Earnings Review

Perform a comprehensive earnings analysis for the company named in the user's request. If no ticker or company is provided, ask for one before proceeding.

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

Follow these steps:

1. Company Lookup

Look up the company by ticker using discover_companies. Capture:

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

2. Core Financial Metrics

Calculate 8 quarters backward from latest_calendar_quarter. Search for these metrics, then pull:

Income Statement:

• Revenue / Net Sales
• Gross Profit
• Operating Income / EBIT
• EBITDA (if not reported, compute as Operating Income + D&A — label it "EBITDA (calc.)")
• Net Income
• Diluted EPS
• Operating Expenses (SG&A, R&D where available)

Cash Flow & Balance Sheet:

• Operating Cash Flow
• CapEx (Purchases of property, plant and equipment)
• Free Cash Flow (compute as Operating Cash Flow - CapEx — label it "FCF (calc.)")
• D&A (needed for EBITDA calc if not directly reported)

For any derived/computed metric, mark it with "(calc.)" so the reader knows it's not directly sourced.

Flag any one-time items that distort a quarter (e.g., tax charges, impairments, litigation settlements) with a footnote so YoY comparisons aren't misleading.

3. Company-Specific KPIs

First, think about what the most important KPIs are for THIS specific company based on its business model and what drives its valuation. For example:

• SaaS/cloud: ARR, net revenue retention, RPO/cRPO, customers >$100K
• Consumer tech: DAU/MAU, ARPU, engagement metrics, installed base, paid subscribers
• E-commerce/marketplace: GMV, take rate, active buyers/sellers, order frequency
• Retail: same-store sales, store count, average ticket, transactions
• Telecom/media: subscribers, churn, ARPU, content spend
• Hardware: units shipped, ASP, attach rate
• Financial services: AUM, NIM, loan growth, credit quality metrics
• Pharma/biotech: pipeline stage, patient starts, scripts, market share

Then search for those specific KPIs by name, plus cast a wider net for anything else available. Also search for:

• Segment/product revenue breakdown
• Geographic revenue breakdown

Pull for the same 8-quarter period. If some KPIs only have data for recent quarters, include what's available and note the gap.

4. Growth & Margins

Calculate and present:

• YoY revenue growth for each of the last 4 quarters (not just one)
• Gross margin, operating margin, EBITDA margin, net margin trends over 8 quarters
• EPS growth YoY for each of the last 4 quarters
• Segment revenue YoY growth for the most recent quarter
• Geographic revenue YoY growth for the most recent quarter
• KPI growth rates where applicable

If the company has strong seasonality (e.g., retail Q4 holiday, back-to-school, cyclical patterns), add a note so the reader interprets QoQ swings correctly.

4.5. Cost Structure & Margin Drivers

Decompose what's driving margin trends. This turns the margin table from Section 4 into an analytical narrative.

COGS Analysis:

• Pull product COGS and services COGS (or equivalent cost breakdown) if available
• Identify the 3-5 biggest cost line items and their YoY trends
• Is COGS growing faster or slower than revenue? If slower, what's driving the efficiency — input costs, mix shift, pricing power, or scale leverage?

OpEx Breakdown:

• Pull R&D and SG&A separately for the last 8 quarters
• Compute R&D % of revenue and SG&A % of revenue trends
• Is the company investing more in R&D (growth mode) or cutting SG&A (efficiency mode)? Both? Neither?
• Flag any quarter where OpEx growth materially exceeds revenue growth — that's operating deleverage

Margin Driver Synthesis: For each major margin (gross, operating, net), write 1-2 sentences identifying what's driving expansion or compression:

• Pricing power vs cost inflation
• Mix shift (higher-margin products/services growing faster)
• Scale leverage vs investment spending
• One-time items distorting the trend
• FX impact if material

Include this as a commentary block after the margins table in the report. Cite specific Daloopa figures.

5. Guidance vs Actuals

Search for guidance series (revenue guidance, EPS guidance, margin guidance, OpEx guidance, any KPI guidance). If available:

• Pull guidance and actual results
• CRITICAL: Apply +1 quarter offset — guidance from Q(N) applies to Q(N+1) results
• Calculate beat/miss amounts and percentages
• Note patterns (consistent beats, narrows, etc.)
• If the company provides directional guidance (e.g., "low-to-mid-teens growth") rather than hard numbers, note this and compare against the actual growth rate

If no formal guidance series exist, note that the company does not provide quantitative guidance.

6. Consensus Context (if available)

If consensus estimates are available (see ../data-access.md Section 3), add:

• Consensus revenue and EPS vs actual results — beat/miss vs Street
• Estimate revision trends (are estimates moving up or down?)
• Note the source of consensus data used

If consensus data is not available, skip this section and note "consensus data not available."

7. Management Commentary

Search SEC filings/documents for management commentary. Try multiple searches to get broad coverage:

• First search: "results" or "record" for earnings highlights
• Second search: "outlook" or "guidance" for forward-looking commentary
• Third search: strategy-specific terms relevant to the company (e.g., "AI", "cloud", "subscribers")
• If a search returns empty, try broader single-keyword searches before giving up

Extract:

• Earnings results and key drivers
• Forward outlook and guidance language
• Segment performance highlights
• Any notable call-outs (one-time items, macro commentary, strategic updates)
• Direct management quotes where available (with document citations)

7.5. News Context & Stock Reaction

Stock price reaction (from Daloopa): Use get_stock_prices (see ../data-access.md Section 1.7) to get the actual post-earnings price move. Pull prices for a window around the earnings date: start_date = 1 trading day before the likely earnings date (estimate from the latest_calendar_quarter end + ~30-45 days), end_date = 3 trading days after. Compute the next-day percentage change from the pre-earnings close to the post-earnings close. This gives you the hard number for "how did the stock react."

Also pull the current stock price (3 most recent calendar days) so the report includes where the stock trades NOW relative to the post-earnings reaction.

Web search for context: Run 2 WebSearch queries to add external context around the earnings:

1. "{TICKER} {company_name} earnings {latest_quarter} {year}" — coverage and analyst reactions
2. "{TICKER} analyst price target {year}" — sell-side sentiment

Source quality (MANDATORY): Follow ../data-access.md Section 2.5 — cite only primary sources (SEC filings, IR pages, press releases, transcripts) and Tier-1 financial press (Reuters, Bloomberg, WSJ, FT). Never use or cite Yahoo Finance editorial, Benzinga, Seeking Alpha, Motley Fool, Zacks, TipRanks, StockTwits, Reddit, or similar aggregators/blogs.

Distill into a brief Earnings Context block (3-5 bullet points):

• How did the stock react to earnings? (use the actual price data from get_stock_prices, not just search results)
• What were the key analyst takeaways or debates?
• Any price target changes or rating changes post-earnings?
• Any macro/industry context that affected the quarter?

Keep this concise — it supplements the Daloopa data with market reaction context. Include it as a short section in the report before the Forward Outlook.

7.6. Forward Outlook & Revenue Drivers

Synthesize the backward-looking data into a forward-looking view. This section turns the earnings analysis from "what happened" into "what it means for the future."

Forward Guidance Analysis:

• What is management guiding for NEXT quarter and/or full year? Extract specific numbers (revenue range, EPS range, margin targets, CapEx plans).
• Is the guide conservative or aggressive? Compare to: (a) the company's historical beat rate from Section 5, (b) the current run rate extrapolated forward, (c) consensus if available. A company that beats by 3% every quarter and guides flat is sandbagging; a company that guides for acceleration after 3 quarters of deceleration is aggressive.
• How does forward guidance compare to trailing trends? If revenue grew +8% YoY last quarter and guidance implies +5%, is management signaling deceleration or being conservative?

Revenue Driver Decomposition:

• Break down what's driving growth: volume vs price vs mix. Which segments are contributing vs dragging?
• For each major segment, identify the unit economics driver: units x ASP, subscribers x ARPU, GMV x take rate, etc.
• What has to happen for current growth rates to sustain? If growth is coming from price increases, is there a ceiling? If from volume, is the TAM expanding or saturating?

KPI Trajectory Implications:

• Connect KPI trends to revenue outlook. If subscriber growth is decelerating, what does that imply for next quarter's revenue? If ASPs are rising but units are flat, is that sustainable?
• If backlog/RPO/deferred revenue is building, when does it convert to recognized revenue? If it's declining, that's a leading indicator of future revenue pressure.
• Flag any KPI-to-revenue divergences (e.g., user growth accelerating but ARPU declining — net effect on revenue?)

Trend Synthesis:

• Looking at the last 4-8 quarters holistically — is this company accelerating, decelerating, or at a plateau?
• What's the single most important metric to watch next quarter? Why?
• Are operating KPIs leading or lagging the financial results?

Risks to the Forward View:

• What could go wrong with the guidance? What assumptions are embedded that could break?
• Identify the 2-3 biggest risks to the forward trajectory: competitive threats, macro sensitivity, product cycle dependency, regulatory risk, customer concentration.
• If the bull case requires multiple things to go right simultaneously, flag that explicitly.

7.7. Read-Throughs & Competitive Implications

This is one of the most valuable sections of the report. Every company's earnings contain signal about adjacent companies — suppliers, customers, competitors, and the broader industry. An analyst covering a sector doesn't just read one company's print; they read it for what it says about every other name in their portfolio.

Identify the Read-Through Universe: Think about who is most affected by this company's results. Consider:

• Suppliers: If this company's revenue/COGS/CapEx changed materially, which suppliers feel it? (e.g., AAPL iPhone strength → TSMC, Broadcom, Corning benefit; AAPL CapEx guidance up → supplier order books filling)
• Customers: If this company is a major input to others, what do its pricing/volume trends imply? (e.g., TSMC price increases → margin pressure for AAPL, AMD, NVDA)
• Direct competitors: How does this quarter compare to what peers have reported or guided? Is this company gaining or losing share? (e.g., MSFT cloud growth accelerating while AMZN AWS decelerates → share shift)
• Indirect competitors / substitutes: Any signals about demand shifting between categories? (e.g., strong enterprise software spend → weak services/consulting spend)
• Industry bellwether signals: If this is a large company, what do its results say about the macro/sector? (e.g., consumer discretionary weakness at WMT → read-through to all retail)

For each read-through (aim for 5-8), state:

1. The affected company (ticker + name)
2. The specific data point from this earnings that creates the read-through — cite the Daloopa figure
3. The implication — bullish or bearish for the adjacent company, and why
4. Confidence level — is this a direct/disclosed relationship (high confidence) or an inferred/estimated one (moderate)?

Example read-throughs:

• "AAPL Services revenue grew +14% YoY to $26.3B → Positive for APP (AppLovin): Apple's App Store is a major distribution channel; growing Services revenue confirms healthy app ecosystem spending. Negative for GOOG: AAPL's growing services monetization strengthens their negotiating leverage on the Google TAC agreement."
• "TSMC guided CapEx up 25% YoY → Positive for ASML, AMAT, LRCX, KLAC: equipment spend is the most direct read-through to semicap names. ASML in particular given EUV concentration."
• "NFLX added 19M subscribers vs 13M expected → Negative for DIS, WBD, PARA: In a zero-sum attention economy, NFLX's accelerating sub growth likely came partly at the expense of other streamers."

Sequencing context:

• Note whether this company reported before or after its peers this earnings season. If it's early in the cycle, the read-throughs are forward-looking predictions. If it's late, compare against what peers already reported — confirm or contradict the emerging narrative.
• If a peer has already reported, note any divergence: "MSFT reported cloud growth of +29% last week; today's AMZN AWS at +19% confirms the share shift narrative."

Web research for validation: Run 1-2 targeted searches to validate read-throughs:

• "{TICKER} earnings read through implications {year}" — analyst commentary on cross-company signals
• "{TICKER} {peer_ticker} competitive positioning {year}" — specific competitive dynamics

Present as a structured list in the report, grouped by relationship type (Suppliers / Customers / Competitors / Industry). Each read-through should be a concise 2-3 sentence paragraph with the data citation, the affected name, and the implication.

8. Save Report

Save to reports/{TICKER}_earnings_{PERIOD}.html (where PERIOD is the most recent quarter analyzed) using the HTML report template from ../design-system.md. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.

The report should include:

• Executive summary (2-3 sentence overview of the quarter + 2-3 most notable findings)
• Core financial metrics table (8 quarters, periods as columns, metrics as rows, including FCF)
• Segment and geographic revenue breakdown tables
• KPI table (with notes on any data gaps)
• Margin trends table (8 quarters)
• Cost structure & margin driver commentary (after margins table)
• YoY growth rates table (last 4 quarters, showing each quarter's YoY)
• Guidance vs actuals table (if applicable) with pattern analysis
• News context (analyst reactions, price target changes, market sentiment)
• Forward outlook and revenue drivers analysis
• Management commentary with direct quotes and document citations
• Read-throughs & competitive implications (grouped by Suppliers / Customers / Competitors / Industry)
• Seasonality note if applicable

All financial figures must use Daloopa citation format: <a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>

Tell the user where the HTML report was saved.

Highlight the 2-3 most notable findings with a critical lens:

• Quality of earnings: Are the beats sustainable or driven by one-time items, favorable timing, or accounting changes? Is revenue growth real or pulled forward?
• Red flags: Any deterioration in cash conversion, growing GAAP vs non-GAAP gaps, rising SBC dilution, margin expansion from under-investment?
• What the market is missing: What does the data say that consensus might not be pricing in — positive or negative?