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Read, create, and review PDFs with checks of both content and appearance. Uses Python tools for document generation and text extraction, then inspects rendered page images for spacing, alignment, and readability.
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Screen listed companies using seven financial measures covering profitability, cash flow, debt payments, and share dilution, which reduces existing shareholders' ownership. Produce comparison tables showing exclusions, exemptions, borderline results, and missing data to guide further research.
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Calculate advertising costs, revenue relative to ad spend, break-even targets, and budget forecasts. The skill makes inputs and formulas explicit, checks inconsistent data, and compares base, downside, and upside scenarios when uncertainty affects the decision.
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Plan advertising budget allocation, bidding, and spending pace using goals, financial constraints, and evidence about additional spending returns. Compare options and produce a plan with amounts, timing, owners, success measures, and triggers for reversing changes.
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Check generated PDFs against a page limit or target count, then adjust layout and regenerate as needed. Provides a repeatable workflow for tuning margins, images, tables, and text while respecting readability limits.
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Evaluate SaaS customer economics and cash efficiency using acquisition costs, customer lifetime value, margins, and payback periods. Compare segments and channels, estimate how long cash will last, and assess whether to expand spending or improve efficiency.
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Design reading interfaces that resemble archival books, pairing serif text and aged paper surfaces with a dark catalog frame. Organize chapters, notes, and metadata through index navigation, with adjustable texture, page depth, and visual density.
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Analyze spending, revenue, and conversions across advertising channels to recommend budget shifts. Compare overall efficiency with the revenue gained from additional spending, identify saturation, and produce a gradual reallocation plan with monitoring priorities.
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Plan how to divide your advertising budget across Google and Meta channels using recent results. Compare proposed allocations, expected conversions and revenue, and the return from additional spending in each channel.
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Compare project options by valuing costs and benefits over time. Report net present value, the value remaining after discounted costs, separately for society and the sponsor, alongside funding needs and tests of how assumptions affect results.
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Analyze a company's most recent (or a specified past) earnings report from Yahoo Finance data (yfinance): actual vs estimated EPS, surprise size, revenue and margin trends, and the stock's price reaction. Use this skill whenever the user asks how earnings went — beat or miss, earnings surprise, quarterly results, the post-earnings move, or an earnings call recap — including casual references to a past report such as "AMZN reported last night" or "how did they do". For an upcoming report, use earnings-preview.
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Price changes within the store's guardrails, rate recommendations from demand, occupancy, or sell-through pace, promotions with their scope, depth, and dates, the markdown option for stock or capacity that is not selling, and the margin preview before any of it is staged. Not needed for explaining why revenue moved (performance-insights) or writing promotional copy (marketing-campaigns).
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Use when evaluating business model viability, analyzing profitability per customer/product/transaction, validating startup metrics (CAC, LTV, payback period), making pricing decisions, assessing scalability, comparing business models, or when user mentions unit economics, CAC/LTV ratio, contribution margin, customer profitability, break-even analysis, or needs to determine if a business can be profitable at scale.
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Use when choosing or evaluating a startup revenue model, pricing/value metric, packaging/tier design, or calculating unit economics (LTV, CAC, payback, gross margin, NRR), including usage-based/credit/AI pricing and variable compute/COGS constraints.
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Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
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Comprehensive quality control for flow cytometry and CyTOF data. Covers flow rate stability, signal drift, margin events, dead cell exclusion, and batch QC. Use when assessing acquisition quality or identifying problematic samples before analysis.
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Create a spacing scale from a base unit with rules for when each step applies. Use when standardising padding and margins. For page-level columns and gutters, use `layout-grid`.
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Define a responsive grid — columns, gutters, margins, and breakpoint behaviour. Use when establishing page structure. For the spacing scale inside components use `spacing-system`; for cross-device behaviour use `responsive-design`.
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Score every decision point with a Thoroughness Rating (1-10). AI makes the marginal cost of doing things properly near-zero — pick the higher-rated option every time. Includes scope checks to distinguish contained vs unbounded work.
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Establishes whether the business makes money on each customer or unit — contribution margin, acquisition cost, payback period, lifetime value, and the cohort behavior underneath. Use this to assess whether growth is profitable, evaluate a channel or segment, support a pricing decision, judge how fast the business can afford to grow, or diagnose why revenue growth is not producing profit.
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Use when evaluating Seth Klarman-style deep value and distressed opportunities: extreme margin of safety, forced sellers, liquidity discounts, complexity, downside protection, and patience.
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Use when evaluating Benjamin Graham-style deep value: net-nets, working capital bargains, margin of safety, statistical cheapness, and balance-sheet protection.
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Use when evaluating a business through Buffett-style ownership, owner earnings, durable moat, management quality, capital allocation, and margin-of-safety judgment.
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Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.
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