investment-memo-craft
Codex-only writing and layout overlay for AI Berkshire investment research reports. Use whenever Codex creates, rewrites, revises, or critiques company/industry/fund research reports, especially long-form Markdown reports that need financial rigor, readable business mechanics, contrarian analysis, valuation-to-action guidance, investor-specific recommendations, restrained typography, and clear buy/hold/sell signals. Do not use this to modify Claude Code slash-command sources.
git clone --depth 1 https://github.com/xbtlin/ai-berkshire /tmp/investment-memo-craft && cp -r /tmp/investment-memo-craft/codex-skills/investment-memo-craft ~/.claude/skills/investment-memo-craftSKILL.md
# Investment Memo Craft ## Purpose Turn investment research into a decision-ready Codex research report. Keep the data discipline of the underlying research skill, but make the output easier for an investor to use: concrete business mechanics, sharp inverse thinking, explicit opportunity cost, action thresholds, and calm Markdown typography. Use this as a writing and judgment overlay. It does not replace financial-data rules, primary-source checks, valuation tools, or report audit tooling. For long-form AI Berkshire outputs, title the artifact as a "research report" by default. Use "investment memo" only when the user explicitly asks for a memo format. This is a Codex-only hand-written skill kept under `codex-skills/` for simple installation. Do not add a same-named `skills/investment-memo-craft.md` source unless intentionally adopting this workflow for Claude Code too. ## Core Workflow 1. Open with context; reserve the full decision for after the evidence. - In the first screen, state the research date, price, market cap, valuation, and a short thesis. - Do not front-load the full buy/hold/sell table unless the user explicitly asks for an executive memo. - Put the detailed recommendation, investor-specific actions, and price bands near the end, after business quality, risk, and valuation have been argued. - Separate "good business" from "good investment at this price". 2. Build the operating map before the philosophy. - Include revenue structure, segment economics, unit drivers, and 3-5 year trends early. - For asset-heavy businesses, show the key assets individually when they explain the moat. - Explain the pricing mechanism, customer lock-in, cost structure, and reinvestment needs. 3. Compress business essence into one memorable sentence. - Prefer a sentence that describes who pays, why they pay, what is scarce, and what repeats. - Avoid generic labels such as "industry leader" unless followed by the mechanism that makes leadership durable. 4. Make the moat falsifiable. - Score or table the moat by source: brand/pricing power, switching cost, network effect, scale, cost advantage, regulation, resource scarcity, technology. - Explain whether the moat widened or narrowed over the last 5 years. - Ask what can destroy the moat, even if the answer is "not competitors, but regulation/weather/price paid". 5. Do real inverse thinking. - Include failure paths with probability, impact, and observable indicators. - Write the strongest bear case in language a smart short seller or non-buyer would actually use. - Explicitly identify the most likely analytical mistake. 6. Evaluate management through capital allocation. - Replace vague praise with decision history: acquisitions, divestitures, buybacks, dividends, leverage, reinvestment, strategic pivots. - Judge incentives: insider ownership, controlling shareholder behavior, compensation, related-party transactions, and shareholder return policy. - Ask whether the business depends on a person or on a system. 7. Connect industry trend to value capture. - Distinguish civilization-level trend from investable company-level economics. - Describe where the company sits in the value chain and who captures the profit pool. - Identify whether TAM growth, pricing, utilization, or capital intensity is the real driver. 8. Convert valuation into action. - Show current multiples, reverse DCF intuition, scenario valuation, historical comparison, and comparable companies when relevant. - Include dividends or capital returns in expected return when they matter. - Provide price bands, add signals, trim/sell signals, and what would change the thesis. 9. Close with a decision memo. - Include a summary table by business quality, moat, management, risk, trend, and valuation. - Give distinct advice for empty-handed investors and existing holders. - Include the action table here, not at the top, for long-form research reports. - End by separating AI analysis confidence from actual investment certainty. ## Style Standards - Prefer concrete numbers and mechanisms over adjectives. - Use tables when they reduce cognitive load: assets, segments, failure paths, management decisions, scenario valuations, action bands. - Write in clear investor prose. A good memo should be understandable after one read and useful after one month. - Keep memorable formulations, but never let rhetoric outrun evidence. - Avoid hiding behind vague labels such as "wait and see" without specifying the price or event that would change the recommendation. ## Layout Standards For long-form research reports, prefer a calm stepped layout: - Use a simple title: `公司名(ticker)研究报告`. Avoid adding "四大师综合" or "投资备忘录" to the title unless the user asks for that framing. - Use dated filenames for reports: `公司名研究报告-YYYYMMDD.md`. - Start with one compact metadata block: research date, price, market cap, key multiples, and a one-sentence thesis. - Use horizontal separators between major sections. - Use Chinese step headings for readability, for example "第一步:核心数据总览", "第二步:生意本质分析", and "第八步:最终决策与行动清单". - Keep section titles short and concrete; avoid dense numbering such as "2.3.1" unless the document is technical. - Use quote blocks for master-style questions, not inline bold paragraphs. - Treat GitHub Markdown as the typography system: use heading levels, tables, quote blocks, and bold text; do not add HTML/CSS font styling unless the user explicitly asks for a non-GitHub artifact. - Use bold sparingly as a reading guide: metadata labels, one-sentence conclusion labels, key phrases, total/current-company rows, latest-year values, scenario target prices, action rows, and audit verdicts. - Keep ordinary facts in normal weight. Do not bold full tables or every important-looking number; over-emphasis makes long research feel noisy. - Use explicit `+` and `-` signs for growth rates and return ranges so positive/negative mo
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