[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-openai-earnings-prep":3,"mdc-3kk0ur-key":36,"related-repo-openai-earnings-prep":1604,"related-org-openai-earnings-prep":1727},{"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},"earnings-prep","prepare pre-earnings analysis reports","Pre-earnings preparation report for the night before a company reports",{"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},"Reporting","reporting",{"name":20,"slug":21,"type":15},"Finance","finance",{"name":23,"slug":24,"type":15},"Investment Banking","investment-banking",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\u002Fearnings-prep","---\nname: earnings-prep\ndescription: Pre-earnings preparation report for the night before a company reports\n---\n\nGenerate a pre-earnings preparation report for the company specified by the user named in the user's request. If no ticker or company is provided, ask for one before proceeding.\n\nThis is the note a L\u002FS equity analyst reads the night before a company reports — it tells them exactly what to focus on when the print drops.\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\nFollow these steps:\n\n## 1. Company Lookup\nLook up the company by ticker using `discover_companies`. Capture:\n- `company_id`\n- `latest_calendar_quarter` — anchor for all period calculations below (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\nDetermine the **upcoming quarter** — the one AFTER `latest_calendar_quarter`. This is the quarter the company is about to report. All analysis is oriented around preparing the analyst for this print.\n\n## 2. Last Quarter Recap\nPull the most recent quarter's full financials from Daloopa. Calculate 4 quarters backward from `latest_calendar_quarter` (for YoY context).\n\n**Pull:**\n- Revenue, Gross Profit, Operating Income, EBITDA, Net Income, Diluted EPS\n- Operating Cash Flow, CapEx, FCF (calc.)\n- Segment\u002Fproduct revenue breakdown\n- Company-specific KPIs (use the business-model taxonomy: SaaS → ARR\u002FNRR\u002FRPO; Consumer → DAU\u002FARPU; E-commerce → GMV\u002Ftake rate; etc.)\n\n**Summarize the story of last quarter in 3-5 bullets:**\n- What beat expectations (guidance or consensus)?\n- What missed or disappointed?\n- What was the stock reaction? (use `get_stock_prices` per `..\u002Fdata-access.md` Section 1.7 to get the actual next-day move; supplement with WebSearch for narrative context if needed)\n- What narrative emerged from the call? (e.g., \"AI monetization acceleration,\" \"margin expansion story intact,\" \"consumer weakness\")\n- What was the single most debated metric?\n\nThis is the baseline everyone on the upcoming call will be anchoring to.\n\n## 3. Outstanding Guidance for Upcoming Quarter\nSearch for ALL guidance series using keywords: \"guidance\", \"outlook\", \"estimate\", \"forecast\", \"target\". Apply the +1 quarter offset to identify which guidance applies to the upcoming print:\n- CRITICAL: Guidance from Q(N) earnings call applies to Q(N+1) results\n- The guidance issued during the `latest_calendar_quarter` earnings call is what applies to the upcoming quarter\n\n**Pull and present:**\n- Revenue guidance (point estimate or range)\n- EPS guidance\n- Margin guidance (gross, operating, EBITDA)\n- CapEx guidance\n- Segment-level guidance (if available)\n- KPI guidance (subscriber adds, unit volumes, ARPU targets, etc.)\n\n**Search filings for directional\u002Fqualitative guidance:**\n- Search documents for: \"expect\", \"anticipate\", \"similar to\", \"consistent with\"\n- Search documents for: \"low single digit\", \"mid single digit\", \"double digit\", \"sequential\"\n- Search documents for: \"headwind\", \"tailwind\", \"conservatively\", \"assumes\"\n- Capture exact management quotes with document citations\n\n**Flag any guidance updates between quarters:**\n- Search for \"pre-announce\", \"update\", \"revise\" in the most recent quarter's filings\n- Check if the company issued an 8-K updating guidance after the last earnings call\n\nPresent all guidance in a single table: Metric | Guidance Value | Source Quarter | Type (Quantitative\u002FDirectional).\n\n## 4. Guidance Credibility & Whisper Number\nThis section MUST be built entirely from Daloopa data — guidance series AND actual result series pulled via `get_company_fundamentals`. Do not use web search or estimates for this analysis.\n\n**Step 1: Pull 8 quarters of guidance data.**\nYou already discovered guidance series in Section 3. Now pull ALL of those guidance series for the last 8 quarters (from `latest_calendar_quarter` backward). These are the guidance values management provided each quarter.\n\n**Step 2: Pull 8 quarters of corresponding actuals.**\nFor every guided metric, identify the corresponding actual result series (e.g., if there is a \"Revenue guidance\" series, pull the actual \"Revenue\" series). Pull these actuals for the same 8-quarter period.\n\n**Step 3: Build the complete beat\u002Fmiss table.**\nApply the +1 quarter offset: guidance from Q(N) is compared to the actual result in Q(N+1). For EVERY quarter where both a guidance value and a corresponding actual exist, compute:\n- Guidance value (midpoint if range)\n- Actual value\n- Delta (Actual - Guidance midpoint)\n- Beat\u002FMiss % ((Actual - Guidance midpoint) \u002F |Guidance midpoint| × 100)\n- Classification: Beat \u002F In-line \u002F Miss (use +\u002F-1% threshold for in-line)\n\n**Present a FULL detail table — every quarter, every guided metric.** This is the core analytical engine of the whisper number. Do not summarize or abbreviate — show all rows. Format:\n\n| Guidance Source Qtr | Metric | Guidance (Mid) | Actual Qtr | Actual | Delta | Beat\u002FMiss % |\n\nIf a company provides range guidance (low\u002Fhigh), show the midpoint and note the range width. If a company only provides directional guidance for some metrics (e.g., \"revenue growth in low teens\"), convert to an implied numeric value for comparison (e.g., 12-13% → midpoint ~12.5% applied to prior year actual).\n\n**Step 4: Compute summary statistics from the detail table:**\n- Beat rate per metric (% of quarters where actual > guidance midpoint)\n- Average beat magnitude per metric (in absolute terms and %)\n- Beat pattern trend: is the beat getting larger (sandbagging increasing), shrinking (guidance getting more accurate), or volatile? Look at the last 4 vs. prior 4.\n- Range width trend: is management tightening or widening guidance ranges?\n\n**Step 5: Calculate the implied \"whisper number\":**\n- Whisper = Current guidance midpoint + Average historical beat (from the detail table above)\n- This is the REAL bar the stock is trading against, not the stated guidance\n- If the company beats by 2% on average, the market expects a 2% beat — an in-line result to guidance is effectively a miss\n- Calculate whisper for EVERY guided metric, not just revenue\n\n**Present the whisper summary:**\n| Metric | Current Guidance (Mid) | Avg Historical Beat | Implied Whisper | Beat Rate (n\u002FN) |\n\n**Credibility verdict:** Is management's guidance informative (tight, accurate) or performative (always sandbagged, uninformative)? If the beat rate is >90%, say so — it means the guidance number is a floor, not a forecast. If the beat magnitude is increasing, management is becoming MORE conservative over time.\n\n## 5. Peer & Adjacent Company Read-Throughs\nThis is the most differentiated section. For companies in the same sector that have ALREADY reported this earnings season, their results contain direct signal about the upcoming print.\n\n**Identify the read-through universe (aim for 5-8 companies):**\n- **Competitors**: Direct rivals in the same market\n- **Suppliers**: Companies that sell to the target company\n- **Customers**: Companies that buy from the target company\n- **Industry bellwethers**: Large companies whose results signal sector trends\n\n**CRITICAL: Always use Daloopa as the primary data source for peer analysis.** For each peer:\n\n1. **Look up the peer in Daloopa:** `discover_companies` with the peer's ticker. If Daloopa has the company, check `latest_calendar_quarter` to determine whether they have already reported the relevant quarter.\n2. **If the peer has data for the current earnings season quarter:** Pull their financials from Daloopa (`discover_company_series` → `get_company_fundamentals`). Focus on 2-4 metrics most relevant to the read-through (e.g., for a supplier: revenue, segment breakdown, inventory; for a competitor: revenue growth, market share proxies, pricing commentary).\n3. **Search the peer's filings in Daloopa:** `search_documents` with keywords related to the target company's products, markets, or industry (e.g., for an Apple supplier, search for \"Apple\", \"smartphone\", \"consumer electronics\").\n4. **Use WebSearch only to supplement Daloopa data** — for earnings-season timing confirmation, stock price reactions, or analyst commentary that Daloopa filings don't cover.\n\n**For each read-through, extract (with Daloopa citations):**\n1. **The specific data point** — the peer's metric that creates signal. Cite the Daloopa `fundamental_id`.\n2. **The implication** — bullish or bearish for the target company, and why\n3. **Confidence level** — High (direct disclosed relationship), Moderate (inferred from industry), Low (circumstantial)\n\n**For peers that haven't reported yet:** Note them as \"reports after {TICKER}\" — their results will be a read-through in the opposite direction.\n\n**Group read-throughs by:**\n- **Competitors** — share shift signals, pricing environment, demand trends\n- **Suppliers** — order book signals, inventory levels, capacity commentary\n- **Customers** — demand signals, inventory destocking\u002Frestocking, spending priorities\n- **Industry Bellwethers** — macro\u002Fsector health, end-market demand\n\n**Web research for sector context (supplementary only — after Daloopa pulls):**\n- Search: `\"{TICKER} sector earnings season {year} read through\"` — analyst commentary on cross-company signals\n- Search: `\"{TICKER} competitors results {upcoming_quarter_label} {year}\"` — what peers have already signaled\n\n## 6. Key Metrics to Watch\nIdentify the 5-7 metrics the analyst should focus on when the print drops. For each metric:\n\n| Metric | Current Level | Guidance\u002FExpected | Bullish Threshold | Bearish Threshold | Why It Matters |\n\n**Be specific with thresholds** — not \"revenue growth\" but \"revenue above $95B signals iPhone cycle acceleration; below $92B confirms China weakness.\" Not \"margins\" but \"gross margin above 47% confirms services mix shift; below 45% signals hardware pricing pressure.\"\n\n**Prioritize by information value:**\n1. Metrics where guidance has been vague or directional (highest uncertainty)\n2. Metrics where peer read-throughs are conflicting (the print will resolve the debate)\n3. Metrics that drive the forward multiple (the ones the market will re-rate on)\n4. KPIs that lead revenue by 1-2 quarters (predictive of next quarter's financials)\n\n## 7. Consensus & Positioning\nGather available consensus context:\n\n**From data sources (consensus estimates if available per `..\u002Fdata-access.md` Section 3):**\n- Consensus revenue and EPS for the upcoming quarter\n- Number of analysts at Buy \u002F Hold \u002F Sell\n- Consensus price target (median and range)\n- Recent estimate revision trends (last 30\u002F60\u002F90 days — moving up or down?)\n\n**From web search (supplement or replace if consensus data unavailable):**\n- Search: `\"{TICKER} earnings preview consensus estimates {upcoming_quarter_label} {year}\"` — sell-side previews\n- Search: `\"{TICKER} analyst expectations {year}\"` — positioning and sentiment\n\n**Note limitations** if consensus data is not directly available. Even directional context (\"estimates have been revised up 3% over the last 90 days\") is valuable.\n\n## 8. Historical Earnings Reaction\n**Stock price data (from Daloopa):**\nUse `get_stock_prices` (see `..\u002Fdata-access.md` Section 1.7) to get actual post-earnings price moves for the last 4-6 earnings prints. For each historical earnings date, pull prices for a window: `start_date` = 1 trading day before earnings, `end_date` = 3-5 trading days after. Compute:\n- Next-day move (pre-earnings close → post-earnings close)\n- 3-day drift (post-earnings close → 3 days later)\n\nTo estimate historical earnings dates, use the quarter-end date + ~30-45 days as an approximation, or use WebSearch to confirm exact dates if needed.\n\nAlso pull the current stock price (3 most recent calendar days) for the report header.\n\n**Supplement with web search for options context:**\n- Search: `\"{TICKER} options implied move earnings {upcoming_quarter_label}\"` — current implied volatility\n\n**Present as a table:**\n| Quarter | Revenue Beat\u002FMiss | EPS Beat\u002FMiss | Next-Day Move | 3-Day Drift | Notes |\n\nPopulate the Revenue\u002FEPS Beat\u002FMiss columns from the guidance credibility analysis in Section 4. The price move columns come from `get_stock_prices`.\n\n**Pattern identification:**\n- Does the stock tend to sell off on beats? (buy-the-rumor, sell-the-news pattern)\n- Does it rally on in-line results? (low expectations already embedded)\n- Is there a pattern of post-earnings drift (continued move in the days after)?\n- What's the current implied move from the options market? If it's elevated vs. history, the market expects a big move.\n\n## 9. Macro & Sector Backdrop\nWeb search for developments since last quarter that could affect results:\n- Search: `\"{TICKER} {industry} outlook {current_year}\"` — sector developments\n- Search: `\"{TICKER} headwinds tailwinds {current_year}\"` — company-specific macro factors\n\n**Distill into 5-8 bullets, each with a directional tag (Positive \u002F Negative \u002F Uncertain):**\n- Industry-specific: new regulations, competitor product launches, market share shifts\n- Macro: FX moves (specify currencies and direction), commodity prices, interest rates\n- Policy: tariffs, trade restrictions, tax changes\n- Channel: inventory levels in the channel, distributor commentary, supply chain status\n- Company-specific: product launches since last quarter, management changes, M&A\n\nKeep each bullet to one sentence. The analyst needs context, not a macro essay.\n\n## 10. Potential Surprises & Call Catalysts\nBeyond the numbers, what could management announce that would move the stock? Search filings and news for signals:\n- Search documents: \"restructuring\", \"acquisition\", \"buyback\", \"dividend\" in recent filings\n- Search: `\"{TICKER} potential announcement catalyst {year}\"` — speculative but grounded\n\n**Categories:**\n- **Capital allocation**: New buyback authorization, dividend change (hike\u002Fcut\u002Finitiation), M&A announcement, asset sale\u002Fspinoff\n- **Operational**: Restructuring\u002Flayoffs, new product launch, partnership\u002Fcontract win, segment reporting changes\n- **Strategic**: New guidance metrics, long-term targets update, management changes, investor day announcement\n- **Accounting\u002FDisclosure**: Guidance methodology change, segment redefinition, one-time charge pre-announcement\n\nFor each potential surprise, note the signal strength (rumored \u002F speculated \u002F no signal) and the likely stock impact direction.\n\n## 11. Pre-Earnings Checklist\nA concise, actionable summary that fits on a single card. This is what the analyst tapes to their monitor:\n\n**The Numbers:**\n- Revenue whisper: $X.XX (guidance: $X.XX, avg beat: +X.X%)\n- EPS whisper: $X.XX (guidance: $X.XX, avg beat: +X.X%)\n\n**Top 3 Metrics to Watch:**\n1. [Metric] — current: X, bull: >Y, bear: \u003CZ\n2. [Metric] — current: X, bull: >Y, bear: \u003CZ\n3. [Metric] — current: X, bull: >Y, bear: \u003CZ\n\n**The Bull Catalyst:** What would make this stock go up 5%+ after the print? (one sentence)\n\n**The Bear Risk:** What would make this stock go down 5%+ after the print? (one sentence)\n\n**Read-Through Signal:** After this company reports, what does it mean for [2-3 other names]?\n\n**Historical Pattern:** Last 4 prints averaged +\u002F-X% next-day move; options imply +\u002F-X% this time.\n\n## 12. Save Report\nSave to `reports\u002F{TICKER}_earnings_prep_{UPCOMING_CQ}.html` (e.g., `AAPL_earnings_prep_2026Q1.html`) using the HTML report template from `..\u002Fdesign-system.md`. The period in the filename is the **upcoming calendar quarter** being prepped for — the one AFTER `latest_calendar_quarter`. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.\n\nThe report should include:\n- Executive summary (2-3 sentences: what quarter is coming, what the key debate is, what the whisper number implies)\n- Last quarter recap (story + key metrics table)\n- Outstanding guidance table with source citations\n- Whisper number calculation with historical beat\u002Fmiss detail table\n- Peer read-throughs (grouped by Competitors \u002F Suppliers \u002F Customers \u002F Industry, with Daloopa citations on peer data)\n- Key metrics to watch (table with specific thresholds)\n- Consensus & positioning summary\n- Historical earnings reaction table\n- Macro & sector backdrop (bulleted list with directional tags)\n- Potential surprises & call catalysts\n- Pre-earnings checklist (prominently styled — this is the payoff of the whole report)\n\nAll financial figures must use Daloopa citation format: `\u003Ca href=\"https:\u002F\u002Fdaloopa.com\u002Fsrc\u002F{fundamental_id}\">$X.XX million\u003C\u002Fa>`\n\nTell the user where the HTML report was saved.\n\nHighlight what makes this print particularly interesting: Is the whisper number meaningfully above guidance (setting up for disappointment even on a beat)? Are peer read-throughs conflicting (creating genuine uncertainty)? Is there a potential surprise catalyst that could overshadow the numbers? Give the analyst the single most important thing to watch.\n",{"data":37,"body":38},{"name":4,"description":6},{"type":39,"children":40},"root",[41,49,54,82,87,94,107,160,179,185,197,205,228,236,279,284,290,295,315,323,356,364,387,395,408,413,419,432,449,459,469,497,507,512,517,525,548,556,579,589,599,605,610,618,661,671,751,759,800,810,818,858,866,894,900,905,910,920,928,951,957,962,977,1000,1008,1035,1045,1051,1091,1104,1109,1114,1122,1137,1147,1158,1166,1189,1195,1200,1227,1235,1263,1268,1274,1279,1299,1307,1350,1355,1361,1366,1374,1387,1395,1425,1435,1445,1462,1472,1478,1520,1525,1583,1594,1599],{"type":42,"tag":43,"props":44,"children":45},"element","p",{},[46],{"type":47,"value":48},"text","Generate a pre-earnings preparation report for the company specified by the user 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],{"type":47,"value":53},"This is the note a L\u002FS equity analyst reads the night before a company reports — it tells them exactly what to focus on when the print drops.",{"type":42,"tag":43,"props":55,"children":56},{},[57,80],{"type":42,"tag":58,"props":59,"children":60},"strong",{},[61,63,70,72,78],{"type":47,"value":62},"Before starting, read ",{"type":42,"tag":64,"props":65,"children":67},"code",{"className":66},[],[68],{"type":47,"value":69},"..\u002Fdata-access.md",{"type":47,"value":71}," for data access methods and ",{"type":42,"tag":64,"props":73,"children":75},{"className":74},[],[76],{"type":47,"value":77},"..\u002Fdesign-system.md",{"type":47,"value":79}," for formatting conventions.",{"type":47,"value":81}," Follow the data access detection logic and design system throughout this skill.",{"type":42,"tag":43,"props":83,"children":84},{},[85],{"type":47,"value":86},"Follow these steps:",{"type":42,"tag":88,"props":89,"children":91},"h2",{"id":90},"_1-company-lookup",[92],{"type":47,"value":93},"1. Company Lookup",{"type":42,"tag":43,"props":95,"children":96},{},[97,99,105],{"type":47,"value":98},"Look up the company by ticker using ",{"type":42,"tag":64,"props":100,"children":102},{"className":101},[],[103],{"type":47,"value":104},"discover_companies",{"type":47,"value":106},". Capture:",{"type":42,"tag":108,"props":109,"children":110},"ul",{},[111,121,139,148],{"type":42,"tag":112,"props":113,"children":114},"li",{},[115],{"type":42,"tag":64,"props":116,"children":118},{"className":117},[],[119],{"type":47,"value":120},"company_id",{"type":42,"tag":112,"props":122,"children":123},{},[124,130,132,137],{"type":42,"tag":64,"props":125,"children":127},{"className":126},[],[128],{"type":47,"value":129},"latest_calendar_quarter",{"type":47,"value":131}," — anchor for all period calculations below (see ",{"type":42,"tag":64,"props":133,"children":135},{"className":134},[],[136],{"type":47,"value":69},{"type":47,"value":138}," Section 1.5)",{"type":42,"tag":112,"props":140,"children":141},{},[142],{"type":42,"tag":64,"props":143,"children":145},{"className":144},[],[146],{"type":47,"value":147},"latest_fiscal_quarter",{"type":42,"tag":112,"props":149,"children":150},{},[151,153,158],{"type":47,"value":152},"Firm name for report attribution (default: \"Daloopa\") — see ",{"type":42,"tag":64,"props":154,"children":156},{"className":155},[],[157],{"type":47,"value":69},{"type":47,"value":159}," Section 4.5",{"type":42,"tag":43,"props":161,"children":162},{},[163,165,170,172,177],{"type":47,"value":164},"Determine the ",{"type":42,"tag":58,"props":166,"children":167},{},[168],{"type":47,"value":169},"upcoming quarter",{"type":47,"value":171}," — the one AFTER ",{"type":42,"tag":64,"props":173,"children":175},{"className":174},[],[176],{"type":47,"value":129},{"type":47,"value":178},". This is the quarter the company is about to report. All analysis is oriented around preparing the analyst for this print.",{"type":42,"tag":88,"props":180,"children":182},{"id":181},"_2-last-quarter-recap",[183],{"type":47,"value":184},"2. Last Quarter Recap",{"type":42,"tag":43,"props":186,"children":187},{},[188,190,195],{"type":47,"value":189},"Pull the most recent quarter's full financials from Daloopa. Calculate 4 quarters backward from ",{"type":42,"tag":64,"props":191,"children":193},{"className":192},[],[194],{"type":47,"value":129},{"type":47,"value":196}," (for YoY context).",{"type":42,"tag":43,"props":198,"children":199},{},[200],{"type":42,"tag":58,"props":201,"children":202},{},[203],{"type":47,"value":204},"Pull:",{"type":42,"tag":108,"props":206,"children":207},{},[208,213,218,223],{"type":42,"tag":112,"props":209,"children":210},{},[211],{"type":47,"value":212},"Revenue, Gross Profit, Operating Income, EBITDA, Net Income, Diluted EPS",{"type":42,"tag":112,"props":214,"children":215},{},[216],{"type":47,"value":217},"Operating Cash Flow, CapEx, FCF (calc.)",{"type":42,"tag":112,"props":219,"children":220},{},[221],{"type":47,"value":222},"Segment\u002Fproduct revenue breakdown",{"type":42,"tag":112,"props":224,"children":225},{},[226],{"type":47,"value":227},"Company-specific KPIs (use the business-model taxonomy: SaaS → ARR\u002FNRR\u002FRPO; Consumer → DAU\u002FARPU; E-commerce → GMV\u002Ftake rate; etc.)",{"type":42,"tag":43,"props":229,"children":230},{},[231],{"type":42,"tag":58,"props":232,"children":233},{},[234],{"type":47,"value":235},"Summarize the story of last quarter in 3-5 bullets:",{"type":42,"tag":108,"props":237,"children":238},{},[239,244,249,269,274],{"type":42,"tag":112,"props":240,"children":241},{},[242],{"type":47,"value":243},"What beat expectations (guidance or consensus)?",{"type":42,"tag":112,"props":245,"children":246},{},[247],{"type":47,"value":248},"What missed or disappointed?",{"type":42,"tag":112,"props":250,"children":251},{},[252,254,260,262,267],{"type":47,"value":253},"What was the stock reaction? (use ",{"type":42,"tag":64,"props":255,"children":257},{"className":256},[],[258],{"type":47,"value":259},"get_stock_prices",{"type":47,"value":261}," per ",{"type":42,"tag":64,"props":263,"children":265},{"className":264},[],[266],{"type":47,"value":69},{"type":47,"value":268}," Section 1.7 to get the actual next-day move; supplement with WebSearch for narrative context if needed)",{"type":42,"tag":112,"props":270,"children":271},{},[272],{"type":47,"value":273},"What narrative emerged from the call? (e.g., \"AI monetization acceleration,\" \"margin expansion story intact,\" \"consumer weakness\")",{"type":42,"tag":112,"props":275,"children":276},{},[277],{"type":47,"value":278},"What was the single most debated metric?",{"type":42,"tag":43,"props":280,"children":281},{},[282],{"type":47,"value":283},"This is the baseline everyone on the upcoming call will be anchoring to.",{"type":42,"tag":88,"props":285,"children":287},{"id":286},"_3-outstanding-guidance-for-upcoming-quarter",[288],{"type":47,"value":289},"3. Outstanding Guidance for Upcoming Quarter",{"type":42,"tag":43,"props":291,"children":292},{},[293],{"type":47,"value":294},"Search for ALL guidance series using keywords: \"guidance\", \"outlook\", \"estimate\", \"forecast\", \"target\". Apply the +1 quarter offset to identify which guidance applies to the upcoming print:",{"type":42,"tag":108,"props":296,"children":297},{},[298,303],{"type":42,"tag":112,"props":299,"children":300},{},[301],{"type":47,"value":302},"CRITICAL: Guidance from Q(N) earnings call applies to Q(N+1) results",{"type":42,"tag":112,"props":304,"children":305},{},[306,308,313],{"type":47,"value":307},"The guidance issued during the ",{"type":42,"tag":64,"props":309,"children":311},{"className":310},[],[312],{"type":47,"value":129},{"type":47,"value":314}," earnings call is what applies to the upcoming quarter",{"type":42,"tag":43,"props":316,"children":317},{},[318],{"type":42,"tag":58,"props":319,"children":320},{},[321],{"type":47,"value":322},"Pull and present:",{"type":42,"tag":108,"props":324,"children":325},{},[326,331,336,341,346,351],{"type":42,"tag":112,"props":327,"children":328},{},[329],{"type":47,"value":330},"Revenue guidance (point estimate or range)",{"type":42,"tag":112,"props":332,"children":333},{},[334],{"type":47,"value":335},"EPS guidance",{"type":42,"tag":112,"props":337,"children":338},{},[339],{"type":47,"value":340},"Margin guidance (gross, operating, EBITDA)",{"type":42,"tag":112,"props":342,"children":343},{},[344],{"type":47,"value":345},"CapEx guidance",{"type":42,"tag":112,"props":347,"children":348},{},[349],{"type":47,"value":350},"Segment-level guidance (if available)",{"type":42,"tag":112,"props":352,"children":353},{},[354],{"type":47,"value":355},"KPI guidance (subscriber adds, unit volumes, ARPU targets, etc.)",{"type":42,"tag":43,"props":357,"children":358},{},[359],{"type":42,"tag":58,"props":360,"children":361},{},[362],{"type":47,"value":363},"Search filings for directional\u002Fqualitative guidance:",{"type":42,"tag":108,"props":365,"children":366},{},[367,372,377,382],{"type":42,"tag":112,"props":368,"children":369},{},[370],{"type":47,"value":371},"Search documents for: \"expect\", \"anticipate\", \"similar to\", \"consistent with\"",{"type":42,"tag":112,"props":373,"children":374},{},[375],{"type":47,"value":376},"Search documents for: \"low single digit\", \"mid single digit\", \"double digit\", \"sequential\"",{"type":42,"tag":112,"props":378,"children":379},{},[380],{"type":47,"value":381},"Search documents for: \"headwind\", \"tailwind\", \"conservatively\", \"assumes\"",{"type":42,"tag":112,"props":383,"children":384},{},[385],{"type":47,"value":386},"Capture exact management quotes with document citations",{"type":42,"tag":43,"props":388,"children":389},{},[390],{"type":42,"tag":58,"props":391,"children":392},{},[393],{"type":47,"value":394},"Flag any guidance updates between quarters:",{"type":42,"tag":108,"props":396,"children":397},{},[398,403],{"type":42,"tag":112,"props":399,"children":400},{},[401],{"type":47,"value":402},"Search for \"pre-announce\", \"update\", \"revise\" in the most recent quarter's filings",{"type":42,"tag":112,"props":404,"children":405},{},[406],{"type":47,"value":407},"Check if the company issued an 8-K updating guidance after the last earnings call",{"type":42,"tag":43,"props":409,"children":410},{},[411],{"type":47,"value":412},"Present all guidance in a single table: Metric | Guidance Value | Source Quarter | Type (Quantitative\u002FDirectional).",{"type":42,"tag":88,"props":414,"children":416},{"id":415},"_4-guidance-credibility-whisper-number",[417],{"type":47,"value":418},"4. Guidance Credibility & Whisper Number",{"type":42,"tag":43,"props":420,"children":421},{},[422,424,430],{"type":47,"value":423},"This section MUST be built entirely from Daloopa data — guidance series AND actual result series pulled via ",{"type":42,"tag":64,"props":425,"children":427},{"className":426},[],[428],{"type":47,"value":429},"get_company_fundamentals",{"type":47,"value":431},". Do not use web search or estimates for this analysis.",{"type":42,"tag":43,"props":433,"children":434},{},[435,440,442,447],{"type":42,"tag":58,"props":436,"children":437},{},[438],{"type":47,"value":439},"Step 1: Pull 8 quarters of guidance data.",{"type":47,"value":441},"\nYou already discovered guidance series in Section 3. Now pull ALL of those guidance series for the last 8 quarters (from ",{"type":42,"tag":64,"props":443,"children":445},{"className":444},[],[446],{"type":47,"value":129},{"type":47,"value":448}," backward). These are the guidance values management provided each quarter.",{"type":42,"tag":43,"props":450,"children":451},{},[452,457],{"type":42,"tag":58,"props":453,"children":454},{},[455],{"type":47,"value":456},"Step 2: Pull 8 quarters of corresponding actuals.",{"type":47,"value":458},"\nFor every guided metric, identify the corresponding actual result series (e.g., if there is a \"Revenue guidance\" series, pull the actual \"Revenue\" series). Pull these actuals for the same 8-quarter period.",{"type":42,"tag":43,"props":460,"children":461},{},[462,467],{"type":42,"tag":58,"props":463,"children":464},{},[465],{"type":47,"value":466},"Step 3: Build the complete beat\u002Fmiss table.",{"type":47,"value":468},"\nApply the +1 quarter offset: guidance from Q(N) is compared to the actual result in Q(N+1). For EVERY quarter where both a guidance value and a corresponding actual exist, compute:",{"type":42,"tag":108,"props":470,"children":471},{},[472,477,482,487,492],{"type":42,"tag":112,"props":473,"children":474},{},[475],{"type":47,"value":476},"Guidance value (midpoint if range)",{"type":42,"tag":112,"props":478,"children":479},{},[480],{"type":47,"value":481},"Actual value",{"type":42,"tag":112,"props":483,"children":484},{},[485],{"type":47,"value":486},"Delta (Actual - Guidance midpoint)",{"type":42,"tag":112,"props":488,"children":489},{},[490],{"type":47,"value":491},"Beat\u002FMiss % ((Actual - Guidance midpoint) \u002F |Guidance midpoint| × 100)",{"type":42,"tag":112,"props":493,"children":494},{},[495],{"type":47,"value":496},"Classification: Beat \u002F In-line \u002F Miss (use +\u002F-1% threshold for in-line)",{"type":42,"tag":43,"props":498,"children":499},{},[500,505],{"type":42,"tag":58,"props":501,"children":502},{},[503],{"type":47,"value":504},"Present a FULL detail table — every quarter, every guided metric.",{"type":47,"value":506}," This is the core analytical engine of the whisper number. Do not summarize or abbreviate — show all rows. Format:",{"type":42,"tag":43,"props":508,"children":509},{},[510],{"type":47,"value":511},"| Guidance Source Qtr | Metric | Guidance (Mid) | Actual Qtr | Actual | Delta | Beat\u002FMiss % |",{"type":42,"tag":43,"props":513,"children":514},{},[515],{"type":47,"value":516},"If a company provides range guidance (low\u002Fhigh), show the midpoint and note the range width. If a company only provides directional guidance for some metrics (e.g., \"revenue growth in low teens\"), convert to an implied numeric value for comparison (e.g., 12-13% → midpoint ~12.5% applied to prior year actual).",{"type":42,"tag":43,"props":518,"children":519},{},[520],{"type":42,"tag":58,"props":521,"children":522},{},[523],{"type":47,"value":524},"Step 4: Compute summary statistics from the detail table:",{"type":42,"tag":108,"props":526,"children":527},{},[528,533,538,543],{"type":42,"tag":112,"props":529,"children":530},{},[531],{"type":47,"value":532},"Beat rate per metric (% of quarters where actual > guidance midpoint)",{"type":42,"tag":112,"props":534,"children":535},{},[536],{"type":47,"value":537},"Average beat magnitude per metric (in absolute terms and %)",{"type":42,"tag":112,"props":539,"children":540},{},[541],{"type":47,"value":542},"Beat pattern trend: is the beat getting larger (sandbagging increasing), shrinking (guidance getting more accurate), or volatile? Look at the last 4 vs. prior 4.",{"type":42,"tag":112,"props":544,"children":545},{},[546],{"type":47,"value":547},"Range width trend: is management tightening or widening guidance ranges?",{"type":42,"tag":43,"props":549,"children":550},{},[551],{"type":42,"tag":58,"props":552,"children":553},{},[554],{"type":47,"value":555},"Step 5: Calculate the implied \"whisper number\":",{"type":42,"tag":108,"props":557,"children":558},{},[559,564,569,574],{"type":42,"tag":112,"props":560,"children":561},{},[562],{"type":47,"value":563},"Whisper = Current guidance midpoint + Average historical beat (from the detail table above)",{"type":42,"tag":112,"props":565,"children":566},{},[567],{"type":47,"value":568},"This is the REAL bar the stock is trading against, not the stated guidance",{"type":42,"tag":112,"props":570,"children":571},{},[572],{"type":47,"value":573},"If the company beats by 2% on average, the market expects a 2% beat — an in-line result to guidance is effectively a miss",{"type":42,"tag":112,"props":575,"children":576},{},[577],{"type":47,"value":578},"Calculate whisper for EVERY guided metric, not just revenue",{"type":42,"tag":43,"props":580,"children":581},{},[582,587],{"type":42,"tag":58,"props":583,"children":584},{},[585],{"type":47,"value":586},"Present the whisper summary:",{"type":47,"value":588},"\n| Metric | Current Guidance (Mid) | Avg Historical Beat | Implied Whisper | Beat Rate (n\u002FN) |",{"type":42,"tag":43,"props":590,"children":591},{},[592,597],{"type":42,"tag":58,"props":593,"children":594},{},[595],{"type":47,"value":596},"Credibility verdict:",{"type":47,"value":598}," Is management's guidance informative (tight, accurate) or performative (always sandbagged, uninformative)? If the beat rate is >90%, say so — it means the guidance number is a floor, not a forecast. If the beat magnitude is increasing, management is becoming MORE conservative over time.",{"type":42,"tag":88,"props":600,"children":602},{"id":601},"_5-peer-adjacent-company-read-throughs",[603],{"type":47,"value":604},"5. Peer & Adjacent Company Read-Throughs",{"type":42,"tag":43,"props":606,"children":607},{},[608],{"type":47,"value":609},"This is the most differentiated section. For companies in the same sector that have ALREADY reported this earnings season, their results contain direct signal about the upcoming print.",{"type":42,"tag":43,"props":611,"children":612},{},[613],{"type":42,"tag":58,"props":614,"children":615},{},[616],{"type":47,"value":617},"Identify the read-through universe (aim for 5-8 companies):",{"type":42,"tag":108,"props":619,"children":620},{},[621,631,641,651],{"type":42,"tag":112,"props":622,"children":623},{},[624,629],{"type":42,"tag":58,"props":625,"children":626},{},[627],{"type":47,"value":628},"Competitors",{"type":47,"value":630},": Direct rivals in the same market",{"type":42,"tag":112,"props":632,"children":633},{},[634,639],{"type":42,"tag":58,"props":635,"children":636},{},[637],{"type":47,"value":638},"Suppliers",{"type":47,"value":640},": Companies that sell to the target company",{"type":42,"tag":112,"props":642,"children":643},{},[644,649],{"type":42,"tag":58,"props":645,"children":646},{},[647],{"type":47,"value":648},"Customers",{"type":47,"value":650},": Companies that buy from the target company",{"type":42,"tag":112,"props":652,"children":653},{},[654,659],{"type":42,"tag":58,"props":655,"children":656},{},[657],{"type":47,"value":658},"Industry bellwethers",{"type":47,"value":660},": Large companies whose results signal sector trends",{"type":42,"tag":43,"props":662,"children":663},{},[664,669],{"type":42,"tag":58,"props":665,"children":666},{},[667],{"type":47,"value":668},"CRITICAL: Always use Daloopa as the primary data source for peer analysis.",{"type":47,"value":670}," For each peer:",{"type":42,"tag":672,"props":673,"children":674},"ol",{},[675,699,724,741],{"type":42,"tag":112,"props":676,"children":677},{},[678,683,685,690,692,697],{"type":42,"tag":58,"props":679,"children":680},{},[681],{"type":47,"value":682},"Look up the peer in Daloopa:",{"type":47,"value":684}," ",{"type":42,"tag":64,"props":686,"children":688},{"className":687},[],[689],{"type":47,"value":104},{"type":47,"value":691}," with the peer's ticker. If Daloopa has the company, check ",{"type":42,"tag":64,"props":693,"children":695},{"className":694},[],[696],{"type":47,"value":129},{"type":47,"value":698}," to determine whether they have already reported the relevant quarter.",{"type":42,"tag":112,"props":700,"children":701},{},[702,707,709,715,717,722],{"type":42,"tag":58,"props":703,"children":704},{},[705],{"type":47,"value":706},"If the peer has data for the current earnings season quarter:",{"type":47,"value":708}," Pull their financials from Daloopa (",{"type":42,"tag":64,"props":710,"children":712},{"className":711},[],[713],{"type":47,"value":714},"discover_company_series",{"type":47,"value":716}," → ",{"type":42,"tag":64,"props":718,"children":720},{"className":719},[],[721],{"type":47,"value":429},{"type":47,"value":723},"). Focus on 2-4 metrics most relevant to the read-through (e.g., for a supplier: revenue, segment breakdown, inventory; for a competitor: revenue growth, market share proxies, pricing commentary).",{"type":42,"tag":112,"props":725,"children":726},{},[727,732,733,739],{"type":42,"tag":58,"props":728,"children":729},{},[730],{"type":47,"value":731},"Search the peer's filings in Daloopa:",{"type":47,"value":684},{"type":42,"tag":64,"props":734,"children":736},{"className":735},[],[737],{"type":47,"value":738},"search_documents",{"type":47,"value":740}," with keywords related to the target company's products, markets, or industry (e.g., for an Apple supplier, search for \"Apple\", \"smartphone\", \"consumer electronics\").",{"type":42,"tag":112,"props":742,"children":743},{},[744,749],{"type":42,"tag":58,"props":745,"children":746},{},[747],{"type":47,"value":748},"Use WebSearch only to supplement Daloopa data",{"type":47,"value":750}," — for earnings-season timing confirmation, stock price reactions, or analyst commentary that Daloopa filings don't cover.",{"type":42,"tag":43,"props":752,"children":753},{},[754],{"type":42,"tag":58,"props":755,"children":756},{},[757],{"type":47,"value":758},"For each read-through, extract (with Daloopa citations):",{"type":42,"tag":672,"props":760,"children":761},{},[762,780,790],{"type":42,"tag":112,"props":763,"children":764},{},[765,770,772,778],{"type":42,"tag":58,"props":766,"children":767},{},[768],{"type":47,"value":769},"The specific data point",{"type":47,"value":771}," — the peer's metric that creates signal. Cite the Daloopa ",{"type":42,"tag":64,"props":773,"children":775},{"className":774},[],[776],{"type":47,"value":777},"fundamental_id",{"type":47,"value":779},".",{"type":42,"tag":112,"props":781,"children":782},{},[783,788],{"type":42,"tag":58,"props":784,"children":785},{},[786],{"type":47,"value":787},"The implication",{"type":47,"value":789}," — bullish or bearish for the target company, and why",{"type":42,"tag":112,"props":791,"children":792},{},[793,798],{"type":42,"tag":58,"props":794,"children":795},{},[796],{"type":47,"value":797},"Confidence level",{"type":47,"value":799}," — High (direct disclosed relationship), Moderate (inferred from industry), Low (circumstantial)",{"type":42,"tag":43,"props":801,"children":802},{},[803,808],{"type":42,"tag":58,"props":804,"children":805},{},[806],{"type":47,"value":807},"For peers that haven't reported yet:",{"type":47,"value":809}," Note them as \"reports after {TICKER}\" — their results will be a read-through in the opposite direction.",{"type":42,"tag":43,"props":811,"children":812},{},[813],{"type":42,"tag":58,"props":814,"children":815},{},[816],{"type":47,"value":817},"Group read-throughs by:",{"type":42,"tag":108,"props":819,"children":820},{},[821,830,839,848],{"type":42,"tag":112,"props":822,"children":823},{},[824,828],{"type":42,"tag":58,"props":825,"children":826},{},[827],{"type":47,"value":628},{"type":47,"value":829}," — share shift signals, pricing environment, demand trends",{"type":42,"tag":112,"props":831,"children":832},{},[833,837],{"type":42,"tag":58,"props":834,"children":835},{},[836],{"type":47,"value":638},{"type":47,"value":838}," — order book signals, inventory levels, capacity commentary",{"type":42,"tag":112,"props":840,"children":841},{},[842,846],{"type":42,"tag":58,"props":843,"children":844},{},[845],{"type":47,"value":648},{"type":47,"value":847}," — demand signals, inventory destocking\u002Frestocking, spending priorities",{"type":42,"tag":112,"props":849,"children":850},{},[851,856],{"type":42,"tag":58,"props":852,"children":853},{},[854],{"type":47,"value":855},"Industry Bellwethers",{"type":47,"value":857}," — macro\u002Fsector health, end-market demand",{"type":42,"tag":43,"props":859,"children":860},{},[861],{"type":42,"tag":58,"props":862,"children":863},{},[864],{"type":47,"value":865},"Web research for sector context (supplementary only — after Daloopa pulls):",{"type":42,"tag":108,"props":867,"children":868},{},[869,882],{"type":42,"tag":112,"props":870,"children":871},{},[872,874,880],{"type":47,"value":873},"Search: ",{"type":42,"tag":64,"props":875,"children":877},{"className":876},[],[878],{"type":47,"value":879},"\"{TICKER} sector earnings season {year} read through\"",{"type":47,"value":881}," — analyst commentary on cross-company signals",{"type":42,"tag":112,"props":883,"children":884},{},[885,886,892],{"type":47,"value":873},{"type":42,"tag":64,"props":887,"children":889},{"className":888},[],[890],{"type":47,"value":891},"\"{TICKER} competitors results {upcoming_quarter_label} {year}\"",{"type":47,"value":893}," — what peers have already signaled",{"type":42,"tag":88,"props":895,"children":897},{"id":896},"_6-key-metrics-to-watch",[898],{"type":47,"value":899},"6. Key Metrics to Watch",{"type":42,"tag":43,"props":901,"children":902},{},[903],{"type":47,"value":904},"Identify the 5-7 metrics the analyst should focus on when the print drops. For each metric:",{"type":42,"tag":43,"props":906,"children":907},{},[908],{"type":47,"value":909},"| Metric | Current Level | Guidance\u002FExpected | Bullish Threshold | Bearish Threshold | Why It Matters |",{"type":42,"tag":43,"props":911,"children":912},{},[913,918],{"type":42,"tag":58,"props":914,"children":915},{},[916],{"type":47,"value":917},"Be specific with thresholds",{"type":47,"value":919}," — not \"revenue growth\" but \"revenue above $95B signals iPhone cycle acceleration; below $92B confirms China weakness.\" Not \"margins\" but \"gross margin above 47% confirms services mix shift; below 45% signals hardware pricing pressure.\"",{"type":42,"tag":43,"props":921,"children":922},{},[923],{"type":42,"tag":58,"props":924,"children":925},{},[926],{"type":47,"value":927},"Prioritize by information value:",{"type":42,"tag":672,"props":929,"children":930},{},[931,936,941,946],{"type":42,"tag":112,"props":932,"children":933},{},[934],{"type":47,"value":935},"Metrics where guidance has been vague or directional (highest uncertainty)",{"type":42,"tag":112,"props":937,"children":938},{},[939],{"type":47,"value":940},"Metrics where peer read-throughs are conflicting (the print will resolve the debate)",{"type":42,"tag":112,"props":942,"children":943},{},[944],{"type":47,"value":945},"Metrics that drive the forward multiple (the ones the market will re-rate on)",{"type":42,"tag":112,"props":947,"children":948},{},[949],{"type":47,"value":950},"KPIs that lead revenue by 1-2 quarters (predictive of next quarter's financials)",{"type":42,"tag":88,"props":952,"children":954},{"id":953},"_7-consensus-positioning",[955],{"type":47,"value":956},"7. Consensus & Positioning",{"type":42,"tag":43,"props":958,"children":959},{},[960],{"type":47,"value":961},"Gather available consensus context:",{"type":42,"tag":43,"props":963,"children":964},{},[965],{"type":42,"tag":58,"props":966,"children":967},{},[968,970,975],{"type":47,"value":969},"From data sources (consensus estimates if available per ",{"type":42,"tag":64,"props":971,"children":973},{"className":972},[],[974],{"type":47,"value":69},{"type":47,"value":976}," Section 3):",{"type":42,"tag":108,"props":978,"children":979},{},[980,985,990,995],{"type":42,"tag":112,"props":981,"children":982},{},[983],{"type":47,"value":984},"Consensus revenue and EPS for the upcoming quarter",{"type":42,"tag":112,"props":986,"children":987},{},[988],{"type":47,"value":989},"Number of analysts at Buy \u002F Hold \u002F Sell",{"type":42,"tag":112,"props":991,"children":992},{},[993],{"type":47,"value":994},"Consensus price target (median and range)",{"type":42,"tag":112,"props":996,"children":997},{},[998],{"type":47,"value":999},"Recent estimate revision trends (last 30\u002F60\u002F90 days — moving up or down?)",{"type":42,"tag":43,"props":1001,"children":1002},{},[1003],{"type":42,"tag":58,"props":1004,"children":1005},{},[1006],{"type":47,"value":1007},"From web search (supplement or replace if consensus data unavailable):",{"type":42,"tag":108,"props":1009,"children":1010},{},[1011,1023],{"type":42,"tag":112,"props":1012,"children":1013},{},[1014,1015,1021],{"type":47,"value":873},{"type":42,"tag":64,"props":1016,"children":1018},{"className":1017},[],[1019],{"type":47,"value":1020},"\"{TICKER} earnings preview consensus estimates {upcoming_quarter_label} {year}\"",{"type":47,"value":1022}," — sell-side previews",{"type":42,"tag":112,"props":1024,"children":1025},{},[1026,1027,1033],{"type":47,"value":873},{"type":42,"tag":64,"props":1028,"children":1030},{"className":1029},[],[1031],{"type":47,"value":1032},"\"{TICKER} analyst expectations {year}\"",{"type":47,"value":1034}," — positioning and sentiment",{"type":42,"tag":43,"props":1036,"children":1037},{},[1038,1043],{"type":42,"tag":58,"props":1039,"children":1040},{},[1041],{"type":47,"value":1042},"Note limitations",{"type":47,"value":1044}," if consensus data is not directly available. Even directional context (\"estimates have been revised up 3% over the last 90 days\") is valuable.",{"type":42,"tag":88,"props":1046,"children":1048},{"id":1047},"_8-historical-earnings-reaction",[1049],{"type":47,"value":1050},"8. Historical Earnings Reaction",{"type":42,"tag":43,"props":1052,"children":1053},{},[1054,1059,1061,1066,1068,1073,1075,1081,1083,1089],{"type":42,"tag":58,"props":1055,"children":1056},{},[1057],{"type":47,"value":1058},"Stock price data (from Daloopa):",{"type":47,"value":1060},"\nUse ",{"type":42,"tag":64,"props":1062,"children":1064},{"className":1063},[],[1065],{"type":47,"value":259},{"type":47,"value":1067}," (see ",{"type":42,"tag":64,"props":1069,"children":1071},{"className":1070},[],[1072],{"type":47,"value":69},{"type":47,"value":1074}," Section 1.7) to get actual post-earnings price moves for the last 4-6 earnings prints. For each historical earnings date, pull prices for a window: ",{"type":42,"tag":64,"props":1076,"children":1078},{"className":1077},[],[1079],{"type":47,"value":1080},"start_date",{"type":47,"value":1082}," = 1 trading day before earnings, ",{"type":42,"tag":64,"props":1084,"children":1086},{"className":1085},[],[1087],{"type":47,"value":1088},"end_date",{"type":47,"value":1090}," = 3-5 trading days after. Compute:",{"type":42,"tag":108,"props":1092,"children":1093},{},[1094,1099],{"type":42,"tag":112,"props":1095,"children":1096},{},[1097],{"type":47,"value":1098},"Next-day move (pre-earnings close → post-earnings close)",{"type":42,"tag":112,"props":1100,"children":1101},{},[1102],{"type":47,"value":1103},"3-day drift (post-earnings close → 3 days later)",{"type":42,"tag":43,"props":1105,"children":1106},{},[1107],{"type":47,"value":1108},"To estimate historical earnings dates, use the quarter-end date + ~30-45 days as an approximation, or use WebSearch to confirm exact dates if needed.",{"type":42,"tag":43,"props":1110,"children":1111},{},[1112],{"type":47,"value":1113},"Also pull the current stock price (3 most recent calendar days) for the report header.",{"type":42,"tag":43,"props":1115,"children":1116},{},[1117],{"type":42,"tag":58,"props":1118,"children":1119},{},[1120],{"type":47,"value":1121},"Supplement with web search for options context:",{"type":42,"tag":108,"props":1123,"children":1124},{},[1125],{"type":42,"tag":112,"props":1126,"children":1127},{},[1128,1129,1135],{"type":47,"value":873},{"type":42,"tag":64,"props":1130,"children":1132},{"className":1131},[],[1133],{"type":47,"value":1134},"\"{TICKER} options implied move earnings {upcoming_quarter_label}\"",{"type":47,"value":1136}," — current implied volatility",{"type":42,"tag":43,"props":1138,"children":1139},{},[1140,1145],{"type":42,"tag":58,"props":1141,"children":1142},{},[1143],{"type":47,"value":1144},"Present as a table:",{"type":47,"value":1146},"\n| Quarter | Revenue Beat\u002FMiss | EPS Beat\u002FMiss | Next-Day Move | 3-Day Drift | Notes |",{"type":42,"tag":43,"props":1148,"children":1149},{},[1150,1152,1157],{"type":47,"value":1151},"Populate the Revenue\u002FEPS Beat\u002FMiss columns from the guidance credibility analysis in Section 4. The price move columns come from ",{"type":42,"tag":64,"props":1153,"children":1155},{"className":1154},[],[1156],{"type":47,"value":259},{"type":47,"value":779},{"type":42,"tag":43,"props":1159,"children":1160},{},[1161],{"type":42,"tag":58,"props":1162,"children":1163},{},[1164],{"type":47,"value":1165},"Pattern identification:",{"type":42,"tag":108,"props":1167,"children":1168},{},[1169,1174,1179,1184],{"type":42,"tag":112,"props":1170,"children":1171},{},[1172],{"type":47,"value":1173},"Does the stock tend to sell off on beats? (buy-the-rumor, sell-the-news pattern)",{"type":42,"tag":112,"props":1175,"children":1176},{},[1177],{"type":47,"value":1178},"Does it rally on in-line results? (low expectations already embedded)",{"type":42,"tag":112,"props":1180,"children":1181},{},[1182],{"type":47,"value":1183},"Is there a pattern of post-earnings drift (continued move in the days after)?",{"type":42,"tag":112,"props":1185,"children":1186},{},[1187],{"type":47,"value":1188},"What's the current implied move from the options market? If it's elevated vs. history, the market expects a big move.",{"type":42,"tag":88,"props":1190,"children":1192},{"id":1191},"_9-macro-sector-backdrop",[1193],{"type":47,"value":1194},"9. Macro & Sector Backdrop",{"type":42,"tag":43,"props":1196,"children":1197},{},[1198],{"type":47,"value":1199},"Web search for developments since last quarter that could affect results:",{"type":42,"tag":108,"props":1201,"children":1202},{},[1203,1215],{"type":42,"tag":112,"props":1204,"children":1205},{},[1206,1207,1213],{"type":47,"value":873},{"type":42,"tag":64,"props":1208,"children":1210},{"className":1209},[],[1211],{"type":47,"value":1212},"\"{TICKER} {industry} outlook {current_year}\"",{"type":47,"value":1214}," — sector developments",{"type":42,"tag":112,"props":1216,"children":1217},{},[1218,1219,1225],{"type":47,"value":873},{"type":42,"tag":64,"props":1220,"children":1222},{"className":1221},[],[1223],{"type":47,"value":1224},"\"{TICKER} headwinds tailwinds {current_year}\"",{"type":47,"value":1226}," — company-specific macro factors",{"type":42,"tag":43,"props":1228,"children":1229},{},[1230],{"type":42,"tag":58,"props":1231,"children":1232},{},[1233],{"type":47,"value":1234},"Distill into 5-8 bullets, each with a directional tag (Positive \u002F Negative \u002F Uncertain):",{"type":42,"tag":108,"props":1236,"children":1237},{},[1238,1243,1248,1253,1258],{"type":42,"tag":112,"props":1239,"children":1240},{},[1241],{"type":47,"value":1242},"Industry-specific: new regulations, competitor product launches, market share shifts",{"type":42,"tag":112,"props":1244,"children":1245},{},[1246],{"type":47,"value":1247},"Macro: FX moves (specify currencies and direction), commodity prices, interest rates",{"type":42,"tag":112,"props":1249,"children":1250},{},[1251],{"type":47,"value":1252},"Policy: tariffs, trade restrictions, tax changes",{"type":42,"tag":112,"props":1254,"children":1255},{},[1256],{"type":47,"value":1257},"Channel: inventory levels in the channel, distributor commentary, supply chain status",{"type":42,"tag":112,"props":1259,"children":1260},{},[1261],{"type":47,"value":1262},"Company-specific: product launches since last quarter, management changes, M&A",{"type":42,"tag":43,"props":1264,"children":1265},{},[1266],{"type":47,"value":1267},"Keep each bullet to one sentence. The analyst needs context, not a macro essay.",{"type":42,"tag":88,"props":1269,"children":1271},{"id":1270},"_10-potential-surprises-call-catalysts",[1272],{"type":47,"value":1273},"10. Potential Surprises & Call Catalysts",{"type":42,"tag":43,"props":1275,"children":1276},{},[1277],{"type":47,"value":1278},"Beyond the numbers, what could management announce that would move the stock? Search filings and news for signals:",{"type":42,"tag":108,"props":1280,"children":1281},{},[1282,1287],{"type":42,"tag":112,"props":1283,"children":1284},{},[1285],{"type":47,"value":1286},"Search documents: \"restructuring\", \"acquisition\", \"buyback\", \"dividend\" in recent filings",{"type":42,"tag":112,"props":1288,"children":1289},{},[1290,1291,1297],{"type":47,"value":873},{"type":42,"tag":64,"props":1292,"children":1294},{"className":1293},[],[1295],{"type":47,"value":1296},"\"{TICKER} potential announcement catalyst {year}\"",{"type":47,"value":1298}," — speculative but grounded",{"type":42,"tag":43,"props":1300,"children":1301},{},[1302],{"type":42,"tag":58,"props":1303,"children":1304},{},[1305],{"type":47,"value":1306},"Categories:",{"type":42,"tag":108,"props":1308,"children":1309},{},[1310,1320,1330,1340],{"type":42,"tag":112,"props":1311,"children":1312},{},[1313,1318],{"type":42,"tag":58,"props":1314,"children":1315},{},[1316],{"type":47,"value":1317},"Capital allocation",{"type":47,"value":1319},": New buyback authorization, dividend change (hike\u002Fcut\u002Finitiation), M&A announcement, asset sale\u002Fspinoff",{"type":42,"tag":112,"props":1321,"children":1322},{},[1323,1328],{"type":42,"tag":58,"props":1324,"children":1325},{},[1326],{"type":47,"value":1327},"Operational",{"type":47,"value":1329},": Restructuring\u002Flayoffs, new product launch, partnership\u002Fcontract win, segment reporting changes",{"type":42,"tag":112,"props":1331,"children":1332},{},[1333,1338],{"type":42,"tag":58,"props":1334,"children":1335},{},[1336],{"type":47,"value":1337},"Strategic",{"type":47,"value":1339},": New guidance metrics, long-term targets update, management changes, investor day announcement",{"type":42,"tag":112,"props":1341,"children":1342},{},[1343,1348],{"type":42,"tag":58,"props":1344,"children":1345},{},[1346],{"type":47,"value":1347},"Accounting\u002FDisclosure",{"type":47,"value":1349},": Guidance methodology change, segment redefinition, one-time charge pre-announcement",{"type":42,"tag":43,"props":1351,"children":1352},{},[1353],{"type":47,"value":1354},"For each potential surprise, note the signal strength (rumored \u002F speculated \u002F no signal) and the likely stock impact direction.",{"type":42,"tag":88,"props":1356,"children":1358},{"id":1357},"_11-pre-earnings-checklist",[1359],{"type":47,"value":1360},"11. Pre-Earnings Checklist",{"type":42,"tag":43,"props":1362,"children":1363},{},[1364],{"type":47,"value":1365},"A concise, actionable summary that fits on a single card. This is what the analyst tapes to their monitor:",{"type":42,"tag":43,"props":1367,"children":1368},{},[1369],{"type":42,"tag":58,"props":1370,"children":1371},{},[1372],{"type":47,"value":1373},"The Numbers:",{"type":42,"tag":108,"props":1375,"children":1376},{},[1377,1382],{"type":42,"tag":112,"props":1378,"children":1379},{},[1380],{"type":47,"value":1381},"Revenue whisper: $X.XX (guidance: $X.XX, avg beat: +X.X%)",{"type":42,"tag":112,"props":1383,"children":1384},{},[1385],{"type":47,"value":1386},"EPS whisper: $X.XX (guidance: $X.XX, avg beat: +X.X%)",{"type":42,"tag":43,"props":1388,"children":1389},{},[1390],{"type":42,"tag":58,"props":1391,"children":1392},{},[1393],{"type":47,"value":1394},"Top 3 Metrics to Watch:",{"type":42,"tag":672,"props":1396,"children":1397},{},[1398,1409,1417],{"type":42,"tag":112,"props":1399,"children":1400},{},[1401,1407],{"type":42,"tag":1402,"props":1403,"children":1404},"span",{},[1405],{"type":47,"value":1406},"Metric",{"type":47,"value":1408}," — current: X, bull: >Y, bear: \u003CZ",{"type":42,"tag":112,"props":1410,"children":1411},{},[1412,1416],{"type":42,"tag":1402,"props":1413,"children":1414},{},[1415],{"type":47,"value":1406},{"type":47,"value":1408},{"type":42,"tag":112,"props":1418,"children":1419},{},[1420,1424],{"type":42,"tag":1402,"props":1421,"children":1422},{},[1423],{"type":47,"value":1406},{"type":47,"value":1408},{"type":42,"tag":43,"props":1426,"children":1427},{},[1428,1433],{"type":42,"tag":58,"props":1429,"children":1430},{},[1431],{"type":47,"value":1432},"The Bull Catalyst:",{"type":47,"value":1434}," What would make this stock go up 5%+ after the print? (one sentence)",{"type":42,"tag":43,"props":1436,"children":1437},{},[1438,1443],{"type":42,"tag":58,"props":1439,"children":1440},{},[1441],{"type":47,"value":1442},"The Bear Risk:",{"type":47,"value":1444}," What would make this stock go down 5%+ after the print? (one sentence)",{"type":42,"tag":43,"props":1446,"children":1447},{},[1448,1453,1455,1460],{"type":42,"tag":58,"props":1449,"children":1450},{},[1451],{"type":47,"value":1452},"Read-Through Signal:",{"type":47,"value":1454}," After this company reports, what does it mean for ",{"type":42,"tag":1402,"props":1456,"children":1457},{},[1458],{"type":47,"value":1459},"2-3 other names",{"type":47,"value":1461},"?",{"type":42,"tag":43,"props":1463,"children":1464},{},[1465,1470],{"type":42,"tag":58,"props":1466,"children":1467},{},[1468],{"type":47,"value":1469},"Historical Pattern:",{"type":47,"value":1471}," Last 4 prints averaged +\u002F-X% next-day move; options imply +\u002F-X% this time.",{"type":42,"tag":88,"props":1473,"children":1475},{"id":1474},"_12-save-report",[1476],{"type":47,"value":1477},"12. Save Report",{"type":42,"tag":43,"props":1479,"children":1480},{},[1481,1483,1489,1491,1497,1499,1504,1506,1511,1513,1518],{"type":47,"value":1482},"Save to ",{"type":42,"tag":64,"props":1484,"children":1486},{"className":1485},[],[1487],{"type":47,"value":1488},"reports\u002F{TICKER}_earnings_prep_{UPCOMING_CQ}.html",{"type":47,"value":1490}," (e.g., ",{"type":42,"tag":64,"props":1492,"children":1494},{"className":1493},[],[1495],{"type":47,"value":1496},"AAPL_earnings_prep_2026Q1.html",{"type":47,"value":1498},") using the HTML report template from ",{"type":42,"tag":64,"props":1500,"children":1502},{"className":1501},[],[1503],{"type":47,"value":77},{"type":47,"value":1505},". The period in the filename is the ",{"type":42,"tag":58,"props":1507,"children":1508},{},[1509],{"type":47,"value":1510},"upcoming calendar quarter",{"type":47,"value":1512}," being prepped for — the one AFTER ",{"type":42,"tag":64,"props":1514,"children":1516},{"className":1515},[],[1517],{"type":47,"value":129},{"type":47,"value":1519},". Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.",{"type":42,"tag":43,"props":1521,"children":1522},{},[1523],{"type":47,"value":1524},"The report should include:",{"type":42,"tag":108,"props":1526,"children":1527},{},[1528,1533,1538,1543,1548,1553,1558,1563,1568,1573,1578],{"type":42,"tag":112,"props":1529,"children":1530},{},[1531],{"type":47,"value":1532},"Executive summary (2-3 sentences: what quarter is coming, what the key debate is, what the whisper number implies)",{"type":42,"tag":112,"props":1534,"children":1535},{},[1536],{"type":47,"value":1537},"Last quarter recap (story + key metrics table)",{"type":42,"tag":112,"props":1539,"children":1540},{},[1541],{"type":47,"value":1542},"Outstanding guidance table with source citations",{"type":42,"tag":112,"props":1544,"children":1545},{},[1546],{"type":47,"value":1547},"Whisper number calculation with historical beat\u002Fmiss detail table",{"type":42,"tag":112,"props":1549,"children":1550},{},[1551],{"type":47,"value":1552},"Peer read-throughs (grouped by Competitors \u002F Suppliers \u002F Customers \u002F Industry, with Daloopa citations on peer data)",{"type":42,"tag":112,"props":1554,"children":1555},{},[1556],{"type":47,"value":1557},"Key metrics to watch (table with specific thresholds)",{"type":42,"tag":112,"props":1559,"children":1560},{},[1561],{"type":47,"value":1562},"Consensus & positioning summary",{"type":42,"tag":112,"props":1564,"children":1565},{},[1566],{"type":47,"value":1567},"Historical earnings reaction table",{"type":42,"tag":112,"props":1569,"children":1570},{},[1571],{"type":47,"value":1572},"Macro & sector backdrop (bulleted list with directional tags)",{"type":42,"tag":112,"props":1574,"children":1575},{},[1576],{"type":47,"value":1577},"Potential surprises & call catalysts",{"type":42,"tag":112,"props":1579,"children":1580},{},[1581],{"type":47,"value":1582},"Pre-earnings checklist (prominently styled — this is the payoff of the whole report)",{"type":42,"tag":43,"props":1584,"children":1585},{},[1586,1588],{"type":47,"value":1587},"All financial figures must use Daloopa citation format: ",{"type":42,"tag":64,"props":1589,"children":1591},{"className":1590},[],[1592],{"type":47,"value":1593},"\u003Ca href=\"https:\u002F\u002Fdaloopa.com\u002Fsrc\u002F{fundamental_id}\">$X.XX million\u003C\u002Fa>",{"type":42,"tag":43,"props":1595,"children":1596},{},[1597],{"type":47,"value":1598},"Tell the user where the HTML report was saved.",{"type":42,"tag":43,"props":1600,"children":1601},{},[1602],{"type":47,"value":1603},"Highlight what makes this print particularly interesting: Is the whisper number meaningfully above guidance (setting up for disappointment even on a beat)? Are peer read-throughs conflicting (creating genuine uncertainty)? Is there a potential surprise catalyst that could overshadow the numbers? Give the analyst the single most important thing to watch.",{"items":1605,"total":1726},[1606,1624,1640,1652,1672,1694,1714],{"slug":1607,"name":1607,"fn":1608,"description":1609,"org":1610,"tags":1611,"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},[1612,1615,1618,1621],{"name":1613,"slug":1614,"type":15},"Accessibility","accessibility",{"name":1616,"slug":1617,"type":15},"Charts","charts",{"name":1619,"slug":1620,"type":15},"Data Visualization","data-visualization",{"name":1622,"slug":1623,"type":15},"Design","design",{"slug":1625,"name":1625,"fn":1626,"description":1627,"org":1628,"tags":1629,"stars":25,"repoUrl":26,"updatedAt":1639},"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},[1630,1633,1636],{"name":1631,"slug":1632,"type":15},"Agents","agents",{"name":1634,"slug":1635,"type":15},"Browser Automation","browser-automation",{"name":1637,"slug":1638,"type":15},"Testing","testing","2026-04-06T18:41:03.44016",{"slug":1641,"name":1641,"fn":1642,"description":1643,"org":1644,"tags":1645,"stars":25,"repoUrl":26,"updatedAt":1651},"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},[1646,1647,1650],{"name":1634,"slug":1635,"type":15},{"name":1648,"slug":1649,"type":15},"Local Development","local-development",{"name":1637,"slug":1638,"type":15},"2026-04-06T18:41:17.526867",{"slug":1653,"name":1653,"fn":1654,"description":1655,"org":1656,"tags":1657,"stars":25,"repoUrl":26,"updatedAt":1671},"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},[1658,1659,1662,1665,1668],{"name":1631,"slug":1632,"type":15},{"name":1660,"slug":1661,"type":15},"Cloudflare Workers","cloudflare-workers",{"name":1663,"slug":1664,"type":15},"SDK","sdk",{"name":1666,"slug":1667,"type":15},"Serverless","serverless",{"name":1669,"slug":1670,"type":15},"WebSockets","websockets","2026-04-06T18:39:51.717063",{"slug":1673,"name":1673,"fn":1674,"description":1675,"org":1676,"tags":1677,"stars":25,"repoUrl":26,"updatedAt":1693},"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},[1678,1681,1684,1687,1690],{"name":1679,"slug":1680,"type":15},"Frontend","frontend",{"name":1682,"slug":1683,"type":15},"React","react",{"name":1685,"slug":1686,"type":15},"shadcn\u002Fui","shadcn-ui",{"name":1688,"slug":1689,"type":15},"UI Components","ui-components",{"name":1691,"slug":1692,"type":15},"Vercel","vercel","2026-04-06T18:40:59.619419",{"slug":1695,"name":1695,"fn":1696,"description":1697,"org":1698,"tags":1699,"stars":25,"repoUrl":26,"updatedAt":1713},"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},[1700,1703,1706,1709,1712],{"name":1701,"slug":1702,"type":15},"AI Infrastructure","ai-infrastructure",{"name":1704,"slug":1705,"type":15},"Cost Optimization","cost-optimization",{"name":1707,"slug":1708,"type":15},"LLM","llm",{"name":1710,"slug":1711,"type":15},"Performance","performance",{"name":1691,"slug":1692,"type":15},"2026-04-06T18:40:44.377464",{"slug":1715,"name":1715,"fn":1716,"description":1717,"org":1718,"tags":1719,"stars":25,"repoUrl":26,"updatedAt":1725},"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},[1720,1721,1724],{"name":1704,"slug":1705,"type":15},{"name":1722,"slug":1723,"type":15},"Database","database",{"name":1707,"slug":1708,"type":15},"2026-04-06T18:41:08.513425",600,{"items":1728,"total":1925},[1729,1750,1773,1790,1806,1823,1842,1854,1868,1882,1894,1909],{"slug":1730,"name":1730,"fn":1731,"description":1732,"org":1733,"tags":1734,"stars":1747,"repoUrl":1748,"updatedAt":1749},"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},[1735,1738,1741,1744],{"name":1736,"slug":1737,"type":15},"Documents","documents",{"name":1739,"slug":1740,"type":15},"Healthcare","healthcare",{"name":1742,"slug":1743,"type":15},"Insurance","insurance",{"name":1745,"slug":1746,"type":15},"Regulatory Compliance","regulatory-compliance",28169,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fopenai-agents-python","2026-04-16T05:11:39.180399",{"slug":1751,"name":1751,"fn":1752,"description":1753,"org":1754,"tags":1755,"stars":1770,"repoUrl":1771,"updatedAt":1772},"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},[1756,1759,1761,1764,1767],{"name":1757,"slug":1758,"type":15},".NET","dotnet",{"name":1760,"slug":1751,"type":15},"ASP.NET Core",{"name":1762,"slug":1763,"type":15},"Blazor","blazor",{"name":1765,"slug":1766,"type":15},"C#","csharp",{"name":1768,"slug":1769,"type":15},"Web Development","web-development",23787,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills","2026-04-12T05:07:02.819491",{"slug":1774,"name":1774,"fn":1775,"description":1776,"org":1777,"tags":1778,"stars":1770,"repoUrl":1771,"updatedAt":1789},"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},[1779,1782,1785,1788],{"name":1780,"slug":1781,"type":15},"Apps SDK","apps-sdk",{"name":1783,"slug":1784,"type":15},"ChatGPT","chatgpt",{"name":1786,"slug":1787,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-04-12T05:07:05.468097",{"slug":1791,"name":1791,"fn":1792,"description":1793,"org":1794,"tags":1795,"stars":1770,"repoUrl":1771,"updatedAt":1805},"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},[1796,1799,1802],{"name":1797,"slug":1798,"type":15},"API Development","api-development",{"name":1800,"slug":1801,"type":15},"CLI","cli",{"name":1803,"slug":1804,"type":15},"Codex","codex","2026-04-12T05:07:04.132762",{"slug":1807,"name":1807,"fn":1808,"description":1809,"org":1810,"tags":1811,"stars":1770,"repoUrl":1771,"updatedAt":1822},"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},[1812,1815,1818,1819],{"name":1813,"slug":1814,"type":15},"Cloudflare","cloudflare",{"name":1816,"slug":1817,"type":15},"Cloudflare Pages","cloudflare-pages",{"name":1660,"slug":1661,"type":15},{"name":1820,"slug":1821,"type":15},"Deployment","deployment","2026-04-12T05:07:14.275118",{"slug":1824,"name":1824,"fn":1825,"description":1826,"org":1827,"tags":1828,"stars":1770,"repoUrl":1771,"updatedAt":1841},"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},[1829,1832,1835,1838],{"name":1830,"slug":1831,"type":15},"Productivity","productivity",{"name":1833,"slug":1834,"type":15},"Project Management","project-management",{"name":1836,"slug":1837,"type":15},"Strategy","strategy",{"name":1839,"slug":1840,"type":15},"Task Management","task-management","2026-05-23T06:17:16.870838",{"slug":1843,"name":1843,"fn":1844,"description":1845,"org":1846,"tags":1847,"stars":1770,"repoUrl":1771,"updatedAt":1853},"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},[1848,1849,1851,1852],{"name":1622,"slug":1623,"type":15},{"name":1850,"slug":1843,"type":15},"Figma",{"name":1679,"slug":1680,"type":15},{"name":1786,"slug":1787,"type":15},"2026-04-12T05:06:47.939943",{"slug":1855,"name":1855,"fn":1856,"description":1857,"org":1858,"tags":1859,"stars":1770,"repoUrl":1771,"updatedAt":1867},"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},[1860,1861,1864,1865,1866],{"name":1622,"slug":1623,"type":15},{"name":1862,"slug":1863,"type":15},"Design System","design-system",{"name":1850,"slug":1843,"type":15},{"name":1679,"slug":1680,"type":15},{"name":1688,"slug":1689,"type":15},"2026-05-10T05:59:52.971881",{"slug":1869,"name":1869,"fn":1870,"description":1871,"org":1872,"tags":1873,"stars":1770,"repoUrl":1771,"updatedAt":1881},"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},[1874,1875,1876,1879,1880],{"name":1622,"slug":1623,"type":15},{"name":1862,"slug":1863,"type":15},{"name":1877,"slug":1878,"type":15},"Documentation","documentation",{"name":1850,"slug":1843,"type":15},{"name":1679,"slug":1680,"type":15},"2026-05-16T06:07:47.821474",{"slug":1883,"name":1883,"fn":1884,"description":1885,"org":1886,"tags":1887,"stars":1770,"repoUrl":1771,"updatedAt":1893},"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},[1888,1889,1890,1891,1892],{"name":1622,"slug":1623,"type":15},{"name":1850,"slug":1843,"type":15},{"name":1679,"slug":1680,"type":15},{"name":1688,"slug":1689,"type":15},{"name":1768,"slug":1769,"type":15},"2026-05-16T06:07:40.583615",{"slug":1895,"name":1895,"fn":1896,"description":1897,"org":1898,"tags":1899,"stars":1770,"repoUrl":1771,"updatedAt":1908},"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},[1900,1903,1904,1907],{"name":1901,"slug":1902,"type":15},"Animation","animation",{"name":1803,"slug":1804,"type":15},{"name":1905,"slug":1906,"type":15},"Creative","creative",{"name":1622,"slug":1623,"type":15},"2026-05-02T05:31:48.48485",{"slug":1910,"name":1910,"fn":1911,"description":1912,"org":1913,"tags":1914,"stars":1770,"repoUrl":1771,"updatedAt":1924},"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},[1915,1916,1917,1920,1923],{"name":1905,"slug":1906,"type":15},{"name":1622,"slug":1623,"type":15},{"name":1918,"slug":1919,"type":15},"Image Generation","image-generation",{"name":1921,"slug":1922,"type":15},"Images","images",{"name":9,"slug":8,"type":15},"2026-05-15T06:23:24.312127",675]