assumption inputs (yellow highlighting): Revenue growth %, Gross margin %, Op margin %, CapEx % revenue, Tax rate %, Buyback rate QoQ\n- Calculated outputs: Projected P&L, BS, CF driven by assumptions\n- Commentary box explaining methodology\n- Same formatting standards\n\n**Tab 7: DCF**\n- Inputs: WACC, Terminal Growth, Risk-Free Rate, ERP, Beta, Cost of Debt\n- FCF Projection (5 years annualized)\n- Terminal Value calculation\n- PV calculations\n- Enterprise Value → Equity Value → Implied Share Price\n- Sensitivity table: WACC (rows) × Terminal Growth (cols) showing implied price\n- Color scale: green (upside) to red (downside) vs current price\n- Same formatting standards\n\n**Tab 8: Summary**\n- Company overview (name, ticker, sector, description)\n- Current market data (price, market cap, shares, beta)\n- Valuation summary: DCF implied price, peer-implied range, current price, upside\u002Fdownside %\n- Peer trading multiples table\n- Key model outputs: Trailing revenue, Projected revenue growth, Trailing\u002FProjected margins\n- Same formatting standards\n\n2. Apply `..\u002Fdesign-system.md` formatting conventions:\n- Number format: $X.Xbn for large numbers, X.X% for percentages, X.Xx for multiples\n- Color palette: Navy #1B2A4A (headers), Steel Blue #4A6FA5 (sub-headers), Gold #C5A55A (highlights), Green #27AE60 (positive), Red #C0392B (negative)\n- Bold headers, frozen top row and left column\n- Yellow fill (#FFEB3B) for editable input cells\n\n3. Save the workbook as `reports\u002F{TICKER}_model.xlsx`\n\n## Output\nPresent both deliverables to the user:\n\n**Research Note (HTML):**\n- Save the styled HTML report to `reports\u002F{TICKER}_initiate_report.html`.\n- Tell the user where the HTML file was saved and that it can be opened in a browser for full formatting.\n\n**Excel Model:**\n- Save the generated Excel model to `reports\u002F{TICKER}_model.xlsx`.\n- Tell the user where the `.xlsx` file was saved.\n- Note that yellow cells in the Projections tab are editable inputs.\n\n**Summary:**\n- 3-4 sentence executive summary\n- Key valuation range (DCF implied price + comps range)\n- Top 3 findings\n- Bull upside % vs bear downside % risk\u002Freward assessment\n\nAll financial figures must use Daloopa citation format: [$X.XX million](https:\u002F\u002Fdaloopa.com\u002Fsrc\u002F{fundamental_id})\n",{"data":37,"body":38},{"name":4,"description":6},{"type":39,"children":40},"root",[41,49,77,82,89,94,100,113,166,178,196,207,213,225,233,311,319,387,395,433,441,454,462,470,478,486,494,502,510,518,560,565,572,577,610,616,621,684,697,710,716,735,755,761,766,849,854,860,865,918,945,951,957,962,990,995,1031,1037,1042,1090,1095,1164,1170,1196,1202,1207,1213,1218,1257,1278,1284,1289,1295,1300,1313,1319,1337,1377,1383,1395,1401,1406,1412,1417,1477,1483,1488,1493,1531,1543,1549,1554,1564,1577,1587,1615,1634,1640,1645,1738,1744,1756,1764,1782,1790,1808,1816,1829,1837,1855,1863,1891,1899,1907,1915,1923,1931,1949,1957,1968,1976,1984,1992,2005,2013,2021,2029,2042,2050,2058,2064,2069,2132,2160,2174,2223,2237,2257,2299,2320,2334,2369,2383,2404,2417,2442,2448,2461,2469,2477,2505,2513,2536,2544,2565,2573,2594,2602,2623,2631,2653,2661,2703,2711,2743,2759,2782,2797,2803,2808,2816,2836,2844,2875,2883,2906],{"type":42,"tag":43,"props":44,"children":45},"element","p",{},[46],{"type":47,"value":48},"text","Initiate coverage on the company named in the user's request. If no ticker or company is provided, ask for one before proceeding.",{"type":42,"tag":43,"props":50,"children":51},{},[52,75],{"type":42,"tag":53,"props":54,"children":55},"strong",{},[56,58,65,67,73],{"type":47,"value":57},"Before starting, read ",{"type":42,"tag":59,"props":60,"children":62},"code",{"className":61},[],[63],{"type":47,"value":64},"..\u002Fdata-access.md",{"type":47,"value":66}," for data access methods and ",{"type":42,"tag":59,"props":68,"children":70},{"className":69},[],[71],{"type":47,"value":72},"..\u002Fdesign-system.md",{"type":47,"value":74}," for formatting conventions.",{"type":47,"value":76}," Follow the data access detection logic and design system throughout this skill.",{"type":42,"tag":43,"props":78,"children":79},{},[80],{"type":47,"value":81},"This is the capstone skill that produces both a research note (styled HTML) and an Excel model (.xlsx) from a single comprehensive data gathering pass.",{"type":42,"tag":83,"props":84,"children":86},"h2",{"id":85},"strategy",[87],{"type":47,"value":88},"Strategy",{"type":42,"tag":43,"props":90,"children":91},{},[92],{"type":47,"value":93},"Rather than running the research-note and build-model skills independently (which would duplicate data gathering), this skill gathers a superset of data once, then renders both outputs.",{"type":42,"tag":83,"props":95,"children":97},{"id":96},"phase-1-company-setup",[98],{"type":47,"value":99},"Phase 1 — Company Setup",{"type":42,"tag":43,"props":101,"children":102},{},[103,105,111],{"type":47,"value":104},"Look up the company by ticker using ",{"type":42,"tag":59,"props":106,"children":108},{"className":107},[],[109],{"type":47,"value":110},"discover_companies",{"type":47,"value":112},". Capture:",{"type":42,"tag":114,"props":115,"children":116},"ul",{},[117,127,145,154],{"type":42,"tag":118,"props":119,"children":120},"li",{},[121],{"type":42,"tag":59,"props":122,"children":124},{"className":123},[],[125],{"type":47,"value":126},"company_id",{"type":42,"tag":118,"props":128,"children":129},{},[130,136,138,143],{"type":42,"tag":59,"props":131,"children":133},{"className":132},[],[134],{"type":47,"value":135},"latest_calendar_quarter",{"type":47,"value":137}," — anchor for all period calculations (see ",{"type":42,"tag":59,"props":139,"children":141},{"className":140},[],[142],{"type":47,"value":64},{"type":47,"value":144}," Section 1.5)",{"type":42,"tag":118,"props":146,"children":147},{},[148],{"type":42,"tag":59,"props":149,"children":151},{"className":150},[],[152],{"type":47,"value":153},"latest_fiscal_quarter",{"type":42,"tag":118,"props":155,"children":156},{},[157,159,164],{"type":47,"value":158},"Firm name for report attribution (default: \"Daloopa\") — see ",{"type":42,"tag":59,"props":160,"children":162},{"className":161},[],[163],{"type":47,"value":64},{"type":47,"value":165}," Section 4.5",{"type":42,"tag":43,"props":167,"children":168},{},[169,171,176],{"type":47,"value":170},"Get market data using the 3-step resolution: (1) MCP market data tools if available, (2) web search, (3) sensible defaults (see ",{"type":42,"tag":59,"props":172,"children":174},{"className":173},[],[175],{"type":47,"value":64},{"type":47,"value":177}," Section 2):",{"type":42,"tag":114,"props":179,"children":180},{},[181,186,191],{"type":42,"tag":118,"props":182,"children":183},{},[184],{"type":47,"value":185},"Current price, market cap, shares outstanding, beta",{"type":42,"tag":118,"props":187,"children":188},{},[189],{"type":47,"value":190},"Trading multiples (P\u002FE, EV\u002FEBITDA, P\u002FS, P\u002FB)",{"type":42,"tag":118,"props":192,"children":193},{},[194],{"type":47,"value":195},"Risk-free rate (for DCF)",{"type":42,"tag":43,"props":197,"children":198},{},[199,201],{"type":47,"value":200},"Initialize context: ",{"type":42,"tag":59,"props":202,"children":204},{"className":203},[],[205],{"type":47,"value":206},"context = {company_name, ticker, date, price, market_cap, firm_name, ...}",{"type":42,"tag":83,"props":208,"children":210},{"id":209},"phase-2-comprehensive-data-gathering",[211],{"type":47,"value":212},"Phase 2 — Comprehensive Data Gathering",{"type":42,"tag":43,"props":214,"children":215},{},[216,218,223],{"type":47,"value":217},"Calculate 8-16 quarters backward from ",{"type":42,"tag":59,"props":219,"children":221},{"className":220},[],[222],{"type":47,"value":135},{"type":47,"value":224},". Pull:",{"type":42,"tag":43,"props":226,"children":227},{},[228],{"type":42,"tag":53,"props":229,"children":230},{},[231],{"type":47,"value":232},"Income Statement — search and pull all available:",{"type":42,"tag":114,"props":234,"children":235},{},[236,241,246,251,256,261,266,271,276,281,286,291,296,301,306],{"type":42,"tag":118,"props":237,"children":238},{},[239],{"type":47,"value":240},"Revenue \u002F Net Sales",{"type":42,"tag":118,"props":242,"children":243},{},[244],{"type":47,"value":245},"Cost of Revenue \u002F COGS",{"type":42,"tag":118,"props":247,"children":248},{},[249],{"type":47,"value":250},"Gross Profit",{"type":42,"tag":118,"props":252,"children":253},{},[254],{"type":47,"value":255},"Research & Development",{"type":42,"tag":118,"props":257,"children":258},{},[259],{"type":47,"value":260},"Selling, General & Administrative",{"type":42,"tag":118,"props":262,"children":263},{},[264],{"type":47,"value":265},"Total Operating Expenses",{"type":42,"tag":118,"props":267,"children":268},{},[269],{"type":47,"value":270},"Operating Income",{"type":42,"tag":118,"props":272,"children":273},{},[274],{"type":47,"value":275},"Interest Expense \u002F Income",{"type":42,"tag":118,"props":277,"children":278},{},[279],{"type":47,"value":280},"Pre-tax Income",{"type":42,"tag":118,"props":282,"children":283},{},[284],{"type":47,"value":285},"Tax Expense",{"type":42,"tag":118,"props":287,"children":288},{},[289],{"type":47,"value":290},"Net Income",{"type":42,"tag":118,"props":292,"children":293},{},[294],{"type":47,"value":295},"Diluted EPS",{"type":42,"tag":118,"props":297,"children":298},{},[299],{"type":47,"value":300},"Diluted Shares Outstanding",{"type":42,"tag":118,"props":302,"children":303},{},[304],{"type":47,"value":305},"EBITDA (or compute from Op Income + D&A, label \"(calc.)\")",{"type":42,"tag":118,"props":307,"children":308},{},[309],{"type":47,"value":310},"D&A",{"type":42,"tag":43,"props":312,"children":313},{},[314],{"type":42,"tag":53,"props":315,"children":316},{},[317],{"type":47,"value":318},"Balance Sheet — search and pull all available:",{"type":42,"tag":114,"props":320,"children":321},{},[322,327,332,337,342,347,352,357,362,367,372,377,382],{"type":42,"tag":118,"props":323,"children":324},{},[325],{"type":47,"value":326},"Cash and Equivalents",{"type":42,"tag":118,"props":328,"children":329},{},[330],{"type":47,"value":331},"Short-term Investments",{"type":42,"tag":118,"props":333,"children":334},{},[335],{"type":47,"value":336},"Accounts Receivable",{"type":42,"tag":118,"props":338,"children":339},{},[340],{"type":47,"value":341},"Inventory",{"type":42,"tag":118,"props":343,"children":344},{},[345],{"type":47,"value":346},"Total Current Assets",{"type":42,"tag":118,"props":348,"children":349},{},[350],{"type":47,"value":351},"PP&E (net)",{"type":42,"tag":118,"props":353,"children":354},{},[355],{"type":47,"value":356},"Goodwill",{"type":42,"tag":118,"props":358,"children":359},{},[360],{"type":47,"value":361},"Total Assets",{"type":42,"tag":118,"props":363,"children":364},{},[365],{"type":47,"value":366},"Accounts Payable",{"type":42,"tag":118,"props":368,"children":369},{},[370],{"type":47,"value":371},"Short-term Debt",{"type":42,"tag":118,"props":373,"children":374},{},[375],{"type":47,"value":376},"Long-term Debt",{"type":42,"tag":118,"props":378,"children":379},{},[380],{"type":47,"value":381},"Total Liabilities",{"type":42,"tag":118,"props":383,"children":384},{},[385],{"type":47,"value":386},"Total Equity",{"type":42,"tag":43,"props":388,"children":389},{},[390],{"type":42,"tag":53,"props":391,"children":392},{},[393],{"type":47,"value":394},"Cash Flow — search and pull all available:",{"type":42,"tag":114,"props":396,"children":397},{},[398,403,408,413,418,423,428],{"type":42,"tag":118,"props":399,"children":400},{},[401],{"type":47,"value":402},"Operating Cash Flow",{"type":42,"tag":118,"props":404,"children":405},{},[406],{"type":47,"value":407},"Capital Expenditures",{"type":42,"tag":118,"props":409,"children":410},{},[411],{"type":47,"value":412},"Depreciation & Amortization",{"type":42,"tag":118,"props":414,"children":415},{},[416],{"type":47,"value":417},"Acquisitions",{"type":42,"tag":118,"props":419,"children":420},{},[421],{"type":47,"value":422},"Dividends Paid",{"type":42,"tag":118,"props":424,"children":425},{},[426],{"type":47,"value":427},"Share Repurchases",{"type":42,"tag":118,"props":429,"children":430},{},[431],{"type":47,"value":432},"Free Cash Flow (compute if not direct: OCF - CapEx, label \"(calc.)\")",{"type":42,"tag":43,"props":434,"children":435},{},[436],{"type":42,"tag":53,"props":437,"children":438},{},[439],{"type":47,"value":440},"Segments:",{"type":42,"tag":114,"props":442,"children":443},{},[444,449],{"type":42,"tag":118,"props":445,"children":446},{},[447],{"type":47,"value":448},"Revenue by segment",{"type":42,"tag":118,"props":450,"children":451},{},[452],{"type":47,"value":453},"Operating income by segment (if available)",{"type":42,"tag":43,"props":455,"children":456},{},[457],{"type":42,"tag":53,"props":458,"children":459},{},[460],{"type":47,"value":461},"Geographic:",{"type":42,"tag":114,"props":463,"children":464},{},[465],{"type":42,"tag":118,"props":466,"children":467},{},[468],{"type":47,"value":469},"Revenue by geography",{"type":42,"tag":43,"props":471,"children":472},{},[473],{"type":42,"tag":53,"props":474,"children":475},{},[476],{"type":47,"value":477},"KPIs:",{"type":42,"tag":114,"props":479,"children":480},{},[481],{"type":42,"tag":118,"props":482,"children":483},{},[484],{"type":47,"value":485},"All company-specific operating metrics (subscribers, units, ARPU, retention, etc.)",{"type":42,"tag":43,"props":487,"children":488},{},[489],{"type":42,"tag":53,"props":490,"children":491},{},[492],{"type":47,"value":493},"Guidance:",{"type":42,"tag":114,"props":495,"children":496},{},[497],{"type":42,"tag":118,"props":498,"children":499},{},[500],{"type":47,"value":501},"All guidance series and corresponding actuals",{"type":42,"tag":43,"props":503,"children":504},{},[505],{"type":42,"tag":53,"props":506,"children":507},{},[508],{"type":47,"value":509},"Share Activity:",{"type":42,"tag":114,"props":511,"children":512},{},[513],{"type":42,"tag":118,"props":514,"children":515},{},[516],{"type":47,"value":517},"Share count, buyback amounts",{"type":42,"tag":43,"props":519,"children":520},{},[521,550,552,558],{"type":42,"tag":53,"props":522,"children":523},{},[524,526,532,534,540,542,548],{"type":47,"value":525},"For every value returned by ",{"type":42,"tag":59,"props":527,"children":529},{"className":528},[],[530],{"type":47,"value":531},"get_company_fundamentals",{"type":47,"value":533},", record its ",{"type":42,"tag":59,"props":535,"children":537},{"className":536},[],[538],{"type":47,"value":539},"fundamental_id",{"type":47,"value":541}," (the ",{"type":42,"tag":59,"props":543,"children":545},{"className":544},[],[546],{"type":47,"value":547},"id",{"type":47,"value":549}," field).",{"type":47,"value":551}," Store each data point as ",{"type":42,"tag":59,"props":553,"children":555},{"className":554},[],[556],{"type":47,"value":557},"{value, fundamental_id}",{"type":47,"value":559}," so citations can be rendered in both outputs.",{"type":42,"tag":43,"props":561,"children":562},{},[563],{"type":47,"value":564},"Compute margins, YoY growth rates, and ratios for each quarter.",{"type":42,"tag":566,"props":567,"children":569},"h3",{"id":568},"cost-structure-margin-analysis",[570],{"type":47,"value":571},"Cost Structure & Margin Analysis",{"type":42,"tag":43,"props":573,"children":574},{},[575],{"type":47,"value":576},"After the core financial pull:",{"type":42,"tag":114,"props":578,"children":579},{},[580,590,600],{"type":42,"tag":118,"props":581,"children":582},{},[583,588],{"type":42,"tag":53,"props":584,"children":585},{},[586],{"type":47,"value":587},"COGS driver identification",{"type":47,"value":589},": Search for cost-related series (\"cost of goods\", \"materials\", \"manufacturing\", \"input cost\"). Identify 3-5 biggest cost line items and their trends.",{"type":42,"tag":118,"props":591,"children":592},{},[593,598],{"type":42,"tag":53,"props":594,"children":595},{},[596],{"type":47,"value":597},"OpEx breakdown",{"type":47,"value":599},": Pull R&D and SG&A separately. Compute R&D % of revenue and SG&A % of revenue trends.",{"type":42,"tag":118,"props":601,"children":602},{},[603,608],{"type":42,"tag":53,"props":604,"children":605},{},[606],{"type":47,"value":607},"Margin driver analysis",{"type":47,"value":609},": For each major margin (gross, operating, net), identify what's driving expansion or compression — pricing power, cost leverage, mix shift, or one-time items.",{"type":42,"tag":83,"props":611,"children":613},{"id":612},"phase-3-industry-specific-deep-dive",[614],{"type":47,"value":615},"Phase 3 — Industry-Specific Deep Dive",{"type":42,"tag":43,"props":617,"children":618},{},[619],{"type":47,"value":620},"Determine the company's sector and apply the relevant analysis template:",{"type":42,"tag":114,"props":622,"children":623},{},[624,634,644,654,664,674],{"type":42,"tag":118,"props":625,"children":626},{},[627,632],{"type":42,"tag":53,"props":628,"children":629},{},[630],{"type":47,"value":631},"Manufacturing\u002FIndustrial",{"type":47,"value":633},": Bookings & backlog, book-to-bill ratio, pipeline by geography, capacity utilization",{"type":42,"tag":118,"props":635,"children":636},{},[637,642],{"type":42,"tag":53,"props":638,"children":639},{},[640],{"type":47,"value":641},"SaaS\u002FTechnology",{"type":47,"value":643},": ARR\u002FMRR trajectory, net retention rate, customer cohort analysis, RPO\u002Fdeferred revenue trends",{"type":42,"tag":118,"props":645,"children":646},{},[647,652],{"type":42,"tag":53,"props":648,"children":649},{},[650],{"type":47,"value":651},"Retail\u002FConsumer",{"type":47,"value":653},": Same-store sales, store count trajectory, traffic vs ticket decomposition, inventory health",{"type":42,"tag":118,"props":655,"children":656},{},[657,662],{"type":42,"tag":53,"props":658,"children":659},{},[660],{"type":47,"value":661},"Financials\u002FBanks",{"type":47,"value":663},": NIM trajectory, provision trends, loan growth by category, capital ratios (CET1, TCE)",{"type":42,"tag":118,"props":665,"children":666},{},[667,672],{"type":42,"tag":53,"props":668,"children":669},{},[670],{"type":47,"value":671},"Healthcare\u002FPharma",{"type":47,"value":673},": Pipeline summary (drug, indication, phase, milestone), product revenue breakdown, patent cliff timeline",{"type":42,"tag":118,"props":675,"children":676},{},[677,682],{"type":42,"tag":53,"props":678,"children":679},{},[680],{"type":47,"value":681},"Energy",{"type":47,"value":683},": Production volumes, realized pricing vs benchmark, proved reserves, breakeven analysis",{"type":42,"tag":43,"props":685,"children":686},{},[687,689,695],{"type":47,"value":688},"Search for relevant series using ",{"type":42,"tag":59,"props":690,"children":692},{"className":691},[],[693],{"type":47,"value":694},"discover_company_series",{"type":47,"value":696}," with sector-appropriate keywords. Pull available data and build the narrative.",{"type":42,"tag":43,"props":698,"children":699},{},[700,702,708],{"type":47,"value":701},"Build ",{"type":42,"tag":59,"props":703,"children":705},{"className":704},[],[706],{"type":47,"value":707},"context.industry_deep_dive",{"type":47,"value":709}," (string) — sector-specific analysis narrative with Daloopa citations, organized by the relevant template above.",{"type":42,"tag":83,"props":711,"children":713},{"id":712},"phase-4-peer-analysis",[714],{"type":47,"value":715},"Phase 4 — Peer Analysis",{"type":42,"tag":43,"props":717,"children":718},{},[719,721,726,728,733],{"type":47,"value":720},"Identify 5-8 comparable companies.\nGet peer trading multiples using the 3-step resolution: (1) MCP market data tools if available, (2) web search, (3) sensible defaults (see ",{"type":42,"tag":59,"props":722,"children":724},{"className":723},[],[725],{"type":47,"value":64},{"type":47,"value":727}," Section 2).\nIf consensus forward estimates are available (",{"type":42,"tag":59,"props":729,"children":731},{"className":730},[],[732],{"type":47,"value":64},{"type":47,"value":734}," Section 3), include NTM estimates.\nPull peer fundamentals from Daloopa where available (revenue growth, margins).",{"type":42,"tag":43,"props":736,"children":737},{},[738,739,745,747,753],{"type":47,"value":701},{"type":42,"tag":59,"props":740,"children":742},{"className":741},[],[743],{"type":47,"value":744},"context.comps",{"type":47,"value":746}," and ",{"type":42,"tag":59,"props":748,"children":750},{"className":749},[],[751],{"type":47,"value":752},"context.comps_table",{"type":47,"value":754},".",{"type":42,"tag":83,"props":756,"children":758},{"id":757},"phase-5-projections",[759],{"type":47,"value":760},"Phase 5 — Projections",{"type":42,"tag":43,"props":762,"children":763},{},[764],{"type":47,"value":765},"Build forward estimates using the following methodology:",{"type":42,"tag":114,"props":767,"children":768},{},[769,779,789,799,809,819,829,839],{"type":42,"tag":118,"props":770,"children":771},{},[772,777],{"type":42,"tag":53,"props":773,"children":774},{},[775],{"type":47,"value":776},"Revenue:",{"type":47,"value":778}," 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.",{"type":42,"tag":118,"props":780,"children":781},{},[782,787],{"type":42,"tag":53,"props":783,"children":784},{},[785],{"type":47,"value":786},"Gross Margin:",{"type":47,"value":788}," Mean-revert to trailing 8-quarter average, with adjustment for recent trends or guidance commentary.",{"type":42,"tag":118,"props":790,"children":791},{},[792,797],{"type":42,"tag":53,"props":793,"children":794},{},[795],{"type":47,"value":796},"Operating Expenses:",{"type":47,"value":798}," Project as % of revenue, trending toward trailing averages. R&D and SG&A may have different trajectories.",{"type":42,"tag":118,"props":800,"children":801},{},[802,807],{"type":42,"tag":53,"props":803,"children":804},{},[805],{"type":47,"value":806},"CapEx:",{"type":47,"value":808}," Project as % of revenue based on trailing 4-8 quarter average and guidance.",{"type":42,"tag":118,"props":810,"children":811},{},[812,817],{"type":42,"tag":53,"props":813,"children":814},{},[815],{"type":47,"value":816},"D&A:",{"type":47,"value":818}," Project based on trailing average as % of revenue or PP&E.",{"type":42,"tag":118,"props":820,"children":821},{},[822,827],{"type":42,"tag":53,"props":823,"children":824},{},[825],{"type":47,"value":826},"Tax Rate:",{"type":47,"value":828}," Use trailing effective tax rate or guidance.",{"type":42,"tag":118,"props":830,"children":831},{},[832,837],{"type":42,"tag":53,"props":833,"children":834},{},[835],{"type":47,"value":836},"Share Count:",{"type":47,"value":838}," Project dilution\u002Fbuyback based on trailing trends and guidance.",{"type":42,"tag":118,"props":840,"children":841},{},[842,847],{"type":42,"tag":53,"props":843,"children":844},{},[845],{"type":47,"value":846},"Working Capital:",{"type":47,"value":848}," Project DSO, DIO, DPO based on trailing averages.",{"type":42,"tag":43,"props":850,"children":851},{},[852],{"type":47,"value":853},"Calculate all quarterly projections, then sum to annual. Project 4-8 quarters forward. Describe methodology inline and perform calculations directly.",{"type":42,"tag":83,"props":855,"children":857},{"id":856},"phase-6-dcf-valuation",[858],{"type":47,"value":859},"Phase 6 — DCF Valuation",{"type":42,"tag":43,"props":861,"children":862},{},[863],{"type":47,"value":864},"Calculate:",{"type":42,"tag":114,"props":866,"children":867},{},[868,878,888,898,908],{"type":42,"tag":118,"props":869,"children":870},{},[871,876],{"type":42,"tag":53,"props":872,"children":873},{},[874],{"type":47,"value":875},"WACC:",{"type":47,"value":877}," Use CAPM for cost of equity (Rf + Beta × ERP, where ERP = 6.0%). Cost of debt = Interest Expense \u002F Total Debt. WACC = (E\u002FV × Re) + (D\u002FV × Rd × (1 - Tax Rate)).",{"type":42,"tag":118,"props":879,"children":880},{},[881,886],{"type":42,"tag":53,"props":882,"children":883},{},[884],{"type":47,"value":885},"5-year FCF projections:",{"type":47,"value":887}," Annualize from quarterly projections (FCF = Op Cash Flow - CapEx).",{"type":42,"tag":118,"props":889,"children":890},{},[891,896],{"type":42,"tag":53,"props":892,"children":893},{},[894],{"type":47,"value":895},"Terminal Value:",{"type":47,"value":897}," Use perpetuity growth at 2.5-3.0%.",{"type":42,"tag":118,"props":899,"children":900},{},[901,906],{"type":42,"tag":53,"props":902,"children":903},{},[904],{"type":47,"value":905},"Implied Share Price:",{"type":47,"value":907}," (PV of FCFs + Terminal Value - Net Debt) \u002F Shares Outstanding",{"type":42,"tag":118,"props":909,"children":910},{},[911,916],{"type":42,"tag":53,"props":912,"children":913},{},[914],{"type":47,"value":915},"Sensitivity Matrix:",{"type":47,"value":917}," WACC (7 values: -3% to +3% from base) × Terminal Growth (6 values: 1.5% to 4.0%).",{"type":42,"tag":43,"props":919,"children":920},{},[921,922,928,929,935,937,943],{"type":47,"value":701},{"type":42,"tag":59,"props":923,"children":925},{"className":924},[],[926],{"type":47,"value":927},"context.dcf",{"type":47,"value":746},{"type":42,"tag":59,"props":930,"children":932},{"className":931},[],[933],{"type":47,"value":934},"context.dcf_summary",{"type":47,"value":936}," (set ",{"type":42,"tag":59,"props":938,"children":940},{"className":939},[],[941],{"type":47,"value":942},"context.has_dcf = true",{"type":47,"value":944},").",{"type":42,"tag":83,"props":946,"children":948},{"id":947},"phase-7-qualitative-research-news-catalysts",[949],{"type":47,"value":950},"Phase 7 — Qualitative Research + News & Catalysts",{"type":42,"tag":566,"props":952,"children":954},{"id":953},"sec-filing-research",[955],{"type":47,"value":956},"SEC Filing Research",{"type":42,"tag":43,"props":958,"children":959},{},[960],{"type":47,"value":961},"Search SEC filings across multiple queries:",{"type":42,"tag":114,"props":963,"children":964},{},[965,970,975,980,985],{"type":42,"tag":118,"props":966,"children":967},{},[968],{"type":47,"value":969},"\"risk\" \u002F \"uncertainty\" \u002F \"challenge\" for risk factors",{"type":42,"tag":118,"props":971,"children":972},{},[973],{"type":47,"value":974},"\"growth\" \u002F \"opportunity\" \u002F \"expansion\" for growth drivers",{"type":42,"tag":118,"props":976,"children":977},{},[978],{"type":47,"value":979},"\"competition\" \u002F \"market share\" for competitive dynamics",{"type":42,"tag":118,"props":981,"children":982},{},[983],{"type":47,"value":984},"\"outlook\" \u002F \"guidance\" for management's forward view",{"type":42,"tag":118,"props":986,"children":987},{},[988],{"type":47,"value":989},"Company-specific strategic topics (e.g., \"AI\", \"cloud\", etc.)",{"type":42,"tag":43,"props":991,"children":992},{},[993],{"type":47,"value":994},"Extract and organize into:",{"type":42,"tag":114,"props":996,"children":997},{},[998,1009,1020],{"type":42,"tag":118,"props":999,"children":1000},{},[1001,1007],{"type":42,"tag":59,"props":1002,"children":1004},{"className":1003},[],[1005],{"type":47,"value":1006},"context.risks",{"type":47,"value":1008}," — ranked list of risks with impact\u002Fprobability",{"type":42,"tag":118,"props":1010,"children":1011},{},[1012,1018],{"type":42,"tag":59,"props":1013,"children":1015},{"className":1014},[],[1016],{"type":47,"value":1017},"context.investment_thesis",{"type":47,"value":1019}," — variant perception, thesis pillars, catalysts",{"type":42,"tag":118,"props":1021,"children":1022},{},[1023,1029],{"type":42,"tag":59,"props":1024,"children":1026},{"className":1025},[],[1027],{"type":47,"value":1028},"context.company_description",{"type":47,"value":1030}," — 2-3 sentence business description",{"type":42,"tag":566,"props":1032,"children":1034},{"id":1033},"news-catalysts-via-websearch",[1035],{"type":47,"value":1036},"News & Catalysts via WebSearch",{"type":42,"tag":43,"props":1038,"children":1039},{},[1040],{"type":47,"value":1041},"Run 4 WebSearch queries to gather recent external context:",{"type":42,"tag":1043,"props":1044,"children":1045},"ol",{},[1046,1057,1068,1079],{"type":42,"tag":118,"props":1047,"children":1048},{},[1049,1055],{"type":42,"tag":59,"props":1050,"children":1052},{"className":1051},[],[1053],{"type":47,"value":1054},"\"{TICKER} {company_name} news {year}\"",{"type":47,"value":1056}," — recent headlines and developments",{"type":42,"tag":118,"props":1058,"children":1059},{},[1060,1066],{"type":42,"tag":59,"props":1061,"children":1063},{"className":1062},[],[1064],{"type":47,"value":1065},"\"{TICKER} analyst upgrade downgrade price target\"",{"type":47,"value":1067}," — sell-side sentiment shifts",{"type":42,"tag":118,"props":1069,"children":1070},{},[1071,1077],{"type":42,"tag":59,"props":1072,"children":1074},{"className":1073},[],[1075],{"type":47,"value":1076},"\"{TICKER} catalysts risks\"",{"type":47,"value":1078}," — forward-looking events and risk factors",{"type":42,"tag":118,"props":1080,"children":1081},{},[1082,1088],{"type":42,"tag":59,"props":1083,"children":1085},{"className":1084},[],[1086],{"type":47,"value":1087},"\"{company_name} industry outlook {sector}\"",{"type":47,"value":1089}," — macro and industry trends",{"type":42,"tag":43,"props":1091,"children":1092},{},[1093],{"type":47,"value":1094},"Organize results into:",{"type":42,"tag":114,"props":1096,"children":1097},{},[1098,1109,1153],{"type":42,"tag":118,"props":1099,"children":1100},{},[1101,1107],{"type":42,"tag":59,"props":1102,"children":1104},{"className":1103},[],[1105],{"type":47,"value":1106},"context.news_timeline",{"type":47,"value":1108}," (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 \u002F Negative \u002F Mixed \u002F Upcoming). Format as a numbered list.",{"type":42,"tag":118,"props":1110,"children":1111},{},[1112,1118,1120],{"type":42,"tag":59,"props":1113,"children":1115},{"className":1114},[],[1116],{"type":47,"value":1117},"context.forward_catalysts",{"type":47,"value":1119}," (string) — Organized by timeframe:",{"type":42,"tag":114,"props":1121,"children":1122},{},[1123,1133,1143],{"type":42,"tag":118,"props":1124,"children":1125},{},[1126,1131],{"type":42,"tag":53,"props":1127,"children":1128},{},[1129],{"type":47,"value":1130},"Near-term (0-3 months, HIGH priority)",{"type":47,"value":1132},": earnings dates, product launches, regulatory decisions",{"type":42,"tag":118,"props":1134,"children":1135},{},[1136,1141],{"type":42,"tag":53,"props":1137,"children":1138},{},[1139],{"type":47,"value":1140},"Medium-term (3-12 months, MEDIUM priority)",{"type":47,"value":1142},": strategic milestones, contract renewals, industry events",{"type":42,"tag":118,"props":1144,"children":1145},{},[1146,1151],{"type":42,"tag":53,"props":1147,"children":1148},{},[1149],{"type":47,"value":1150},"Long-term (1-3 years, LOW priority)",{"type":47,"value":1152},": secular trends, market expansion, competitive dynamics",{"type":42,"tag":118,"props":1154,"children":1155},{},[1156,1162],{"type":42,"tag":59,"props":1157,"children":1159},{"className":1158},[],[1160],{"type":47,"value":1161},"context.policy_backdrop",{"type":47,"value":1163}," (string) — Macro\u002Fregulatory context affecting the company. Tariffs, regulation, interest rates, sector-specific policy. Leave empty string if not material.",{"type":42,"tag":83,"props":1165,"children":1167},{"id":1166},"phase-8-guidance-track-record",[1168],{"type":47,"value":1169},"Phase 8 — Guidance Track Record",{"type":42,"tag":43,"props":1171,"children":1172},{},[1173,1175,1181,1182,1188,1189,1195],{"type":47,"value":1174},"Search for guidance series (\"guidance\", \"outlook\", \"forecast\", \"estimate\", \"target\").\nPull guidance and corresponding actuals. Apply +1 quarter offset rule for quarterly guidance, same-year rule for annual guidance from Q1\u002FQ2\u002FQ3, next-year rule for annual guidance from Q4.\nCompute beat\u002Fmiss rates and patterns.\nBuild ",{"type":42,"tag":59,"props":1176,"children":1178},{"className":1177},[],[1179],{"type":47,"value":1180},"context.guidance",{"type":47,"value":746},{"type":42,"tag":59,"props":1183,"children":1185},{"className":1184},[],[1186],{"type":47,"value":1187},"context.guidance_table",{"type":47,"value":936},{"type":42,"tag":59,"props":1190,"children":1192},{"className":1191},[],[1193],{"type":47,"value":1194},"context.has_guidance = true\u002Ffalse",{"type":47,"value":944},{"type":42,"tag":83,"props":1197,"children":1199},{"id":1198},"phase-9-what-you-need-to-believe",[1200],{"type":47,"value":1201},"Phase 9 — What You Need to Believe",{"type":42,"tag":43,"props":1203,"children":1204},{},[1205],{"type":47,"value":1206},"Build falsifiable bull\u002Fbear beliefs:",{"type":42,"tag":566,"props":1208,"children":1210},{"id":1209},"bull-beliefs-to-go-long",[1211],{"type":47,"value":1212},"Bull Beliefs (To Go Long)",{"type":42,"tag":43,"props":1214,"children":1215},{},[1216],{"type":47,"value":1217},"Write 4-6 numbered beliefs, each with:",{"type":42,"tag":114,"props":1219,"children":1220},{},[1221,1233,1245],{"type":42,"tag":118,"props":1222,"children":1223},{},[1224,1226,1231],{"type":47,"value":1225},"One ",{"type":42,"tag":53,"props":1227,"children":1228},{},[1229],{"type":47,"value":1230},"bold statement",{"type":47,"value":1232}," (the belief itself)",{"type":42,"tag":118,"props":1234,"children":1235},{},[1236,1238,1243],{"type":47,"value":1237},"2-3 sentences of ",{"type":42,"tag":53,"props":1239,"children":1240},{},[1241],{"type":47,"value":1242},"evidence",{"type":47,"value":1244}," with Daloopa citations supporting why this could be true",{"type":42,"tag":118,"props":1246,"children":1247},{},[1248,1250,1255],{"type":47,"value":1249},"Each belief must be ",{"type":42,"tag":53,"props":1251,"children":1252},{},[1253],{"type":47,"value":1254},"falsifiable",{"type":47,"value":1256}," — testable with observable data within 6 months",{"type":42,"tag":43,"props":1258,"children":1259},{},[1260,1262,1267,1269,1276],{"type":47,"value":1261},"Example format: \"1. ",{"type":42,"tag":53,"props":1263,"children":1264},{},[1265],{"type":47,"value":1266},"Revenue growth re-accelerates to 15%+ as AI monetization scales.",{"type":47,"value":1268}," Cloud segment grew ",{"type":42,"tag":1270,"props":1271,"children":1273},"a",{"href":1272},"link",[1274],{"type":47,"value":1275},"$X.Xbn",{"type":47,"value":1277}," last quarter, up X% YoY, with management noting...\"",{"type":42,"tag":566,"props":1279,"children":1281},{"id":1280},"bear-beliefs-to-go-short",[1282],{"type":47,"value":1283},"Bear Beliefs (To Go Short)",{"type":42,"tag":43,"props":1285,"children":1286},{},[1287],{"type":47,"value":1288},"Same format — 4-6 numbered falsifiable beliefs with evidence for the downside case.",{"type":42,"tag":566,"props":1290,"children":1292},{"id":1291},"valuation-math",[1293],{"type":47,"value":1294},"Valuation Math",{"type":42,"tag":43,"props":1296,"children":1297},{},[1298],{"type":47,"value":1299},"For each side:",{"type":42,"tag":114,"props":1301,"children":1302},{},[1303,1308],{"type":42,"tag":118,"props":1304,"children":1305},{},[1306],{"type":47,"value":1307},"Bull target: forward multiple × forward earnings estimate = price target. Show the math.",{"type":42,"tag":118,"props":1309,"children":1310},{},[1311],{"type":47,"value":1312},"Bear target: same structure with bear-case multiple and earnings.",{"type":42,"tag":566,"props":1314,"children":1316},{"id":1315},"riskreward-assessment",[1317],{"type":47,"value":1318},"Risk\u002FReward Assessment",{"type":42,"tag":114,"props":1320,"children":1321},{},[1322,1327,1332],{"type":42,"tag":118,"props":1323,"children":1324},{},[1325],{"type":47,"value":1326},"Compare bull upside % vs bear downside % from current price",{"type":42,"tag":118,"props":1328,"children":1329},{},[1330],{"type":47,"value":1331},"If asymmetry is significant (e.g., 30% upside vs 40% downside), flag it explicitly",{"type":42,"tag":118,"props":1333,"children":1334},{},[1335],{"type":47,"value":1336},"State which side has the better risk\u002Freward and why",{"type":42,"tag":43,"props":1338,"children":1339},{},[1340,1341,1347,1349,1355,1356,1362,1363,1369,1370,1376],{"type":47,"value":701},{"type":42,"tag":59,"props":1342,"children":1344},{"className":1343},[],[1345],{"type":47,"value":1346},"context.bull_beliefs",{"type":47,"value":1348},", ",{"type":42,"tag":59,"props":1350,"children":1352},{"className":1351},[],[1353],{"type":47,"value":1354},"context.bull_target",{"type":47,"value":1348},{"type":42,"tag":59,"props":1357,"children":1359},{"className":1358},[],[1360],{"type":47,"value":1361},"context.bear_beliefs",{"type":47,"value":1348},{"type":42,"tag":59,"props":1364,"children":1366},{"className":1365},[],[1367],{"type":47,"value":1368},"context.bear_target",{"type":47,"value":1348},{"type":42,"tag":59,"props":1371,"children":1373},{"className":1372},[],[1374],{"type":47,"value":1375},"context.risk_reward_assessment",{"type":47,"value":754},{"type":42,"tag":83,"props":1378,"children":1380},{"id":1379},"phase-10-capital-allocation",[1381],{"type":47,"value":1382},"Phase 10 — Capital Allocation",{"type":42,"tag":43,"props":1384,"children":1385},{},[1386,1388,1394],{"type":47,"value":1387},"Pull buyback, dividend, share count, FCF data.\nCompute shareholder yield, FCF payout ratio, net leverage.\nBuild ",{"type":42,"tag":59,"props":1389,"children":1391},{"className":1390},[],[1392],{"type":47,"value":1393},"context.capital_allocation_commentary",{"type":47,"value":754},{"type":42,"tag":83,"props":1396,"children":1398},{"id":1397},"phase-11-synthesis-tensions-monitoring",[1399],{"type":47,"value":1400},"Phase 11 — Synthesis + Tensions + Monitoring",{"type":42,"tag":43,"props":1402,"children":1403},{},[1404],{"type":47,"value":1405},"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.",{"type":42,"tag":566,"props":1407,"children":1409},{"id":1408},"core-synthesis",[1410],{"type":47,"value":1411},"Core Synthesis",{"type":42,"tag":43,"props":1413,"children":1414},{},[1415],{"type":47,"value":1416},"Write:",{"type":42,"tag":114,"props":1418,"children":1419},{},[1420,1430,1440,1450,1460],{"type":42,"tag":118,"props":1421,"children":1422},{},[1423,1428],{"type":42,"tag":53,"props":1424,"children":1425},{},[1426],{"type":47,"value":1427},"Executive Summary",{"type":47,"value":1429},": 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?",{"type":42,"tag":118,"props":1431,"children":1432},{},[1433,1438],{"type":42,"tag":53,"props":1434,"children":1435},{},[1436],{"type":47,"value":1437},"Variant Perception",{"type":47,"value":1439},": 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.",{"type":42,"tag":118,"props":1441,"children":1442},{},[1443,1448],{"type":42,"tag":53,"props":1444,"children":1445},{},[1446],{"type":47,"value":1447},"Key Findings",{"type":47,"value":1449},": Top 3-5 most notable data points or trends — prioritize what changes the investment thesis, not just what's interesting",{"type":42,"tag":118,"props":1451,"children":1452},{},[1453,1458],{"type":42,"tag":53,"props":1454,"children":1455},{},[1456],{"type":47,"value":1457},"Red Flags & Concerns",{"type":47,"value":1459},": Any quality-of-earnings issues, sustainability questions, or risks the market may be underpricing",{"type":42,"tag":118,"props":1461,"children":1462},{},[1463,1464,1470,1471],{"type":47,"value":701},{"type":42,"tag":59,"props":1465,"children":1467},{"className":1466},[],[1468],{"type":47,"value":1469},"context.executive_summary",{"type":47,"value":1348},{"type":42,"tag":59,"props":1472,"children":1474},{"className":1473},[],[1475],{"type":47,"value":1476},"context.variant_perception",{"type":42,"tag":566,"props":1478,"children":1480},{"id":1479},"five-key-tensions",[1481],{"type":47,"value":1482},"Five Key Tensions",{"type":42,"tag":43,"props":1484,"children":1485},{},[1486],{"type":47,"value":1487},"Identify the 5 most critical bull\u002Fbear 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.",{"type":42,"tag":43,"props":1489,"children":1490},{},[1491],{"type":47,"value":1492},"Format as a numbered list:",{"type":42,"tag":1043,"props":1494,"children":1495},{},[1496,1516],{"type":42,"tag":118,"props":1497,"children":1498},{},[1499,1501,1507,1509,1514],{"type":47,"value":1500},"\"",{"type":42,"tag":1502,"props":1503,"children":1504},"span",{},[1505],{"type":47,"value":1506},"Bullish factor",{"type":47,"value":1508}," vs ",{"type":42,"tag":1502,"props":1510,"children":1511},{},[1512],{"type":47,"value":1513},"Bearish factor",{"type":47,"value":1515},"\" — cite the specific metric",{"type":42,"tag":118,"props":1517,"children":1518},{},[1519,1520,1524,1525,1529],{"type":47,"value":1500},{"type":42,"tag":1502,"props":1521,"children":1522},{},[1523],{"type":47,"value":1513},{"type":47,"value":1508},{"type":42,"tag":1502,"props":1526,"children":1527},{},[1528],{"type":47,"value":1506},{"type":47,"value":1530},"\" — cite the specific metric\n...etc.",{"type":42,"tag":43,"props":1532,"children":1533},{},[1534,1535,1541],{"type":47,"value":701},{"type":42,"tag":59,"props":1536,"children":1538},{"className":1537},[],[1539],{"type":47,"value":1540},"context.five_key_tensions",{"type":47,"value":1542}," (string).",{"type":42,"tag":566,"props":1544,"children":1546},{"id":1545},"monitoring-framework",[1547],{"type":47,"value":1548},"Monitoring Framework",{"type":42,"tag":43,"props":1550,"children":1551},{},[1552],{"type":47,"value":1553},"Build two monitoring lists for ongoing tracking:",{"type":42,"tag":43,"props":1555,"children":1556},{},[1557,1562],{"type":42,"tag":53,"props":1558,"children":1559},{},[1560],{"type":47,"value":1561},"Quantitative Monitors",{"type":47,"value":1563}," — 5-7 specific metrics with explicit thresholds:",{"type":42,"tag":114,"props":1565,"children":1566},{},[1567,1572],{"type":42,"tag":118,"props":1568,"children":1569},{},[1570],{"type":47,"value":1571},"Format: \"Metric: current value → bull threshold \u002F bear threshold\"",{"type":42,"tag":118,"props":1573,"children":1574},{},[1575],{"type":47,"value":1576},"Example: \"Gross Margin: 45.2% → above 46% confirms pricing power \u002F below 43% signals cost pressure\"",{"type":42,"tag":43,"props":1578,"children":1579},{},[1580,1585],{"type":42,"tag":53,"props":1581,"children":1582},{},[1583],{"type":47,"value":1584},"Qualitative Monitors",{"type":47,"value":1586}," — 5-7 factors to watch:",{"type":42,"tag":114,"props":1588,"children":1589},{},[1590,1595,1600,1605,1610],{"type":42,"tag":118,"props":1591,"children":1592},{},[1593],{"type":47,"value":1594},"Management tone shifts on earnings calls",{"type":42,"tag":118,"props":1596,"children":1597},{},[1598],{"type":47,"value":1599},"Competitive dynamics (new entrants, pricing pressure)",{"type":42,"tag":118,"props":1601,"children":1602},{},[1603],{"type":47,"value":1604},"Regulatory developments",{"type":42,"tag":118,"props":1606,"children":1607},{},[1608],{"type":47,"value":1609},"Customer concentration changes",{"type":42,"tag":118,"props":1611,"children":1612},{},[1613],{"type":47,"value":1614},"Capital allocation pivots",{"type":42,"tag":43,"props":1616,"children":1617},{},[1618,1619,1625,1626,1632],{"type":47,"value":701},{"type":42,"tag":59,"props":1620,"children":1622},{"className":1621},[],[1623],{"type":47,"value":1624},"context.monitoring_quantitative",{"type":47,"value":746},{"type":42,"tag":59,"props":1627,"children":1629},{"className":1628},[],[1630],{"type":47,"value":1631},"context.monitoring_qualitative",{"type":47,"value":1633}," (strings, numbered lists).",{"type":42,"tag":566,"props":1635,"children":1637},{"id":1636},"structured-tables",[1638],{"type":47,"value":1639},"Structured Tables",{"type":42,"tag":43,"props":1641,"children":1642},{},[1643],{"type":47,"value":1644},"Build structured tables for both outputs:",{"type":42,"tag":114,"props":1646,"children":1647},{},[1648,1666,1683,1706,1722],{"type":42,"tag":118,"props":1649,"children":1650},{},[1651,1657,1659,1664],{"type":42,"tag":59,"props":1652,"children":1654},{"className":1653},[],[1655],{"type":47,"value":1656},"context.key_metrics_table",{"type":47,"value":1658}," — ",{"type":42,"tag":1502,"props":1660,"children":1661},{},[1662],{"type":47,"value":1663},"{metric, value, vs_prior}",{"type":47,"value":1665}," for the exec summary table",{"type":42,"tag":118,"props":1667,"children":1668},{},[1669,1675,1676,1681],{"type":42,"tag":59,"props":1670,"children":1672},{"className":1671},[],[1673],{"type":47,"value":1674},"context.financials_table",{"type":47,"value":1658},{"type":42,"tag":1502,"props":1677,"children":1678},{},[1679],{"type":47,"value":1680},"{metric, q1, q2, ...}",{"type":47,"value":1682}," for the financial analysis section",{"type":42,"tag":118,"props":1684,"children":1685},{},[1686,1692,1693,1699,1700],{"type":42,"tag":59,"props":1687,"children":1689},{"className":1688},[],[1690],{"type":47,"value":1691},"context.segments_table",{"type":47,"value":1348},{"type":42,"tag":59,"props":1694,"children":1696},{"className":1695},[],[1697],{"type":47,"value":1698},"context.geo_table",{"type":47,"value":1348},{"type":42,"tag":59,"props":1701,"children":1703},{"className":1702},[],[1704],{"type":47,"value":1705},"context.shares_outstanding_table",{"type":42,"tag":118,"props":1707,"children":1708},{},[1709,1715,1716,1720],{"type":42,"tag":59,"props":1710,"children":1712},{"className":1711},[],[1713],{"type":47,"value":1714},"context.opex_breakdown_table",{"type":47,"value":1658},{"type":42,"tag":1502,"props":1717,"children":1718},{},[1719],{"type":47,"value":1680},{"type":47,"value":1721}," for R&D, SG&A, % of revenue rows",{"type":42,"tag":118,"props":1723,"children":1724},{},[1725,1730,1731,1736],{"type":42,"tag":59,"props":1726,"children":1728},{"className":1727},[],[1729],{"type":47,"value":1187},{"type":47,"value":1348},{"type":42,"tag":59,"props":1732,"children":1734},{"className":1733},[],[1735],{"type":47,"value":752},{"type":47,"value":1737},", etc.",{"type":42,"tag":83,"props":1739,"children":1741},{"id":1740},"phase-12-render-research-note-html",[1742],{"type":47,"value":1743},"Phase 12 — Render Research Note (HTML)",{"type":42,"tag":43,"props":1745,"children":1746},{},[1747,1749,1754],{"type":47,"value":1748},"Using the HTML Report Template from ",{"type":42,"tag":59,"props":1750,"children":1752},{"className":1751},[],[1753],{"type":47,"value":72},{"type":47,"value":1755},", generate a styled HTML report with full CSS inlined. The report should include:",{"type":42,"tag":43,"props":1757,"children":1758},{},[1759],{"type":42,"tag":53,"props":1760,"children":1761},{},[1762],{"type":47,"value":1763},"Header Section:",{"type":42,"tag":114,"props":1765,"children":1766},{},[1767,1772,1777],{"type":42,"tag":118,"props":1768,"children":1769},{},[1770],{"type":47,"value":1771},"Company name and ticker",{"type":42,"tag":118,"props":1773,"children":1774},{},[1775],{"type":47,"value":1776},"Report date and firm attribution",{"type":42,"tag":118,"props":1778,"children":1779},{},[1780],{"type":47,"value":1781},"Five Key Tensions (numbered list)",{"type":42,"tag":43,"props":1783,"children":1784},{},[1785],{"type":42,"tag":53,"props":1786,"children":1787},{},[1788],{"type":47,"value":1789},"Section 1: Executive Summary",{"type":42,"tag":114,"props":1791,"children":1792},{},[1793,1798,1803],{"type":42,"tag":118,"props":1794,"children":1795},{},[1796],{"type":47,"value":1797},"Key metrics table",{"type":42,"tag":118,"props":1799,"children":1800},{},[1801],{"type":47,"value":1802},"Executive summary narrative",{"type":42,"tag":118,"props":1804,"children":1805},{},[1806],{"type":47,"value":1807},"Variant perception",{"type":42,"tag":43,"props":1809,"children":1810},{},[1811],{"type":42,"tag":53,"props":1812,"children":1813},{},[1814],{"type":47,"value":1815},"Section 2: Company Overview",{"type":42,"tag":114,"props":1817,"children":1818},{},[1819,1824],{"type":42,"tag":118,"props":1820,"children":1821},{},[1822],{"type":47,"value":1823},"Business description",{"type":42,"tag":118,"props":1825,"children":1826},{},[1827],{"type":47,"value":1828},"Investment thesis",{"type":42,"tag":43,"props":1830,"children":1831},{},[1832],{"type":42,"tag":53,"props":1833,"children":1834},{},[1835],{"type":47,"value":1836},"Section 3: Recent News & Catalysts",{"type":42,"tag":114,"props":1838,"children":1839},{},[1840,1845,1850],{"type":42,"tag":118,"props":1841,"children":1842},{},[1843],{"type":47,"value":1844},"News timeline",{"type":42,"tag":118,"props":1846,"children":1847},{},[1848],{"type":47,"value":1849},"Forward catalysts",{"type":42,"tag":118,"props":1851,"children":1852},{},[1853],{"type":47,"value":1854},"Policy backdrop",{"type":42,"tag":43,"props":1856,"children":1857},{},[1858],{"type":42,"tag":53,"props":1859,"children":1860},{},[1861],{"type":47,"value":1862},"Section 4: Financial Analysis",{"type":42,"tag":114,"props":1864,"children":1865},{},[1866,1871,1876,1881,1886],{"type":42,"tag":118,"props":1867,"children":1868},{},[1869],{"type":47,"value":1870},"Financials table (8-16 quarters)",{"type":42,"tag":118,"props":1872,"children":1873},{},[1874],{"type":47,"value":1875},"Cost structure & margin analysis",{"type":42,"tag":118,"props":1877,"children":1878},{},[1879],{"type":47,"value":1880},"OpEx breakdown table",{"type":42,"tag":118,"props":1882,"children":1883},{},[1884],{"type":47,"value":1885},"Segment and geographic tables",{"type":42,"tag":118,"props":1887,"children":1888},{},[1889],{"type":47,"value":1890},"Share count table",{"type":42,"tag":43,"props":1892,"children":1893},{},[1894],{"type":42,"tag":53,"props":1895,"children":1896},{},[1897],{"type":47,"value":1898},"Section 5: Industry-Specific Analysis",{"type":42,"tag":114,"props":1900,"children":1901},{},[1902],{"type":42,"tag":118,"props":1903,"children":1904},{},[1905],{"type":47,"value":1906},"Industry deep dive narrative",{"type":42,"tag":43,"props":1908,"children":1909},{},[1910],{"type":42,"tag":53,"props":1911,"children":1912},{},[1913],{"type":47,"value":1914},"Section 6: Guidance Track Record",{"type":42,"tag":114,"props":1916,"children":1917},{},[1918],{"type":42,"tag":118,"props":1919,"children":1920},{},[1921],{"type":47,"value":1922},"Guidance table and beat\u002Fmiss analysis (if available)",{"type":42,"tag":43,"props":1924,"children":1925},{},[1926],{"type":42,"tag":53,"props":1927,"children":1928},{},[1929],{"type":47,"value":1930},"Section 7: What You Need to Believe",{"type":42,"tag":114,"props":1932,"children":1933},{},[1934,1939,1944],{"type":42,"tag":118,"props":1935,"children":1936},{},[1937],{"type":47,"value":1938},"Bull beliefs with valuation target",{"type":42,"tag":118,"props":1940,"children":1941},{},[1942],{"type":47,"value":1943},"Bear beliefs with valuation target",{"type":42,"tag":118,"props":1945,"children":1946},{},[1947],{"type":47,"value":1948},"Risk\u002Freward assessment",{"type":42,"tag":43,"props":1950,"children":1951},{},[1952],{"type":42,"tag":53,"props":1953,"children":1954},{},[1955],{"type":47,"value":1956},"Section 8: Catalysts",{"type":42,"tag":114,"props":1958,"children":1959},{},[1960,1964],{"type":42,"tag":118,"props":1961,"children":1962},{},[1963],{"type":47,"value":1849},{"type":42,"tag":118,"props":1965,"children":1966},{},[1967],{"type":47,"value":1854},{"type":42,"tag":43,"props":1969,"children":1970},{},[1971],{"type":42,"tag":53,"props":1972,"children":1973},{},[1974],{"type":47,"value":1975},"Section 9: Capital Allocation",{"type":42,"tag":114,"props":1977,"children":1978},{},[1979],{"type":42,"tag":118,"props":1980,"children":1981},{},[1982],{"type":47,"value":1983},"Capital allocation commentary",{"type":42,"tag":43,"props":1985,"children":1986},{},[1987],{"type":42,"tag":53,"props":1988,"children":1989},{},[1990],{"type":47,"value":1991},"Section 10: Valuation",{"type":42,"tag":114,"props":1993,"children":1994},{},[1995,2000],{"type":42,"tag":118,"props":1996,"children":1997},{},[1998],{"type":47,"value":1999},"DCF summary and sensitivity (if available)",{"type":42,"tag":118,"props":2001,"children":2002},{},[2003],{"type":47,"value":2004},"Comps commentary (if available)",{"type":42,"tag":43,"props":2006,"children":2007},{},[2008],{"type":42,"tag":53,"props":2009,"children":2010},{},[2011],{"type":47,"value":2012},"Section 11: Risks",{"type":42,"tag":114,"props":2014,"children":2015},{},[2016],{"type":42,"tag":118,"props":2017,"children":2018},{},[2019],{"type":47,"value":2020},"Risks summary",{"type":42,"tag":43,"props":2022,"children":2023},{},[2024],{"type":42,"tag":53,"props":2025,"children":2026},{},[2027],{"type":47,"value":2028},"Section 12: Monitoring Framework",{"type":42,"tag":114,"props":2030,"children":2031},{},[2032,2037],{"type":42,"tag":118,"props":2033,"children":2034},{},[2035],{"type":47,"value":2036},"Quantitative monitors",{"type":42,"tag":118,"props":2038,"children":2039},{},[2040],{"type":47,"value":2041},"Qualitative monitors",{"type":42,"tag":43,"props":2043,"children":2044},{},[2045],{"type":42,"tag":53,"props":2046,"children":2047},{},[2048],{"type":47,"value":2049},"Appendix:",{"type":42,"tag":114,"props":2051,"children":2052},{},[2053],{"type":42,"tag":118,"props":2054,"children":2055},{},[2056],{"type":47,"value":2057},"Additional context or data",{"type":42,"tag":566,"props":2059,"children":2061},{"id":2060},"context-key-checklist",[2062],{"type":47,"value":2063},"Context Key Checklist",{"type":42,"tag":43,"props":2065,"children":2066},{},[2067],{"type":47,"value":2068},"Verify these keys exist before rendering (set empty string if data unavailable):",{"type":42,"tag":43,"props":2070,"children":2071},{},[2072,2077,2083,2084,2090,2091,2097,2098,2104,2105,2111,2112,2118,2119,2125,2126],{"type":42,"tag":53,"props":2073,"children":2074},{},[2075],{"type":47,"value":2076},"Cover & Summary:",{"type":42,"tag":59,"props":2078,"children":2080},{"className":2079},[],[2081],{"type":47,"value":2082},"company_name",{"type":47,"value":1348},{"type":42,"tag":59,"props":2085,"children":2087},{"className":2086},[],[2088],{"type":47,"value":2089},"ticker",{"type":47,"value":1348},{"type":42,"tag":59,"props":2092,"children":2094},{"className":2093},[],[2095],{"type":47,"value":2096},"date",{"type":47,"value":1348},{"type":42,"tag":59,"props":2099,"children":2101},{"className":2100},[],[2102],{"type":47,"value":2103},"price",{"type":47,"value":1348},{"type":42,"tag":59,"props":2106,"children":2108},{"className":2107},[],[2109],{"type":47,"value":2110},"market_cap",{"type":47,"value":1348},{"type":42,"tag":59,"props":2113,"children":2115},{"className":2114},[],[2116],{"type":47,"value":2117},"five_key_tensions",{"type":47,"value":1348},{"type":42,"tag":59,"props":2120,"children":2122},{"className":2121},[],[2123],{"type":47,"value":2124},"executive_summary",{"type":47,"value":1348},{"type":42,"tag":59,"props":2127,"children":2129},{"className":2128},[],[2130],{"type":47,"value":2131},"key_metrics_table",{"type":42,"tag":43,"props":2133,"children":2134},{},[2135,2140,2146,2147,2153,2154],{"type":42,"tag":53,"props":2136,"children":2137},{},[2138],{"type":47,"value":2139},"Thesis & Overview:",{"type":42,"tag":59,"props":2141,"children":2143},{"className":2142},[],[2144],{"type":47,"value":2145},"investment_thesis",{"type":47,"value":1348},{"type":42,"tag":59,"props":2148,"children":2150},{"className":2149},[],[2151],{"type":47,"value":2152},"variant_perception",{"type":47,"value":1348},{"type":42,"tag":59,"props":2155,"children":2157},{"className":2156},[],[2158],{"type":47,"value":2159},"company_description",{"type":42,"tag":43,"props":2161,"children":2162},{},[2163,2168],{"type":42,"tag":53,"props":2164,"children":2165},{},[2166],{"type":47,"value":2167},"News:",{"type":42,"tag":59,"props":2169,"children":2171},{"className":2170},[],[2172],{"type":47,"value":2173},"news_timeline",{"type":42,"tag":43,"props":2175,"children":2176},{},[2177,2182,2188,2189,2195,2196,2202,2203,2209,2210,2216,2217],{"type":42,"tag":53,"props":2178,"children":2179},{},[2180],{"type":47,"value":2181},"Financials:",{"type":42,"tag":59,"props":2183,"children":2185},{"className":2184},[],[2186],{"type":47,"value":2187},"financials_table",{"type":47,"value":1348},{"type":42,"tag":59,"props":2190,"children":2192},{"className":2191},[],[2193],{"type":47,"value":2194},"cost_margin_analysis",{"type":47,"value":1348},{"type":42,"tag":59,"props":2197,"children":2199},{"className":2198},[],[2200],{"type":47,"value":2201},"opex_breakdown_table",{"type":47,"value":1348},{"type":42,"tag":59,"props":2204,"children":2206},{"className":2205},[],[2207],{"type":47,"value":2208},"segments_table",{"type":47,"value":1348},{"type":42,"tag":59,"props":2211,"children":2213},{"className":2212},[],[2214],{"type":47,"value":2215},"geo_table",{"type":47,"value":1348},{"type":42,"tag":59,"props":2218,"children":2220},{"className":2219},[],[2221],{"type":47,"value":2222},"shares_outstanding_table",{"type":42,"tag":43,"props":2224,"children":2225},{},[2226,2231],{"type":42,"tag":53,"props":2227,"children":2228},{},[2229],{"type":47,"value":2230},"Industry:",{"type":42,"tag":59,"props":2232,"children":2234},{"className":2233},[],[2235],{"type":47,"value":2236},"industry_deep_dive",{"type":42,"tag":43,"props":2238,"children":2239},{},[2240,2244,2250,2251],{"type":42,"tag":53,"props":2241,"children":2242},{},[2243],{"type":47,"value":493},{"type":42,"tag":59,"props":2245,"children":2247},{"className":2246},[],[2248],{"type":47,"value":2249},"has_guidance",{"type":47,"value":1348},{"type":42,"tag":59,"props":2252,"children":2254},{"className":2253},[],[2255],{"type":47,"value":2256},"guidance_track_record",{"type":42,"tag":43,"props":2258,"children":2259},{},[2260,2265,2271,2272,2278,2279,2285,2286,2292,2293],{"type":42,"tag":53,"props":2261,"children":2262},{},[2263],{"type":47,"value":2264},"What You Need to Believe:",{"type":42,"tag":59,"props":2266,"children":2268},{"className":2267},[],[2269],{"type":47,"value":2270},"bull_beliefs",{"type":47,"value":1348},{"type":42,"tag":59,"props":2273,"children":2275},{"className":2274},[],[2276],{"type":47,"value":2277},"bull_target",{"type":47,"value":1348},{"type":42,"tag":59,"props":2280,"children":2282},{"className":2281},[],[2283],{"type":47,"value":2284},"bear_beliefs",{"type":47,"value":1348},{"type":42,"tag":59,"props":2287,"children":2289},{"className":2288},[],[2290],{"type":47,"value":2291},"bear_target",{"type":47,"value":1348},{"type":42,"tag":59,"props":2294,"children":2296},{"className":2295},[],[2297],{"type":47,"value":2298},"risk_reward_assessment",{"type":42,"tag":43,"props":2300,"children":2301},{},[2302,2307,2313,2314],{"type":42,"tag":53,"props":2303,"children":2304},{},[2305],{"type":47,"value":2306},"Catalysts:",{"type":42,"tag":59,"props":2308,"children":2310},{"className":2309},[],[2311],{"type":47,"value":2312},"forward_catalysts",{"type":47,"value":1348},{"type":42,"tag":59,"props":2315,"children":2317},{"className":2316},[],[2318],{"type":47,"value":2319},"policy_backdrop",{"type":42,"tag":43,"props":2321,"children":2322},{},[2323,2328],{"type":42,"tag":53,"props":2324,"children":2325},{},[2326],{"type":47,"value":2327},"Capital Allocation:",{"type":42,"tag":59,"props":2329,"children":2331},{"className":2330},[],[2332],{"type":47,"value":2333},"capital_allocation_commentary",{"type":42,"tag":43,"props":2335,"children":2336},{},[2337,2342,2348,2349,2355,2356,2362,2363],{"type":42,"tag":53,"props":2338,"children":2339},{},[2340],{"type":47,"value":2341},"Valuation:",{"type":42,"tag":59,"props":2343,"children":2345},{"className":2344},[],[2346],{"type":47,"value":2347},"has_dcf",{"type":47,"value":1348},{"type":42,"tag":59,"props":2350,"children":2352},{"className":2351},[],[2353],{"type":47,"value":2354},"dcf_summary",{"type":47,"value":1348},{"type":42,"tag":59,"props":2357,"children":2359},{"className":2358},[],[2360],{"type":47,"value":2361},"has_comps",{"type":47,"value":1348},{"type":42,"tag":59,"props":2364,"children":2366},{"className":2365},[],[2367],{"type":47,"value":2368},"comps_commentary",{"type":42,"tag":43,"props":2370,"children":2371},{},[2372,2377],{"type":42,"tag":53,"props":2373,"children":2374},{},[2375],{"type":47,"value":2376},"Risks:",{"type":42,"tag":59,"props":2378,"children":2380},{"className":2379},[],[2381],{"type":47,"value":2382},"risks_summary",{"type":42,"tag":43,"props":2384,"children":2385},{},[2386,2391,2397,2398],{"type":42,"tag":53,"props":2387,"children":2388},{},[2389],{"type":47,"value":2390},"Monitoring:",{"type":42,"tag":59,"props":2392,"children":2394},{"className":2393},[],[2395],{"type":47,"value":2396},"monitoring_quantitative",{"type":47,"value":1348},{"type":42,"tag":59,"props":2399,"children":2401},{"className":2400},[],[2402],{"type":47,"value":2403},"monitoring_qualitative",{"type":42,"tag":43,"props":2405,"children":2406},{},[2407,2411],{"type":42,"tag":53,"props":2408,"children":2409},{},[2410],{"type":47,"value":2049},{"type":42,"tag":59,"props":2412,"children":2414},{"className":2413},[],[2415],{"type":47,"value":2416},"appendix_content",{"type":42,"tag":43,"props":2418,"children":2419},{},[2420,2425,2427,2433,2435,2440],{"type":42,"tag":53,"props":2421,"children":2422},{},[2423],{"type":47,"value":2424},"Citation enforcement:",{"type":47,"value":2426}," Every financial figure from Daloopa in the HTML report must use citation format: ",{"type":42,"tag":59,"props":2428,"children":2430},{"className":2429},[],[2431],{"type":47,"value":2432},"[$X.XX million](https:\u002F\u002Fdaloopa.com\u002Fsrc\u002F{fundamental_id})",{"type":47,"value":2434},". If a number came from ",{"type":42,"tag":59,"props":2436,"children":2438},{"className":2437},[],[2439],{"type":47,"value":531},{"type":47,"value":2441},", it must have a citation link. No exceptions.",{"type":42,"tag":83,"props":2443,"children":2445},{"id":2444},"phase-13-render-excel-model",[2446],{"type":47,"value":2447},"Phase 13 — Render Excel Model",{"type":42,"tag":43,"props":2449,"children":2450},{},[2451,2453,2459],{"type":47,"value":2452},"Generate the ",{"type":42,"tag":59,"props":2454,"children":2456},{"className":2455},[],[2457],{"type":47,"value":2458},".xlsx",{"type":47,"value":2460}," file directly using the best available spreadsheet-generation workflow. For Codex, prefer bundled spreadsheet tooling or Python\u002Fopenpyxl when available. The workbook should:",{"type":42,"tag":1043,"props":2462,"children":2463},{},[2464],{"type":42,"tag":118,"props":2465,"children":2466},{},[2467],{"type":47,"value":2468},"Create 8 tabs with the following structure:",{"type":42,"tag":43,"props":2470,"children":2471},{},[2472],{"type":42,"tag":53,"props":2473,"children":2474},{},[2475],{"type":47,"value":2476},"Tab 1: Income Statement",{"type":42,"tag":114,"props":2478,"children":2479},{},[2480,2485,2490,2495,2500],{"type":42,"tag":118,"props":2481,"children":2482},{},[2483],{"type":47,"value":2484},"Rows: Revenue, COGS, Gross Profit, R&D, SG&A, Total OpEx, Op Income, Interest, Pre-Tax Income, Tax, Net Income, Diluted EPS, Shares",{"type":42,"tag":118,"props":2486,"children":2487},{},[2488],{"type":47,"value":2489},"Columns: Historical periods (8-16Q) + Projected periods (4-8Q)",{"type":42,"tag":118,"props":2491,"children":2492},{},[2493],{"type":47,"value":2494},"Sub-rows: YoY growth %, margin % where applicable",{"type":42,"tag":118,"props":2496,"children":2497},{},[2498],{"type":47,"value":2499},"Header: Company name, ticker, report date",{"type":42,"tag":118,"props":2501,"children":2502},{},[2503],{"type":47,"value":2504},"Formatting: Numbers with commas\u002Fdecimals, percentages, bold headers, frozen panes",{"type":42,"tag":43,"props":2506,"children":2507},{},[2508],{"type":42,"tag":53,"props":2509,"children":2510},{},[2511],{"type":47,"value":2512},"Tab 2: Balance Sheet",{"type":42,"tag":114,"props":2514,"children":2515},{},[2516,2521,2526,2531],{"type":42,"tag":118,"props":2517,"children":2518},{},[2519],{"type":47,"value":2520},"Rows: Assets section (Cash, Investments, AR, Inventory, Current Assets, PP&E, Goodwill, Total Assets), Liabilities section (AP, ST Debt, LT Debt, Total Liabilities, Equity)",{"type":42,"tag":118,"props":2522,"children":2523},{},[2524],{"type":47,"value":2525},"Columns: Historical + Projected periods",{"type":42,"tag":118,"props":2527,"children":2528},{},[2529],{"type":47,"value":2530},"Sub-rows: % of Total Assets for key line items",{"type":42,"tag":118,"props":2532,"children":2533},{},[2534],{"type":47,"value":2535},"Same formatting standards",{"type":42,"tag":43,"props":2537,"children":2538},{},[2539],{"type":42,"tag":53,"props":2540,"children":2541},{},[2542],{"type":47,"value":2543},"Tab 3: Cash Flow",{"type":42,"tag":114,"props":2545,"children":2546},{},[2547,2552,2556,2561],{"type":42,"tag":118,"props":2548,"children":2549},{},[2550],{"type":47,"value":2551},"Rows: Op Cash Flow, CapEx, Free Cash Flow, Acquisitions, Dividends, Buybacks, Net Change in Cash",{"type":42,"tag":118,"props":2553,"children":2554},{},[2555],{"type":47,"value":2525},{"type":42,"tag":118,"props":2557,"children":2558},{},[2559],{"type":47,"value":2560},"Sub-rows: FCF yield %, CapEx as % Revenue",{"type":42,"tag":118,"props":2562,"children":2563},{},[2564],{"type":47,"value":2535},{"type":42,"tag":43,"props":2566,"children":2567},{},[2568],{"type":42,"tag":53,"props":2569,"children":2570},{},[2571],{"type":47,"value":2572},"Tab 4: Segments",{"type":42,"tag":114,"props":2574,"children":2575},{},[2576,2581,2585,2590],{"type":42,"tag":118,"props":2577,"children":2578},{},[2579],{"type":47,"value":2580},"Rows: Revenue by segment, Op Income by segment (if available)",{"type":42,"tag":118,"props":2582,"children":2583},{},[2584],{"type":47,"value":2525},{"type":42,"tag":118,"props":2586,"children":2587},{},[2588],{"type":47,"value":2589},"Sub-rows: Segment as % of total, segment growth rates",{"type":42,"tag":118,"props":2591,"children":2592},{},[2593],{"type":47,"value":2535},{"type":42,"tag":43,"props":2595,"children":2596},{},[2597],{"type":42,"tag":53,"props":2598,"children":2599},{},[2600],{"type":47,"value":2601},"Tab 5: KPIs",{"type":42,"tag":114,"props":2603,"children":2604},{},[2605,2610,2614,2619],{"type":42,"tag":118,"props":2606,"children":2607},{},[2608],{"type":47,"value":2609},"Rows: All company-specific operating metrics discovered",{"type":42,"tag":118,"props":2611,"children":2612},{},[2613],{"type":47,"value":2525},{"type":42,"tag":118,"props":2615,"children":2616},{},[2617],{"type":47,"value":2618},"Sub-rows: YoY growth or relevant unit economics",{"type":42,"tag":118,"props":2620,"children":2621},{},[2622],{"type":47,"value":2535},{"type":42,"tag":43,"props":2624,"children":2625},{},[2626],{"type":42,"tag":53,"props":2627,"children":2628},{},[2629],{"type":47,"value":2630},"Tab 6: Projections",{"type":42,"tag":114,"props":2632,"children":2633},{},[2634,2639,2644,2649],{"type":42,"tag":118,"props":2635,"children":2636},{},[2637],{"type":47,"value":2638},"Editable assumption inputs (yellow highlighting): Revenue growth %, Gross margin %, Op margin %, CapEx % revenue, Tax rate %, Buyback rate QoQ",{"type":42,"tag":118,"props":2640,"children":2641},{},[2642],{"type":47,"value":2643},"Calculated outputs: Projected P&L, BS, CF driven by assumptions",{"type":42,"tag":118,"props":2645,"children":2646},{},[2647],{"type":47,"value":2648},"Commentary box explaining methodology",{"type":42,"tag":118,"props":2650,"children":2651},{},[2652],{"type":47,"value":2535},{"type":42,"tag":43,"props":2654,"children":2655},{},[2656],{"type":42,"tag":53,"props":2657,"children":2658},{},[2659],{"type":47,"value":2660},"Tab 7: DCF",{"type":42,"tag":114,"props":2662,"children":2663},{},[2664,2669,2674,2679,2684,2689,2694,2699],{"type":42,"tag":118,"props":2665,"children":2666},{},[2667],{"type":47,"value":2668},"Inputs: WACC, Terminal Growth, Risk-Free Rate, ERP, Beta, Cost of Debt",{"type":42,"tag":118,"props":2670,"children":2671},{},[2672],{"type":47,"value":2673},"FCF Projection (5 years annualized)",{"type":42,"tag":118,"props":2675,"children":2676},{},[2677],{"type":47,"value":2678},"Terminal Value calculation",{"type":42,"tag":118,"props":2680,"children":2681},{},[2682],{"type":47,"value":2683},"PV calculations",{"type":42,"tag":118,"props":2685,"children":2686},{},[2687],{"type":47,"value":2688},"Enterprise Value → Equity Value → Implied Share Price",{"type":42,"tag":118,"props":2690,"children":2691},{},[2692],{"type":47,"value":2693},"Sensitivity table: WACC (rows) × Terminal Growth (cols) showing implied price",{"type":42,"tag":118,"props":2695,"children":2696},{},[2697],{"type":47,"value":2698},"Color scale: green (upside) to red (downside) vs current price",{"type":42,"tag":118,"props":2700,"children":2701},{},[2702],{"type":47,"value":2535},{"type":42,"tag":43,"props":2704,"children":2705},{},[2706],{"type":42,"tag":53,"props":2707,"children":2708},{},[2709],{"type":47,"value":2710},"Tab 8: Summary",{"type":42,"tag":114,"props":2712,"children":2713},{},[2714,2719,2724,2729,2734,2739],{"type":42,"tag":118,"props":2715,"children":2716},{},[2717],{"type":47,"value":2718},"Company overview (name, ticker, sector, description)",{"type":42,"tag":118,"props":2720,"children":2721},{},[2722],{"type":47,"value":2723},"Current market data (price, market cap, shares, beta)",{"type":42,"tag":118,"props":2725,"children":2726},{},[2727],{"type":47,"value":2728},"Valuation summary: DCF implied price, peer-implied range, current price, upside\u002Fdownside %",{"type":42,"tag":118,"props":2730,"children":2731},{},[2732],{"type":47,"value":2733},"Peer trading multiples table",{"type":42,"tag":118,"props":2735,"children":2736},{},[2737],{"type":47,"value":2738},"Key model outputs: Trailing revenue, Projected revenue growth, Trailing\u002FProjected margins",{"type":42,"tag":118,"props":2740,"children":2741},{},[2742],{"type":47,"value":2535},{"type":42,"tag":1043,"props":2744,"children":2746},{"start":2745},2,[2747],{"type":42,"tag":118,"props":2748,"children":2749},{},[2750,2752,2757],{"type":47,"value":2751},"Apply ",{"type":42,"tag":59,"props":2753,"children":2755},{"className":2754},[],[2756],{"type":47,"value":72},{"type":47,"value":2758}," formatting conventions:",{"type":42,"tag":114,"props":2760,"children":2761},{},[2762,2767,2772,2777],{"type":42,"tag":118,"props":2763,"children":2764},{},[2765],{"type":47,"value":2766},"Number format: $X.Xbn for large numbers, X.X% for percentages, X.Xx for multiples",{"type":42,"tag":118,"props":2768,"children":2769},{},[2770],{"type":47,"value":2771},"Color palette: Navy #1B2A4A (headers), Steel Blue #4A6FA5 (sub-headers), Gold #C5A55A (highlights), Green #27AE60 (positive), Red #C0392B (negative)",{"type":42,"tag":118,"props":2773,"children":2774},{},[2775],{"type":47,"value":2776},"Bold headers, frozen top row and left column",{"type":42,"tag":118,"props":2778,"children":2779},{},[2780],{"type":47,"value":2781},"Yellow fill (#FFEB3B) for editable input cells",{"type":42,"tag":1043,"props":2783,"children":2785},{"start":2784},3,[2786],{"type":42,"tag":118,"props":2787,"children":2788},{},[2789,2791],{"type":47,"value":2790},"Save the workbook as ",{"type":42,"tag":59,"props":2792,"children":2794},{"className":2793},[],[2795],{"type":47,"value":2796},"reports\u002F{TICKER}_model.xlsx",{"type":42,"tag":83,"props":2798,"children":2800},{"id":2799},"output",[2801],{"type":47,"value":2802},"Output",{"type":42,"tag":43,"props":2804,"children":2805},{},[2806],{"type":47,"value":2807},"Present both deliverables to the user:",{"type":42,"tag":43,"props":2809,"children":2810},{},[2811],{"type":42,"tag":53,"props":2812,"children":2813},{},[2814],{"type":47,"value":2815},"Research Note (HTML):",{"type":42,"tag":114,"props":2817,"children":2818},{},[2819,2831],{"type":42,"tag":118,"props":2820,"children":2821},{},[2822,2824,2830],{"type":47,"value":2823},"Save the styled HTML report to ",{"type":42,"tag":59,"props":2825,"children":2827},{"className":2826},[],[2828],{"type":47,"value":2829},"reports\u002F{TICKER}_initiate_report.html",{"type":47,"value":754},{"type":42,"tag":118,"props":2832,"children":2833},{},[2834],{"type":47,"value":2835},"Tell the user where the HTML file was saved and that it can be opened in a browser for full formatting.",{"type":42,"tag":43,"props":2837,"children":2838},{},[2839],{"type":42,"tag":53,"props":2840,"children":2841},{},[2842],{"type":47,"value":2843},"Excel Model:",{"type":42,"tag":114,"props":2845,"children":2846},{},[2847,2858,2870],{"type":42,"tag":118,"props":2848,"children":2849},{},[2850,2852,2857],{"type":47,"value":2851},"Save the generated Excel model to ",{"type":42,"tag":59,"props":2853,"children":2855},{"className":2854},[],[2856],{"type":47,"value":2796},{"type":47,"value":754},{"type":42,"tag":118,"props":2859,"children":2860},{},[2861,2863,2868],{"type":47,"value":2862},"Tell the user where the ",{"type":42,"tag":59,"props":2864,"children":2866},{"className":2865},[],[2867],{"type":47,"value":2458},{"type":47,"value":2869}," file was saved.",{"type":42,"tag":118,"props":2871,"children":2872},{},[2873],{"type":47,"value":2874},"Note that yellow cells in the Projections tab are editable inputs.",{"type":42,"tag":43,"props":2876,"children":2877},{},[2878],{"type":42,"tag":53,"props":2879,"children":2880},{},[2881],{"type":47,"value":2882},"Summary:",{"type":42,"tag":114,"props":2884,"children":2885},{},[2886,2891,2896,2901],{"type":42,"tag":118,"props":2887,"children":2888},{},[2889],{"type":47,"value":2890},"3-4 sentence executive summary",{"type":42,"tag":118,"props":2892,"children":2893},{},[2894],{"type":47,"value":2895},"Key valuation range (DCF implied price + comps range)",{"type":42,"tag":118,"props":2897,"children":2898},{},[2899],{"type":47,"value":2900},"Top 3 findings",{"type":42,"tag":118,"props":2902,"children":2903},{},[2904],{"type":47,"value":2905},"Bull upside % vs bear downside % risk\u002Freward assessment",{"type":42,"tag":43,"props":2907,"children":2908},{},[2909,2911],{"type":47,"value":2910},"All financial figures must use Daloopa citation format: ",{"type":42,"tag":1270,"props":2912,"children":2916},{"href":2913,"rel":2914},"https:\u002F\u002Fdaloopa.com\u002Fsrc\u002F%7Bfundamental_id%7D",[2915],"nofollow",[2917],{"type":47,"value":2918},"$X.XX million",{"items":2920,"total":3123},[2921,2942,2965,2982,2998,3017,3034,3050,3066,3080,3092,3107],{"slug":2922,"name":2922,"fn":2923,"description":2924,"org":2925,"tags":2926,"stars":2939,"repoUrl":2940,"updatedAt":2941},"prior-auth-packet-builder","build healthcare prior authorization packets","Build a concise prior authorization packet from local case files and payer policy docs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2927,2930,2933,2936],{"name":2928,"slug":2929,"type":15},"Documents","documents",{"name":2931,"slug":2932,"type":15},"Healthcare","healthcare",{"name":2934,"slug":2935,"type":15},"Insurance","insurance",{"name":2937,"slug":2938,"type":15},"Regulatory Compliance","regulatory-compliance",28169,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fopenai-agents-python","2026-04-16T05:11:39.180399",{"slug":2943,"name":2943,"fn":2944,"description":2945,"org":2946,"tags":2947,"stars":2962,"repoUrl":2963,"updatedAt":2964},"aspnet-core","build ASP.NET Core web applications","Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authentication, authorization, testing, performance, deployment, or ASP.NET Core upgrades.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2948,2951,2953,2956,2959],{"name":2949,"slug":2950,"type":15},".NET","dotnet",{"name":2952,"slug":2943,"type":15},"ASP.NET Core",{"name":2954,"slug":2955,"type":15},"Blazor","blazor",{"name":2957,"slug":2958,"type":15},"C#","csharp",{"name":2960,"slug":2961,"type":15},"Web Development","web-development",23787,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills","2026-04-12T05:07:02.819491",{"slug":2966,"name":2966,"fn":2967,"description":2968,"org":2969,"tags":2970,"stars":2962,"repoUrl":2963,"updatedAt":2981},"chatgpt-apps","build ChatGPT Apps SDK applications","Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2971,2974,2977,2980],{"name":2972,"slug":2973,"type":15},"Apps SDK","apps-sdk",{"name":2975,"slug":2976,"type":15},"ChatGPT","chatgpt",{"name":2978,"slug":2979,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-04-12T05:07:05.468097",{"slug":2983,"name":2983,"fn":2984,"description":2985,"org":2986,"tags":2987,"stars":2962,"repoUrl":2963,"updatedAt":2997},"cli-creator","build CLIs from API docs","Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read\u002Fwrite commands, return stable JSON, manage auth, and pair with a companion skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2988,2991,2994],{"name":2989,"slug":2990,"type":15},"API Development","api-development",{"name":2992,"slug":2993,"type":15},"CLI","cli",{"name":2995,"slug":2996,"type":15},"Codex","codex","2026-04-12T05:07:04.132762",{"slug":2999,"name":2999,"fn":3000,"description":3001,"org":3002,"tags":3003,"stars":2962,"repoUrl":2963,"updatedAt":3016},"cloudflare-deploy","deploy projects to Cloudflare","Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3004,3007,3010,3013],{"name":3005,"slug":3006,"type":15},"Cloudflare","cloudflare",{"name":3008,"slug":3009,"type":15},"Cloudflare Pages","cloudflare-pages",{"name":3011,"slug":3012,"type":15},"Cloudflare Workers","cloudflare-workers",{"name":3014,"slug":3015,"type":15},"Deployment","deployment","2026-04-12T05:07:14.275118",{"slug":3018,"name":3018,"fn":3019,"description":3020,"org":3021,"tags":3022,"stars":2962,"repoUrl":2963,"updatedAt":3033},"define-goal","define and set measurable project goals","Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3023,3026,3029,3030],{"name":3024,"slug":3025,"type":15},"Productivity","productivity",{"name":3027,"slug":3028,"type":15},"Project Management","project-management",{"name":88,"slug":85,"type":15},{"name":3031,"slug":3032,"type":15},"Task Management","task-management","2026-05-23T06:17:16.870838",{"slug":3035,"name":3035,"fn":3036,"description":3037,"org":3038,"tags":3039,"stars":2962,"repoUrl":2963,"updatedAt":3049},"figma","translate Figma designs into code","Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3040,3043,3045,3048],{"name":3041,"slug":3042,"type":15},"Design","design",{"name":3044,"slug":3035,"type":15},"Figma",{"name":3046,"slug":3047,"type":15},"Frontend","frontend",{"name":2978,"slug":2979,"type":15},"2026-04-12T05:06:47.939943",{"slug":3051,"name":3051,"fn":3052,"description":3053,"org":3054,"tags":3055,"stars":2962,"repoUrl":2963,"updatedAt":3065},"figma-code-connect-components","connect Figma designs to code components","Connects Figma design components to code components using Code Connect mapping tools. Use when user says \"code connect\", \"connect this component to code\", \"map this component\", \"link component to code\", \"create code connect mapping\", or wants to establish mappings between Figma designs and code implementations. For canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3056,3057,3060,3061,3062],{"name":3041,"slug":3042,"type":15},{"name":3058,"slug":3059,"type":15},"Design System","design-system",{"name":3044,"slug":3035,"type":15},{"name":3046,"slug":3047,"type":15},{"name":3063,"slug":3064,"type":15},"UI Components","ui-components","2026-05-10T05:59:52.971881",{"slug":3067,"name":3067,"fn":3068,"description":3069,"org":3070,"tags":3071,"stars":2962,"repoUrl":2963,"updatedAt":3079},"figma-create-design-system-rules","generate design system rules from Figma","Generates custom design system rules for the user's codebase. Use when user says \"create design system rules\", \"generate rules for my project\", \"set up design rules\", \"customize design system guidelines\", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3072,3073,3074,3077,3078],{"name":3041,"slug":3042,"type":15},{"name":3058,"slug":3059,"type":15},{"name":3075,"slug":3076,"type":15},"Documentation","documentation",{"name":3044,"slug":3035,"type":15},{"name":3046,"slug":3047,"type":15},"2026-05-16T06:07:47.821474",{"slug":3081,"name":3081,"fn":3082,"description":3083,"org":3084,"tags":3085,"stars":2962,"repoUrl":2963,"updatedAt":3091},"figma-implement-design","translate Figma designs into application code","Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions \"implement design\", \"generate code\", \"implement component\", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3086,3087,3088,3089,3090],{"name":3041,"slug":3042,"type":15},{"name":3044,"slug":3035,"type":15},{"name":3046,"slug":3047,"type":15},{"name":3063,"slug":3064,"type":15},{"name":2960,"slug":2961,"type":15},"2026-05-16T06:07:40.583615",{"slug":3093,"name":3093,"fn":3094,"description":3095,"org":3096,"tags":3097,"stars":2962,"repoUrl":2963,"updatedAt":3106},"hatch-pet","create animated pets for Codex","Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3098,3101,3102,3105],{"name":3099,"slug":3100,"type":15},"Animation","animation",{"name":2995,"slug":2996,"type":15},{"name":3103,"slug":3104,"type":15},"Creative","creative",{"name":3041,"slug":3042,"type":15},"2026-05-02T05:31:48.48485",{"slug":3108,"name":3108,"fn":3109,"description":3110,"org":3111,"tags":3112,"stars":2962,"repoUrl":2963,"updatedAt":3122},"imagegen","generate and edit raster images","Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG\u002Fvector\u002Fcode-native assets, extending an established icon or logo system, or building the visual directly in HTML\u002FCSS\u002Fcanvas.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3113,3114,3115,3118,3121],{"name":3103,"slug":3104,"type":15},{"name":3041,"slug":3042,"type":15},{"name":3116,"slug":3117,"type":15},"Image Generation","image-generation",{"name":3119,"slug":3120,"type":15},"Images","images",{"name":9,"slug":8,"type":15},"2026-05-15T06:23:24.312127",675,{"items":3125,"total":3238},[3126,3142,3158,3170,3188,3206,3226],{"slug":3127,"name":3127,"fn":3128,"description":3129,"org":3130,"tags":3131,"stars":25,"repoUrl":26,"updatedAt":27},"accessibility-and-inclusive-visualization","make data visualizations accessible","Make data visualizations accessible and inclusive. Use when the user needs chart or diagram accessibility guidance, text alternatives for complex visuals, color and contrast review, keyboard support, reduced-motion behavior for animation or parallax, or an accessibility QA workflow for exported figures, UML-like diagrams, and dashboards.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3132,3135,3138,3141],{"name":3133,"slug":3134,"type":15},"Accessibility","accessibility",{"name":3136,"slug":3137,"type":15},"Charts","charts",{"name":3139,"slug":3140,"type":15},"Data Visualization","data-visualization",{"name":3041,"slug":3042,"type":15},{"slug":3143,"name":3143,"fn":3144,"description":3145,"org":3146,"tags":3147,"stars":25,"repoUrl":26,"updatedAt":3157},"agent-browser","automate browser interactions for agents","Browser automation CLI for AI agents. Use when the user needs to interact with websites, verify dev server output, test web apps, navigate pages, fill forms, click buttons, take screenshots, extract data, or automate any browser task. Also triggers when a dev server starts so you can verify it visually.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3148,3151,3154],{"name":3149,"slug":3150,"type":15},"Agents","agents",{"name":3152,"slug":3153,"type":15},"Browser Automation","browser-automation",{"name":3155,"slug":3156,"type":15},"Testing","testing","2026-04-06T18:41:03.44016",{"slug":3159,"name":3159,"fn":3160,"description":3161,"org":3162,"tags":3163,"stars":25,"repoUrl":26,"updatedAt":3169},"agent-browser-verify","verify dev server output with automated browser","Automated browser verification for dev servers. Triggers when a dev server starts to run a visual gut-check with agent-browser — verifies the page loads, checks for console errors, validates key UI elements, and reports pass\u002Ffail before continuing.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3164,3165,3168],{"name":3152,"slug":3153,"type":15},{"name":3166,"slug":3167,"type":15},"Local Development","local-development",{"name":3155,"slug":3156,"type":15},"2026-04-06T18:41:17.526867",{"slug":3171,"name":3171,"fn":3172,"description":3173,"org":3174,"tags":3175,"stars":25,"repoUrl":26,"updatedAt":3187},"agents-sdk","build AI agents on Cloudflare Workers","Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3176,3177,3178,3181,3184],{"name":3149,"slug":3150,"type":15},{"name":3011,"slug":3012,"type":15},{"name":3179,"slug":3180,"type":15},"SDK","sdk",{"name":3182,"slug":3183,"type":15},"Serverless","serverless",{"name":3185,"slug":3186,"type":15},"WebSockets","websockets","2026-04-06T18:39:51.717063",{"slug":3189,"name":3189,"fn":3190,"description":3191,"org":3192,"tags":3193,"stars":25,"repoUrl":26,"updatedAt":3205},"ai-elements","build chat UIs with AI Elements","AI Elements component library guidance — pre-built React components for AI interfaces built on shadcn\u002Fui. Use when building chat UIs, message displays, tool call rendering, streaming responses, reasoning panels, or any AI-native interface with the AI SDK.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3194,3195,3198,3201,3202],{"name":3046,"slug":3047,"type":15},{"name":3196,"slug":3197,"type":15},"React","react",{"name":3199,"slug":3200,"type":15},"shadcn\u002Fui","shadcn-ui",{"name":3063,"slug":3064,"type":15},{"name":3203,"slug":3204,"type":15},"Vercel","vercel","2026-04-06T18:40:59.619419",{"slug":3207,"name":3207,"fn":3208,"description":3209,"org":3210,"tags":3211,"stars":25,"repoUrl":26,"updatedAt":3225},"ai-gateway","configure Vercel AI Gateway","Vercel AI Gateway expert guidance. Use when configuring model routing, provider failover, cost tracking, or managing multiple AI providers through a unified API.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3212,3215,3218,3221,3224],{"name":3213,"slug":3214,"type":15},"AI Infrastructure","ai-infrastructure",{"name":3216,"slug":3217,"type":15},"Cost Optimization","cost-optimization",{"name":3219,"slug":3220,"type":15},"LLM","llm",{"name":3222,"slug":3223,"type":15},"Performance","performance",{"name":3203,"slug":3204,"type":15},"2026-04-06T18:40:44.377464",{"slug":3227,"name":3227,"fn":3228,"description":3229,"org":3230,"tags":3231,"stars":25,"repoUrl":26,"updatedAt":3237},"ai-generation-persistence","implement persistence patterns for AI generations","AI generation persistence patterns — unique IDs, addressable URLs, database storage, and cost tracking for every LLM generation",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3232,3233,3236],{"name":3216,"slug":3217,"type":15},{"name":3234,"slug":3235,"type":15},"Database","database",{"name":3219,"slug":3220,"type":15},"2026-04-06T18:41:08.513425",600]