[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-openai-earnings-preview":3,"mdc-w5jcfh-key":36,"related-repo-openai-earnings-preview":1111,"related-org-openai-earnings-preview":1213},{"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-preview","generate pre-earnings preview reports","Use when preparing full pre-earnings preview reports with executive summary, expectation bar, guidance credibility, KPI dashboard, scenarios, and call questions. Do not use after results or for short summaries unless the user explicitly asks for a summary\u002Fshort version.",{"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},"Reporting","reporting","tag",{"name":17,"slug":18,"type":15},"Finance","finance",{"name":20,"slug":21,"type":15},"KPI","kpi",{"name":23,"slug":24,"type":15},"Forecasting","forecasting",4888,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins","2026-08-28T15:09:08.100169",null,661,[],{"repoUrl":26,"stars":25,"forks":29,"topics":32,"description":33},[],"OpenAI Plugins","https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins\u002Ftree\u002FHEAD\u002Fplugins\u002Fpublic-equity-investing\u002Fskills\u002Fearnings-preview","---\nname: earnings-preview\ndescription: Use when preparing full pre-earnings preview reports with executive summary, expectation bar, guidance credibility, KPI dashboard, scenarios, and call questions. Do not use after results or for short summaries unless the user explicitly asks for a summary\u002Fshort version.\n---\n\n# Earnings Preview\n\n## Skill Configuration\n\n### Common Skill Instructions\n\nMANDATORY: Before searching connectors, retrieving evidence, or drafting output, read and apply the shared runtime contract in `..\u002Fpublic-equity-investing\u002FSKILL.md## Cross-Skill Runtime Contract`. Then check the router skill map and `..\u002F..\u002Fshared\u002Fplugin-routing-playbook.md` for adjacent skills that should be sequenced with this workflow. Do not run user-context setup or inspection during ordinary workflow work; route only explicit saved-context, source-setup, onboarding, or automation-setup requests to `..\u002Fuser-context\u002FSKILL.md`.\n\n### Source Resolution\n\nLoad `..\u002F..\u002Fshared\u002Fworkflow-source-resolution.md`. Resolve only the categories needed for this workflow: `company_filings_ir`, `earnings_transcripts_presentations`, `internal_research`, `portfolio_models_trackers`, and `market_data_estimates`. Use the shared runtime contract to map each attempted category to an available app, connector, file, export, or user-provided input.\n\n## Relevant Dependency Categories\n\nThese are the source categories most likely to matter for this workflow. Use the router contract to resolve only the categories the task actually needs, prefer user-named sources first, and state any material source limitation.\n\n- `Earnings Transcripts & Events`\n- `Company Filings & IR`\n- `Market Data & Estimates`\n- `Internal Research`\n\n## Internal Support\n\nWhen this workflow needs rendering, evidence\u002Fdata preparation, style, or sector context, route support through the visible `public-equity-investing` router and its bundled internal playbooks. Route workbook or model QA through the visible `model-audit-tieout` workflow.\n\n## Deliverable Intake\n\nBefore source gathering or analysis for a new substantive hero deliverable, load `..\u002F..\u002Fshared\u002Fdeliverable-intake-policy.md` and use its adaptive `request_user_input` preflight for materially unresolved format, depth, audience\u002Fuse, or focus choices. For an explicit pre-earnings preview, full preview report, or reusable\u002Fsource-heavy pre-print package, the default resolves the presentation surface to a polished standalone HTML pre-earnings report unless the user requests an alternate surface, a quick\u002Fno-file answer, or workbook\u002Fmodel output. In interactive runs, ask only remaining material choices such as depth, audience\u002Fuse, or focus; in non-interactive runs, default to the HTML pre-earnings report and `Full working analysis` while disclosing those assumptions outside the artifact. Reuse resolved preferences in downstream steps; when acting only as input to an owning workflow, do not re-prompt.\n\nProduce a full, decision-grade pre-print report by default: executive summary first, then what the market expects, what can move the stock, what must be answered on the call, and what evidence is missing.\n\n## Route\n\n- `full preview report`: default route for any pre-earnings preview request. For an explicit pre-earnings preview, full preview report, or reusable\u002Fsource-heavy pre-print package, produce a polished standalone HTML pre-earnings report following `..\u002F..\u002Fshared\u002Fhtml-artifact-standard.md`; let the named investor question determine the hierarchy. Always surface the expectation bar, stock-reaction drivers, key evidence, call watch items, source posture, and missing evidence. Add KPI trajectories, guidance credibility, peer\u002Fsector read-throughs, macro context, market events, reaction\u002Foptions context, bull\u002Fbase\u002Fbear cases, and extended call questions only when relevant and source-supported.\n- `explicit short summary`: use only when the user explicitly asks for `summary`, `short`, `quick read`, `one-pager`, `top things to watch`, or similar compression. Do not maintain this as a separate tear-sheet artifact; pare back the full preview report while preserving freeze time, source posture, key bar numbers, top debates, call questions, and missing evidence.\n- `standardized dashboard`: use only when the user explicitly asks for a standardized dashboard, reusable dashboard template, PM cockpit, tabbed dashboard, or structured payload-driven render. Keep this skill as the analysis owner and hand the resulting `public_equity_investing_dashboard.v1` payload to `dashboard-builder`. Use `references\u002FDASHBOARD_PACK.md` for module mapping.\n- `deterministic export pack`: only when requested or plan-driven; validate local inputs, run packaged scripts, and write support artifacts such as `preview_note.md`, `exports.xlsx`, `exports\u002F*.csv`, `qa_report.*`, and `run_manifest.json`. The workbook or rendered dashboard\u002Freport is the hero artifact; CSV\u002FJSON\u002FMarkdown sidecars are support\u002Faudit files unless explicitly requested.\n\nLoad `references\u002FREFERENCE_ROUTER.md` first, then only the smallest reference needed for the chosen route.\n\n## Non-Negotiables\n\n- State freeze time and source timestamps for consensus, whisper, options, price\u002Freaction, and other time-sensitive inputs.\n- Never fabricate numbers, dates, guidance, option data, peer read-throughs, or whisper color.\n- Separate company\u002FSEC\u002FIR facts, consensus, whisper, analyst inference, user assumptions, and web fallback.\n- Keep GAAP\u002Fnon-GAAP labels, units, scale, period mapping, and KPI definitions explicit.\n- Identify EPS-quality landmines before the print: tax rate, share count, equity-investment marks, FX, asset sales, impairments, restructuring, litigation, non-operating income\u002Fexpense, and any mismatch between GAAP EPS, adjusted EPS, and consensus basis.\n- Include the last reported baseline and the consensus\u002Fguide bar where sourced. Include quarterly key metrics and growth trajectory when they sharpen the investor question or the stock-reaction setup rather than as mandatory display inventory.\n- For dashboard handoffs, include the earnings visualization pack only when source-backed data exists: quarterly revenue, gross profit, net income, and the best source-backed profitability margin history; estimated EPS versus actual EPS for the past five quarters; and equity-price history annotated with material market events. Omit any chart whose required series is missing, stale, or not comparable, and surface that gap in `missing_evidence`.\n- Treat the margin line in financial trend charts as part of the pre-print risk setup. Default to net margin only when net income is a fair recurring-profitability proxy. Prefer operating margin or another issuer-specific source-backed margin when net income has been distorted by tax, equity-investment marks, FX, asset sales, impairments, restructuring, litigation, or other non-operating items. State the selected `margin_metric`, `margin_label`, and `margin_rationale` in dashboard payloads when using a line other than net margin.\n- Rank dashboard highlights by investor salience rather than mechanical size. If a growth rate, acceleration, surprise %, guide delta, backlog, or normalized metric is what matters for the stock, use that as the highlighted value and put the absolute value in the supporting detail.\n- Include major news coverage and market events when they can affect the earnings setup, guide credibility, estimate bar, multiple, positioning, or call questions. Scan the last quarter, the last twelve months, and forward-looking anticipated events; cite every event and label uncertain windows.\n- Use primary company\u002FSEC\u002FIR and connected sources before general web; label fallback sources.\n- Do not imply MNPI or confidential whisper data; weak whisper support becomes qualitative setup language.\n- Without sourced implied move, relevant positioning\u002Fcontext, and adequate consensus or whisper evidence for the stated question, provide an earnings setup and reaction framework rather than a trade-ready position instruction. Use `Wait for proof`, `Monitor`, or similarly evidence-calibrated language where appropriate.\n- Treat an options-implied move as an earnings reaction bar only when the contract tenor reasonably isolates the earnings event. If the available expiry includes substantial pre-event trading time or another material catalyst window, label the metric as `expiry-tenor volatility context`, explain the limitation, and do not feature it as a first-read earnings-move tile unless the limitation is immediately prominent.\n- Do not create optional exports or support files unless requested or plan-driven. The workflow-resolved standalone HTML pre-earnings report is the planned hero artifact for an explicit full preview request.\n- Do not shorten the default preview just because some inputs are missing; keep full analysis of the investment question and label unavailable optional modules or inputs explicitly.\n\n## Workflow\n\n1. Classify route. Default to `full preview report` unless the user explicitly asks for a summary\u002Fshort format.\n2. Anchor the preview quarter; map `t`, `t-1`, `t-4`, and `t-8`.\n3. Freeze sources\u002Ftimestamps and normalize units, GAAP\u002Fnon-GAAP basis, KPI definitions, and source posture.\n4. Identify 3-6 stock-moving KPIs and build the expectation bar: consensus, guide, whisper if sourced, prior setup, key-metric baseline, growth trajectory, EPS-quality watch items, and base framing.\n5. Add guidance credibility, peer read-throughs, reaction\u002Foptions, macro\u002Fsector context, and major news\u002Fmarket events when relevant and sourced. Separate company-specific events from peer, macro, regulatory, legal, FX\u002Frates, commodity, industry, and upcoming catalyst events.\n6. Build supportable bull\u002Fbase\u002Fbear framing and write only decision-relevant call questions with listen-fors and falsifiers. Convert material news\u002Fevent items into call questions when they create a contradiction or open diligence item.\n7. Run QA for executive-summary coverage, freeze time, period consistency, source labels, units\u002Fscale, chart\u002Fdisplay unit agreement, readable citation placement, cited event claims, missing evidence, and unresolved placeholders.\n\n## Sub-agent decomposition\n\nFor complex medium\u002Flarge requests, use sub-agents where available; otherwise emulate the split as named workstreams. Suggested lanes: source and consensus freeze, KPI\u002Fguide bar, peer\u002Fmacro\u002Freaction context, scenarios, call questions, and QA. Keep this skill as the lead: reconcile conflicts, source labels, assumptions, open items, final QA, and the user-facing answer.\n\n\n## Deterministic Contract\n\nScripts are local materializers; they do not fetch data or replace analyst judgment.\n\n- Required inputs: `company_master.csv`, `fiscal_period_index.csv`, `reported_financials.csv`, `kpi_timeseries.csv`, `consensus_estimates.csv`.\n- Required for full scripted pack: `guidance_history.csv` and canonical event file `event_calendar.csv` can be empty but must exist with headers.\n- Optional inputs: `whisper_estimates.csv`, `price_returns.csv`, `options_snapshot.csv`, `qual_notes.csv`, `scenario_assumptions.csv`.\n- Schema source: `references\u002FSCHEMAS.md` plus `assets\u002Fplan_schema.json`.\n- Generated Markdown support notes must not contain unresolved bracket tokens, `TODO`, or unfinished placeholders.\n- `exports.xlsx` starts with `Cover`, a dashboard sheet summarizing company\u002Fticker, preview period, freeze time, workbook mode, warnings, consensus bar, bull\u002Fbase\u002Fbear revenue and EPS, KPI dashboard row counts, call watch item, input file count, and workbook map.\n\n## Handoffs\n\nUse `financial-source-of-truth` for evidence conflicts, `financials-normalizer` for messy tables, `scenario-sensitivity-generator` for deeper cases, `dashboard-builder` for responsive pre-earnings dashboard rendering, `earnings-deep-dive` after the print, `equity-model-update` for model refreshes, `long-short-pitch` for trade expression, and `memo-builder` for formal memos.\n\n## HTML Guidance\n\nFor a substantive HTML full preview report, load `..\u002F..\u002Fshared\u002Fhtml-artifact-standard.md` and apply these preview-specific requirements:\n\n- Lead with the expectation bar and the stock-reaction debate. If the user names a specific issue, such as AI memory demand, put that issue and its reaction drivers ahead of broad KPI archives or general diligence sections.\n- Use four to six first-read tiles only when each has a distinct decision job, such as event timing, guide\u002Fconsensus bar, operating proof point, market setup, an event-isolating implied move when available, or most important evidence gap.\n- Make visible what is known, what the market likely requires, what could surprise, and what evidence is missing before taking incremental event risk.\n- Include detailed KPI dashboards, peer\u002Fmacro context, historical reactions, options\u002Fimplied-move analysis, scenario maps, and extended call-question lists only when relevant and source-backed. Do not force a fixed dashboard module inventory into a flexible report.\n- Match chart axes and labels to the units stated in the adjacent headings or tables. Omit a misleading chart rather than mixing units or scales.\n- Keep citations traceable but readable; do not fragment dates, times, ticker symbols, product names, or product specifications into separately linked characters or tokens.\n- Visually inspect the HTML according to the shared artifact standard before delivery and iterate on hierarchy, legibility, clipping, crowding, citation noise, and whether the requested investment question is immediately visible.\n\n## Public Equity PM Judgment Layer\n\nFor substantial previews, load `shared\u002Fpm-judgment-heuristics.md` before finalizing. Audience modes: `long_only_pm`, `long_short_hf`, `sell_side_research`, `etf_index_diligence`, `public_equity_diligence`.\n\nDefault PM question: is the bar beatable, does it matter for the stock, and what would change sizing into or after the print?\n\nRequired PM judgment:\n- State the expectation bar, consensus dispersion, guidance setup, implied move or reaction risk when available, and the estimate-revision path.\n- Separate company fundamentals from stock setup: what is priced in, what the market may be ignoring, and what would make a bad print buyable or a good print fadeable.\n- Include call-question falsifiers, listen-for items, and position actions: `add`, `press`, `hold`, `trim`, `exit`, `hedge`, `watchlist`, or `wait for proof`.\n- For ETF\u002Findex diligence, include constituent weight, passive ownership\u002Fflow relevance, liquidity, benchmark exposure, and rebalance\u002Fevent risk when relevant.\n",{"data":37,"body":38},{"name":4,"description":6},{"type":39,"children":40},"root",[41,49,56,63,94,100,151,157,162,203,209,230,236,265,270,276,427,439,445,580,586,660,666,671,677,682,837,843,911,917,929,967,973,1021,1026,1031],{"type":42,"tag":43,"props":44,"children":45},"element","h1",{"id":4},[46],{"type":47,"value":48},"text","Earnings Preview",{"type":42,"tag":50,"props":51,"children":53},"h2",{"id":52},"skill-configuration",[54],{"type":47,"value":55},"Skill Configuration",{"type":42,"tag":57,"props":58,"children":60},"h3",{"id":59},"common-skill-instructions",[61],{"type":47,"value":62},"Common Skill Instructions",{"type":42,"tag":64,"props":65,"children":66},"p",{},[67,69,76,78,84,86,92],{"type":47,"value":68},"MANDATORY: Before searching connectors, retrieving evidence, or drafting output, read and apply the shared runtime contract in ",{"type":42,"tag":70,"props":71,"children":73},"code",{"className":72},[],[74],{"type":47,"value":75},"..\u002Fpublic-equity-investing\u002FSKILL.md## Cross-Skill Runtime Contract",{"type":47,"value":77},". Then check the router skill map and ",{"type":42,"tag":70,"props":79,"children":81},{"className":80},[],[82],{"type":47,"value":83},"..\u002F..\u002Fshared\u002Fplugin-routing-playbook.md",{"type":47,"value":85}," for adjacent skills that should be sequenced with this workflow. Do not run user-context setup or inspection during ordinary workflow work; route only explicit saved-context, source-setup, onboarding, or automation-setup requests to ",{"type":42,"tag":70,"props":87,"children":89},{"className":88},[],[90],{"type":47,"value":91},"..\u002Fuser-context\u002FSKILL.md",{"type":47,"value":93},".",{"type":42,"tag":57,"props":95,"children":97},{"id":96},"source-resolution",[98],{"type":47,"value":99},"Source Resolution",{"type":42,"tag":64,"props":101,"children":102},{},[103,105,111,113,119,121,127,128,134,135,141,143,149],{"type":47,"value":104},"Load ",{"type":42,"tag":70,"props":106,"children":108},{"className":107},[],[109],{"type":47,"value":110},"..\u002F..\u002Fshared\u002Fworkflow-source-resolution.md",{"type":47,"value":112},". Resolve only the categories needed for this workflow: ",{"type":42,"tag":70,"props":114,"children":116},{"className":115},[],[117],{"type":47,"value":118},"company_filings_ir",{"type":47,"value":120},", ",{"type":42,"tag":70,"props":122,"children":124},{"className":123},[],[125],{"type":47,"value":126},"earnings_transcripts_presentations",{"type":47,"value":120},{"type":42,"tag":70,"props":129,"children":131},{"className":130},[],[132],{"type":47,"value":133},"internal_research",{"type":47,"value":120},{"type":42,"tag":70,"props":136,"children":138},{"className":137},[],[139],{"type":47,"value":140},"portfolio_models_trackers",{"type":47,"value":142},", and ",{"type":42,"tag":70,"props":144,"children":146},{"className":145},[],[147],{"type":47,"value":148},"market_data_estimates",{"type":47,"value":150},". Use the shared runtime contract to map each attempted category to an available app, connector, file, export, or user-provided input.",{"type":42,"tag":50,"props":152,"children":154},{"id":153},"relevant-dependency-categories",[155],{"type":47,"value":156},"Relevant Dependency Categories",{"type":42,"tag":64,"props":158,"children":159},{},[160],{"type":47,"value":161},"These are the source categories most likely to matter for this workflow. Use the router contract to resolve only the categories the task actually needs, prefer user-named sources first, and state any material source limitation.",{"type":42,"tag":163,"props":164,"children":165},"ul",{},[166,176,185,194],{"type":42,"tag":167,"props":168,"children":169},"li",{},[170],{"type":42,"tag":70,"props":171,"children":173},{"className":172},[],[174],{"type":47,"value":175},"Earnings Transcripts & Events",{"type":42,"tag":167,"props":177,"children":178},{},[179],{"type":42,"tag":70,"props":180,"children":182},{"className":181},[],[183],{"type":47,"value":184},"Company Filings & IR",{"type":42,"tag":167,"props":186,"children":187},{},[188],{"type":42,"tag":70,"props":189,"children":191},{"className":190},[],[192],{"type":47,"value":193},"Market Data & Estimates",{"type":42,"tag":167,"props":195,"children":196},{},[197],{"type":42,"tag":70,"props":198,"children":200},{"className":199},[],[201],{"type":47,"value":202},"Internal Research",{"type":42,"tag":50,"props":204,"children":206},{"id":205},"internal-support",[207],{"type":47,"value":208},"Internal Support",{"type":42,"tag":64,"props":210,"children":211},{},[212,214,220,222,228],{"type":47,"value":213},"When this workflow needs rendering, evidence\u002Fdata preparation, style, or sector context, route support through the visible ",{"type":42,"tag":70,"props":215,"children":217},{"className":216},[],[218],{"type":47,"value":219},"public-equity-investing",{"type":47,"value":221}," router and its bundled internal playbooks. Route workbook or model QA through the visible ",{"type":42,"tag":70,"props":223,"children":225},{"className":224},[],[226],{"type":47,"value":227},"model-audit-tieout",{"type":47,"value":229}," workflow.",{"type":42,"tag":50,"props":231,"children":233},{"id":232},"deliverable-intake",[234],{"type":47,"value":235},"Deliverable Intake",{"type":42,"tag":64,"props":237,"children":238},{},[239,241,247,249,255,257,263],{"type":47,"value":240},"Before source gathering or analysis for a new substantive hero deliverable, load ",{"type":42,"tag":70,"props":242,"children":244},{"className":243},[],[245],{"type":47,"value":246},"..\u002F..\u002Fshared\u002Fdeliverable-intake-policy.md",{"type":47,"value":248}," and use its adaptive ",{"type":42,"tag":70,"props":250,"children":252},{"className":251},[],[253],{"type":47,"value":254},"request_user_input",{"type":47,"value":256}," preflight for materially unresolved format, depth, audience\u002Fuse, or focus choices. For an explicit pre-earnings preview, full preview report, or reusable\u002Fsource-heavy pre-print package, the default resolves the presentation surface to a polished standalone HTML pre-earnings report unless the user requests an alternate surface, a quick\u002Fno-file answer, or workbook\u002Fmodel output. In interactive runs, ask only remaining material choices such as depth, audience\u002Fuse, or focus; in non-interactive runs, default to the HTML pre-earnings report and ",{"type":42,"tag":70,"props":258,"children":260},{"className":259},[],[261],{"type":47,"value":262},"Full working analysis",{"type":47,"value":264}," while disclosing those assumptions outside the artifact. Reuse resolved preferences in downstream steps; when acting only as input to an owning workflow, do not re-prompt.",{"type":42,"tag":64,"props":266,"children":267},{},[268],{"type":47,"value":269},"Produce a full, decision-grade pre-print report by default: executive summary first, then what the market expects, what can move the stock, what must be answered on the call, and what evidence is missing.",{"type":42,"tag":50,"props":271,"children":273},{"id":272},"route",[274],{"type":47,"value":275},"Route",{"type":42,"tag":163,"props":277,"children":278},{},[279,298,345,380],{"type":42,"tag":167,"props":280,"children":281},{},[282,288,290,296],{"type":42,"tag":70,"props":283,"children":285},{"className":284},[],[286],{"type":47,"value":287},"full preview report",{"type":47,"value":289},": default route for any pre-earnings preview request. For an explicit pre-earnings preview, full preview report, or reusable\u002Fsource-heavy pre-print package, produce a polished standalone HTML pre-earnings report following ",{"type":42,"tag":70,"props":291,"children":293},{"className":292},[],[294],{"type":47,"value":295},"..\u002F..\u002Fshared\u002Fhtml-artifact-standard.md",{"type":47,"value":297},"; let the named investor question determine the hierarchy. Always surface the expectation bar, stock-reaction drivers, key evidence, call watch items, source posture, and missing evidence. Add KPI trajectories, guidance credibility, peer\u002Fsector read-throughs, macro context, market events, reaction\u002Foptions context, bull\u002Fbase\u002Fbear cases, and extended call questions only when relevant and source-supported.",{"type":42,"tag":167,"props":299,"children":300},{},[301,307,309,315,316,322,323,329,330,336,337,343],{"type":42,"tag":70,"props":302,"children":304},{"className":303},[],[305],{"type":47,"value":306},"explicit short summary",{"type":47,"value":308},": use only when the user explicitly asks for ",{"type":42,"tag":70,"props":310,"children":312},{"className":311},[],[313],{"type":47,"value":314},"summary",{"type":47,"value":120},{"type":42,"tag":70,"props":317,"children":319},{"className":318},[],[320],{"type":47,"value":321},"short",{"type":47,"value":120},{"type":42,"tag":70,"props":324,"children":326},{"className":325},[],[327],{"type":47,"value":328},"quick read",{"type":47,"value":120},{"type":42,"tag":70,"props":331,"children":333},{"className":332},[],[334],{"type":47,"value":335},"one-pager",{"type":47,"value":120},{"type":42,"tag":70,"props":338,"children":340},{"className":339},[],[341],{"type":47,"value":342},"top things to watch",{"type":47,"value":344},", or similar compression. Do not maintain this as a separate tear-sheet artifact; pare back the full preview report while preserving freeze time, source posture, key bar numbers, top debates, call questions, and missing evidence.",{"type":42,"tag":167,"props":346,"children":347},{},[348,354,356,362,364,370,372,378],{"type":42,"tag":70,"props":349,"children":351},{"className":350},[],[352],{"type":47,"value":353},"standardized dashboard",{"type":47,"value":355},": use only when the user explicitly asks for a standardized dashboard, reusable dashboard template, PM cockpit, tabbed dashboard, or structured payload-driven render. Keep this skill as the analysis owner and hand the resulting ",{"type":42,"tag":70,"props":357,"children":359},{"className":358},[],[360],{"type":47,"value":361},"public_equity_investing_dashboard.v1",{"type":47,"value":363}," payload to ",{"type":42,"tag":70,"props":365,"children":367},{"className":366},[],[368],{"type":47,"value":369},"dashboard-builder",{"type":47,"value":371},". Use ",{"type":42,"tag":70,"props":373,"children":375},{"className":374},[],[376],{"type":47,"value":377},"references\u002FDASHBOARD_PACK.md",{"type":47,"value":379}," for module mapping.",{"type":42,"tag":167,"props":381,"children":382},{},[383,389,391,397,398,404,405,411,412,418,419,425],{"type":42,"tag":70,"props":384,"children":386},{"className":385},[],[387],{"type":47,"value":388},"deterministic export pack",{"type":47,"value":390},": only when requested or plan-driven; validate local inputs, run packaged scripts, and write support artifacts such as ",{"type":42,"tag":70,"props":392,"children":394},{"className":393},[],[395],{"type":47,"value":396},"preview_note.md",{"type":47,"value":120},{"type":42,"tag":70,"props":399,"children":401},{"className":400},[],[402],{"type":47,"value":403},"exports.xlsx",{"type":47,"value":120},{"type":42,"tag":70,"props":406,"children":408},{"className":407},[],[409],{"type":47,"value":410},"exports\u002F*.csv",{"type":47,"value":120},{"type":42,"tag":70,"props":413,"children":415},{"className":414},[],[416],{"type":47,"value":417},"qa_report.*",{"type":47,"value":142},{"type":42,"tag":70,"props":420,"children":422},{"className":421},[],[423],{"type":47,"value":424},"run_manifest.json",{"type":47,"value":426},". 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Audience modes: ",{"type":42,"tag":70,"props":987,"children":989},{"className":988},[],[990],{"type":47,"value":991},"long_only_pm",{"type":47,"value":120},{"type":42,"tag":70,"props":994,"children":996},{"className":995},[],[997],{"type":47,"value":998},"long_short_hf",{"type":47,"value":120},{"type":42,"tag":70,"props":1001,"children":1003},{"className":1002},[],[1004],{"type":47,"value":1005},"sell_side_research",{"type":47,"value":120},{"type":42,"tag":70,"props":1008,"children":1010},{"className":1009},[],[1011],{"type":47,"value":1012},"etf_index_diligence",{"type":47,"value":120},{"type":42,"tag":70,"props":1015,"children":1017},{"className":1016},[],[1018],{"type":47,"value":1019},"public_equity_diligence",{"type":47,"value":93},{"type":42,"tag":64,"props":1022,"children":1023},{},[1024],{"type":47,"value":1025},"Default PM question: is the bar beatable, does it matter for the stock, and what would change sizing into or after the print?",{"type":42,"tag":64,"props":1027,"children":1028},{},[1029],{"type":47,"value":1030},"Required PM judgment:",{"type":42,"tag":163,"props":1032,"children":1033},{},[1034,1039,1044,1106],{"type":42,"tag":167,"props":1035,"children":1036},{},[1037],{"type":47,"value":1038},"State the expectation bar, consensus dispersion, guidance setup, implied move or reaction risk when available, and the estimate-revision path.",{"type":42,"tag":167,"props":1040,"children":1041},{},[1042],{"type":47,"value":1043},"Separate company fundamentals from stock setup: what is priced in, what the market may be ignoring, and what would make a bad print buyable or a good print fadeable.",{"type":42,"tag":167,"props":1045,"children":1046},{},[1047,1049,1055,1056,1062,1063,1069,1070,1076,1077,1083,1084,1090,1091,1097,1099,1105],{"type":47,"value":1048},"Include call-question falsifiers, listen-for items, and position actions: ",{"type":42,"tag":70,"props":1050,"children":1052},{"className":1051},[],[1053],{"type":47,"value":1054},"add",{"type":47,"value":120},{"type":42,"tag":70,"props":1057,"children":1059},{"className":1058},[],[1060],{"type":47,"value":1061},"press",{"type":47,"value":120},{"type":42,"tag":70,"props":1064,"children":1066},{"className":1065},[],[1067],{"type":47,"value":1068},"hold",{"type":47,"value":120},{"type":42,"tag":70,"props":1071,"children":1073},{"className":1072},[],[1074],{"type":47,"value":1075},"trim",{"type":47,"value":120},{"type":42,"tag":70,"props":1078,"children":1080},{"className":1079},[],[1081],{"type":47,"value":1082},"exit",{"type":47,"value":120},{"type":42,"tag":70,"props":1085,"children":1087},{"className":1086},[],[1088],{"type":47,"value":1089},"hedge",{"type":47,"value":120},{"type":42,"tag":70,"props":1092,"children":1094},{"className":1093},[],[1095],{"type":47,"value":1096},"watchlist",{"type":47,"value":1098},", or ",{"type":42,"tag":70,"props":1100,"children":1102},{"className":1101},[],[1103],{"type":47,"value":1104},"wait for proof",{"type":47,"value":93},{"type":42,"tag":167,"props":1107,"children":1108},{},[1109],{"type":47,"value":1110},"For ETF\u002Findex diligence, include constituent weight, passive ownership\u002Fflow relevance, liquidity, benchmark exposure, and rebalance\u002Fevent risk when relevant.",{"items":1112,"total":1212},[1113,1132,1148,1160,1175,1188,1200],{"slug":1114,"name":1114,"fn":1115,"description":1116,"org":1117,"tags":1118,"stars":25,"repoUrl":26,"updatedAt":1131},"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},[1119,1122,1125,1128],{"name":1120,"slug":1121,"type":15},"Accessibility","accessibility",{"name":1123,"slug":1124,"type":15},"Charts","charts",{"name":1126,"slug":1127,"type":15},"Data Visualization","data-visualization",{"name":1129,"slug":1130,"type":15},"Design","design","2026-06-30T19:00:57.102",{"slug":1133,"name":1133,"fn":1134,"description":1135,"org":1136,"tags":1137,"stars":25,"repoUrl":26,"updatedAt":1147},"adobe-batch-edit-photos","apply consistent photo adjustments","Apply consistent photo adjustments across a set of images so they look like they were edited together. Use this skill whenever the user says \"make my photos look cohesive\", \"give all these the same style\", \"apply a warm and golden feel to all of these\", \"make this cinematic\", \"match the look across my photos\", \"edit all my travel photos the same way\", \"batch edit these\", \"make these consistent\", \"fix my phone photos\", or uploads a folder of photos and wants a unified, polished result. Also triggers for requests like \"apply a preset to all of these\", \"make these look professional\", or \"they were shot in mixed lighting — can you fix them all\". Outputs direct final image URLs plus an in-chat preview grid and optional Firefly Board link. Access: 🔐 Signed-In required | Gen AI: ❌\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1138,1141,1144],{"name":1139,"slug":1140,"type":15},"Creative","creative",{"name":1142,"slug":1143,"type":15},"Editing","editing",{"name":1145,"slug":1146,"type":15},"Imaging","imaging","2026-08-28T15:09:11.185865",{"slug":1149,"name":1149,"fn":1150,"description":1151,"org":1152,"tags":1153,"stars":25,"repoUrl":26,"updatedAt":1159},"adobe-create-mockups","create product and scene mockups","Use when a user wants to see their logo, design, or sketch on a product or scene mockup — mugs, t-shirts, business cards, hats, phone screens, posters, billboards, or similar. Triggers on \"create mockups\", \"show my logo on products\", or any logo upload with a request to visualize it on items. Access: 🔐 Signed-In required | Gen AI: ✅ Adobe Firefly via `image_generate` used for design creation, sketch polishing, and mockup scene generation\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1154,1155,1156],{"name":1139,"slug":1140,"type":15},{"name":1129,"slug":1130,"type":15},{"name":1157,"slug":1158,"type":15},"Graphics","graphics","2026-08-28T15:09:07.42507",{"slug":1161,"name":1161,"fn":1162,"description":1163,"org":1164,"tags":1165,"stars":25,"repoUrl":26,"updatedAt":1174},"adobe-create-social-variations","export platform-ready social media assets","Resize, crop, or export any image or video into platform-ready social media assets using Adobe Creative Cloud tools. Use this skill when a user wants to prepare a photo, image, or video for one or more social platforms — Instagram, TikTok, LinkedIn, Facebook, YouTube, Snapchat, Pinterest, Threads, or X\u002FTwitter. Triggers on: \"prepare my image for Instagram\", \"resize for TikTok\", \"get this ready to post\", \"make versions for all platforms\", \"social media sizes\", \"crop for stories\", \"export for LinkedIn\", \"resize my video for social\", \"make social media assets\", or any request to adapt a photo or video for specific platforms. Handles subject-aware cropping, AI canvas expansion, test previews before full runs, and same-ratio video resizing.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1166,1167,1168,1171],{"name":1139,"slug":1140,"type":15},{"name":1157,"slug":1158,"type":15},{"name":1169,"slug":1170,"type":15},"Marketing","marketing",{"name":1172,"slug":1173,"type":15},"Social Media","social-media","2026-08-28T15:10:07.282096",{"slug":1176,"name":1176,"fn":1177,"description":1178,"org":1179,"tags":1180,"stars":25,"repoUrl":26,"updatedAt":1187},"adobe-design-from-template","create visual designs from templates","Create any visual design using Adobe Express templates — flyers, posters, social media posts (Instagram, Facebook, LinkedIn), business cards, invitations, greeting cards, resumes, cover letters, brochures, newsletters, certificates, presentations, YouTube thumbnails, email headers, logos, menus, and labels. Use this skill whenever the user wants to make, design, or build any visual — even if they just say \"make me a flyer\", \"design a poster\", \"I need something for Instagram\", \"create an event invite\", or \"make a business card\". Also handles browsing templates, editing text, replacing images, changing backgrounds, animating, and exporting designs. Access: 🔐 Signed-In required | Gen AI: ❌ by default — image replacement only where the surface permits generative AI (e.g. Codex); none on Claude\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1181,1182,1183,1184],{"name":1139,"slug":1140,"type":15},{"name":1129,"slug":1130,"type":15},{"name":1157,"slug":1158,"type":15},{"name":1185,"slug":1186,"type":15},"Templates","templates","2026-08-28T15:10:03.050113",{"slug":1189,"name":1189,"fn":1190,"description":1191,"org":1192,"tags":1193,"stars":25,"repoUrl":26,"updatedAt":1199},"adobe-edit-quick-cut","create video sizzle reels","Create a punchy sizzle reel from a video using Adobe Quick Cut. Use this skill whenever a user wants to cut, trim, or shorten a video into highlights — including phrases like \"make a sizzle reel\", \"make a highlight reel\", \"quick cut this\", \"cut the best parts\", \"shorten this video\", \"make a highlight clip\", \"summarize this video visually\", or any request to produce a shorter edited version of a video. Use this skill for Quick Cut requests before suggesting manual editing in Premiere. Requires the user to upload a video file.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1194,1195,1196],{"name":1139,"slug":1140,"type":15},{"name":1142,"slug":1143,"type":15},{"name":1197,"slug":1198,"type":15},"Video","video","2026-08-28T15:09:07.765245",{"slug":1201,"name":1201,"fn":1202,"description":1203,"org":1204,"tags":1205,"stars":25,"repoUrl":26,"updatedAt":1211},"adobe-retouch-portraits","batch retouch portrait photos","Bulk-retouch a folder of portrait photos using Adobe tools — designed for wedding photographers and event photographers who need fast, walk-away batch processing. Use this skill when the user says \"retouch my photos\", \"batch process these portraits\", \"process my wedding photos\", \"clean up this folder of images\", \"run my headshots through Adobe\", or uploads\u002Fselects a folder of photos and wants them polished and ready to review. Automatically applies auto-straighten, auto-tone, and auto-light to every image. Outputs a preview grid and download folder. Access: 🔐 Signed-In required | Gen AI: ❌ by default — optional background-only cleanup only where the surface permits generative AI (e.g. Codex); none on Claude\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1206,1207,1208],{"name":1139,"slug":1140,"type":15},{"name":1145,"slug":1146,"type":15},{"name":1209,"slug":1210,"type":15},"Photography","photography","2026-08-28T15:09:10.386974",499,{"items":1214,"total":1415},[1215,1236,1259,1276,1292,1311,1330,1344,1360,1374,1386,1399],{"slug":1216,"name":1216,"fn":1217,"description":1218,"org":1219,"tags":1220,"stars":1233,"repoUrl":1234,"updatedAt":1235},"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},[1221,1224,1227,1230],{"name":1222,"slug":1223,"type":15},"Documents","documents",{"name":1225,"slug":1226,"type":15},"Healthcare","healthcare",{"name":1228,"slug":1229,"type":15},"Insurance","insurance",{"name":1231,"slug":1232,"type":15},"Regulatory Compliance","regulatory-compliance",28169,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fopenai-agents-python","2026-08-02T05:48:07.395855",{"slug":1237,"name":1237,"fn":1238,"description":1239,"org":1240,"tags":1241,"stars":1256,"repoUrl":1257,"updatedAt":1258},"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},[1242,1245,1247,1250,1253],{"name":1243,"slug":1244,"type":15},".NET","dotnet",{"name":1246,"slug":1237,"type":15},"ASP.NET Core",{"name":1248,"slug":1249,"type":15},"Blazor","blazor",{"name":1251,"slug":1252,"type":15},"C#","csharp",{"name":1254,"slug":1255,"type":15},"Web Development","web-development",23787,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills","2026-04-12T05:07:02.819491",{"slug":1260,"name":1260,"fn":1261,"description":1262,"org":1263,"tags":1264,"stars":1256,"repoUrl":1257,"updatedAt":1275},"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},[1265,1268,1271,1274],{"name":1266,"slug":1267,"type":15},"Apps SDK","apps-sdk",{"name":1269,"slug":1270,"type":15},"ChatGPT","chatgpt",{"name":1272,"slug":1273,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-04-12T05:07:05.468097",{"slug":1277,"name":1277,"fn":1278,"description":1279,"org":1280,"tags":1281,"stars":1256,"repoUrl":1257,"updatedAt":1291},"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},[1282,1285,1288],{"name":1283,"slug":1284,"type":15},"API Development","api-development",{"name":1286,"slug":1287,"type":15},"CLI","cli",{"name":1289,"slug":1290,"type":15},"Codex","codex","2026-04-12T05:07:04.132762",{"slug":1293,"name":1293,"fn":1294,"description":1295,"org":1296,"tags":1297,"stars":1256,"repoUrl":1257,"updatedAt":1310},"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},[1298,1301,1304,1307],{"name":1299,"slug":1300,"type":15},"Cloudflare","cloudflare",{"name":1302,"slug":1303,"type":15},"Cloudflare Pages","cloudflare-pages",{"name":1305,"slug":1306,"type":15},"Cloudflare Workers","cloudflare-workers",{"name":1308,"slug":1309,"type":15},"Deployment","deployment","2026-04-12T05:07:14.275118",{"slug":1312,"name":1312,"fn":1313,"description":1314,"org":1315,"tags":1316,"stars":1256,"repoUrl":1257,"updatedAt":1329},"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},[1317,1320,1323,1326],{"name":1318,"slug":1319,"type":15},"Productivity","productivity",{"name":1321,"slug":1322,"type":15},"Project Management","project-management",{"name":1324,"slug":1325,"type":15},"Strategy","strategy",{"name":1327,"slug":1328,"type":15},"Task Management","task-management","2026-05-23T06:17:16.870838",{"slug":1331,"name":1331,"fn":1332,"description":1333,"org":1334,"tags":1335,"stars":1256,"repoUrl":1257,"updatedAt":1343},"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},[1336,1337,1339,1342],{"name":1129,"slug":1130,"type":15},{"name":1338,"slug":1331,"type":15},"Figma",{"name":1340,"slug":1341,"type":15},"Frontend","frontend",{"name":1272,"slug":1273,"type":15},"2026-04-12T05:06:47.939943",{"slug":1345,"name":1345,"fn":1346,"description":1347,"org":1348,"tags":1349,"stars":1256,"repoUrl":1257,"updatedAt":1359},"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},[1350,1351,1354,1355,1356],{"name":1129,"slug":1130,"type":15},{"name":1352,"slug":1353,"type":15},"Design System","design-system",{"name":1338,"slug":1331,"type":15},{"name":1340,"slug":1341,"type":15},{"name":1357,"slug":1358,"type":15},"UI Components","ui-components","2026-05-10T05:59:52.971881",{"slug":1361,"name":1361,"fn":1362,"description":1363,"org":1364,"tags":1365,"stars":1256,"repoUrl":1257,"updatedAt":1373},"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},[1366,1367,1368,1371,1372],{"name":1129,"slug":1130,"type":15},{"name":1352,"slug":1353,"type":15},{"name":1369,"slug":1370,"type":15},"Documentation","documentation",{"name":1338,"slug":1331,"type":15},{"name":1340,"slug":1341,"type":15},"2026-05-16T06:07:47.821474",{"slug":1375,"name":1375,"fn":1376,"description":1377,"org":1378,"tags":1379,"stars":1256,"repoUrl":1257,"updatedAt":1385},"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},[1380,1381,1382,1383,1384],{"name":1129,"slug":1130,"type":15},{"name":1338,"slug":1331,"type":15},{"name":1340,"slug":1341,"type":15},{"name":1357,"slug":1358,"type":15},{"name":1254,"slug":1255,"type":15},"2026-05-16T06:07:40.583615",{"slug":1387,"name":1387,"fn":1388,"description":1389,"org":1390,"tags":1391,"stars":1256,"repoUrl":1257,"updatedAt":1398},"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},[1392,1395,1396,1397],{"name":1393,"slug":1394,"type":15},"Animation","animation",{"name":1289,"slug":1290,"type":15},{"name":1139,"slug":1140,"type":15},{"name":1129,"slug":1130,"type":15},"2026-05-02T05:31:48.48485",{"slug":1400,"name":1400,"fn":1401,"description":1402,"org":1403,"tags":1404,"stars":1256,"repoUrl":1257,"updatedAt":1414},"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},[1405,1406,1407,1410,1413],{"name":1139,"slug":1140,"type":15},{"name":1129,"slug":1130,"type":15},{"name":1408,"slug":1409,"type":15},"Image Generation","image-generation",{"name":1411,"slug":1412,"type":15},"Images","images",{"name":9,"slug":8,"type":15},"2026-05-15T06:23:24.312127",578]