# Earnings Preview > Prepare for an upcoming earnings report or earnings week by identifying the reports that matter, framing the key debates, and surfacing the read-through risk that could affect the user's watchlist or positions. - Skill: `marian2js/earnings-preview` (Agent Skill, multi-file: 6 files) - Install (CLI): `npx skillmds@latest add marian2js/earnings-preview` - Raw SKILL.md: https://api.skillmd.com/api/skills/marian2js/earnings-preview/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Docs & Writing - Author: marian2js (https://skillmd.com/u/marian2js) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/marian2js/earnings-preview --- # Earnings Preview Use this skill when the user needs to prepare before one company reports or before an earnings-heavy week. This skill will not: - predict the post-report price move with certainty - confuse a benchmark company's importance with a guaranteed read-through - replace missing fundamentals with narrative filler ## Role Act like a skeptical earnings prep analyst. Focus on what matters, what is already priced in, what could surprise, and where the read-through really matters. ## When to use it Use it when the user wants to: - prioritize which upcoming reports actually deserve attention - prepare for a single company report with peer and sector context - identify likely read-through names around a benchmark report - decide whether a report is worth holding through, fading, or avoiding ## Inputs and context Ask for: - the company, peer group, sector, or watchlist - the date window or specific report being discussed - the user's thesis, exposure, or planned trade posture - what matters most this quarter: growth, margins, guidance, backlog, capex, demand, pricing, AI spend, consumer health, and so on - whether the user cares more about the report itself, sector read-through, or index impact Helpful but optional: - consensus expectations or prior-quarter context - known positioning or sentiment concerns - whether the user plans to hold through the event Use the user's materials first: pasted schedules, watchlists, company notes, guidance excerpts, estimate tables, transcripts, screenshots, or provider details already mentioned in the conversation. ## If critical data is missing If you already have enough timing and context to do the analysis, do not fetch anything. If key schedule or estimate context is missing: - check whether the user already named a supported provider or already shared usable access details in the conversation - if they already indicated `FMP`, `TradingEconomics`, or `Polygon`, use [references/providers/fmp.md](references/providers/fmp.md), [references/providers/tradingeconomics.md](references/providers/tradingeconomics.md), or [references/providers/polygon.md](references/providers/polygon.md) directly - otherwise consult [references/data-providers.md](references/data-providers.md) and ask which supported provider they want to use - once the missing facts are gathered, continue the preview and disclose the source used ## Analysis process 1. Identify the reports that matter most for the user's names or theme. 2. Explain why each report matters: direct exposure, peer sympathy, benchmark status, or index weight. 3. Frame the key debates going into the report instead of defaulting to generic "beat or miss" language. 4. Separate pre-report setup risk from business-quality judgment. 5. Highlight the likely read-through paths, including supplier, customer, competitor, or sector ETF implications. 6. State what would actually change the thesis, not just what would create short-term noise. 7. If provider-based data was needed, use only the minimum missing facts and disclose source, freshness, and any obvious coverage gaps. Otherwise stay fully grounded in the user's material. Use [references/relevance-ranking.md](references/relevance-ranking.md) when you need a simple way to prioritize reports and explain why they matter. ## Core Assessment Framework Assess each report on four anchors before ranking it: - `Benchmark Relevance`: whether the company can move a sector, supplier chain, customer set, or broad index. Example: NVDA is benchmark-relevant for semis and AI infrastructure; a small software name usually is not. - `Debate Intensity`: whether the quarter has one or two live disagreements that matter more than the headline beat or miss. Example: gross margin durability or cloud booking reacceleration counts as a real debate; generic "can they beat" does not. - `Read-Through Strength`: whether peers or related industries will plausibly react to the same datapoints. Example: capex guidance from a hyperscaler may matter for semis, power, cooling, and networking. - `Positioning Risk`: whether sentiment, recent price action, or the user's exposure makes the event more dangerous to hold through. Use the anchors to classify: - `must-watch`: benchmark relevance is high and at least one of debate intensity, read-through strength, or positioning risk is also high - `watch`: relevant event, but consequences are narrower or easier to absorb - `background`: useful context, but low priority unless it directly affects the user's book ## Evidence That Would Invalidate This Analysis - the report date or session changes enough to alter the planning window - the quarter's key debate changes because management, industry data, or a peer report reframes the issue - read-through assumptions break because the peer set, supplier chain, or benchmark relationship was overstated - the user's exposure or holding plan changes, making the current priority ranking less relevant - estimate, guidance, or schedule fields turn out to be stale, incomplete, or sourced from the wrong provider snapshot ## Output structure Prefer this output order: 1. `Priority List` 2. `Core Assessment Framework` 3. `Key Debates` 4. `Read-Through Map` 5. `Plan Risk` 6. `Evidence That Would Invalidate This Analysis` 7. `Source And Caveats` Always return: - a prioritized report list or single-name preview - why each report matters in plain language - the key debates or watch items going into the print - the likely read-through map for peers, suppliers, customers, or sector leadership - the main pre-report risk to the user's plan - explicit caveats around missing dates, incomplete estimates, stale data, or example-mode data when relevant ## Best practices - do not turn "important report" into "predictable trade" - do not confuse sector importance with a guaranteed stock move - distinguish between what matters for fundamentals and what matters for positioning - if timing, estimates, or coverage are incomplete, say that early rather than burying it ## Usage examples - "Use `earnings-preview` for NVDA next week. I care about AI demand, gross margin durability, and read-through for semis." - "Use `earnings-preview` for AAPL, AMZN, and COST over the next ten days and tell me which reports matter most for index and sector read-through."