Agent skill

Investment Research Report Writing Overlay

by xbtlin in xbtlin/ai-berkshire

Codex-only writing overlay that reshapes value-investing research into a decision-ready report: operating mechanics first, a falsifiable moat score, and the recommendation near the end.

MITAuto-check passedBusiness, Finance & HR

Install Investment Research Report Writing Overlay

skills CLI
$ npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install xbtlin/ai-berkshire investment-memo-craft --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/xbtlin/ai-berkshire.git skills-src && mkdir -p .claude/skills && cp -r skills-src/codex-skills/investment-memo-craft .claude/skills/investment-memo-craft && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
investment-memo-craft
GitHub stars
17k
Token cost
~2.4k tokens
SKILL.md length
1,239 words
Files
2
Skills in repo
22
Repo updated
First seen
Licence
MIT

At a glance

Codex-only writing overlay that reshapes value-investing research into a decision-ready report: operating mechanics first, a falsifiable moat score, and the recommendation near the end.

  • Works in 9 steps: Open with context; reserve the full… → Build the operating map before the… → Compress business essence into one… → …
  • Turning raw investment research into a decision-ready long-form report
  • SKILL.md covers Purpose, Core Workflow, Style Standards and Layout Standards, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

This skill is a writing and judgment layer for AI Berkshire research reports, used after the underlying research skill has already gathered the financial data, primary sources and valuation. It opens a report with the research date, price, market cap and a short thesis, but holds the detailed buy, hold or sell recommendation and specific price bands until after business quality, risk and valuation have been argued, keeping good business and good investment at this price as separate questions.

Ahead of that it builds an operating map of revenue structure, segment economics and multi-year trends, compresses the business into one memorable sentence about who pays and why, and scores the moat by source, brand or pricing power, switching cost, network effect, scale, cost advantage, regulation or resource scarcity, stating whether it widened or narrowed over five years. It also requires real inverse thinking: failure paths with a probability, an impact and an observable indicator. The output is normally titled a research report, reserving investment memo for when you explicitly ask for that format, and it runs only in Codex, not as a Claude Code slash command source.

When your agent uses it

  • Turning raw investment research into a decision-ready long-form report
  • Writing a falsifiable moat analysis for a company
  • Structuring a report so the recommendation comes after the evidence, not before
  • Doing inverse thinking on an investment thesis with scored failure paths

Example prompts

  • “Rewrite this draft research report on the company so the operating mechanics come before the recommendation.”
  • “Score this company's moat by source and say whether it is widening or narrowing.”
  • “Add an inverse-thinking section to this memo with failure paths and their probability and impact.”

Requirements

  • Codex (this skill is Codex-only)
  • An underlying investment research skill that supplies the financial data

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Open with context; reserve the full decision for after the evidence.
  2. Build the operating map before the philosophy.
  3. Compress business essence into one memorable sentence.
  4. Make the moat falsifiable.
  5. Do real inverse thinking.
  6. Evaluate management through capital allocation.
  7. Connect industry trend to value capture.
  8. Convert valuation into action.
  9. Close with a decision memo.

What it can do on your machine

Read from SKILL.md and the folder at commit a221a20. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Investment Research Report Writing Overlay loads about 2.4k tokens when it runs. Until then it costs about 126 tokens; SKILL.md has 1,239 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~126
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from xbtlin/ai-berkshire at commit a221a20, republished under its MIT licence (© xbtlin). 1,239 words, ~2,401 tokens.

Download SKILL.mdSave it as .claude/skills/investment-memo-craft/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
investment-memo-craft
description
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.

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.
Show full SKILL.md (607 more words)Show less

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 movement can be scanned without rereading the sentence.
  • Put checklists under "AI research bias awareness" when the company is information-rich or consensus-heavy.
  • Keep audit and tool details light at the end. Do not expose command lines unless the user asks for reproducibility commands.
  • If a prior report has a layout the user likes, preserve its reading rhythm while keeping only data that passes the current validation standard.

Default Report Shape

For AI Berkshire company reports, use this order unless the user asks otherwise:

  1. AI研究偏见自觉

    • State the information-richness rating, consensus trap, bias checklist, and AI research limitation.
  2. 第一步:核心数据总览

    • Show segment revenue, key operating assets or units, 3-5 year financial trend, and cross-source validation.
  3. 第二步:生意本质分析

    • Define the business in one sentence, map revenue/cost/customer/asset life/growth drivers, and explain the real profit variables.
  4. 第三步:护城河评估

    • Score moat sources, explain evidence, and state what can destroy or weaken the moat.
  5. 第四步:逆向思考与风险清单

    • Put the bear case in serious language. Include failure paths, probability, impact, and observable warning indicators.
  6. 第五步:管理层评估

    • Judge management through capital allocation, governance, incentives, dividends/buybacks, leverage, and whether the business is system-driven.
  7. 第六步:行业与文明趋势

    • Separate broad trend from investable economics and explain where the company captures value.
  8. 第七步:估值与安全边际

    • Show current valuation, reverse-DCF intuition, scenario valuation, comparable companies if useful, and explicit price bands.
  9. 第八步:最终决策与行动清单

    • Put the full decision here, not at the top: summary table, advice for empty-handed investors, advice for holders, add/sell triggers, and master-style comments if useful.
  10. AI分析置信度 vs 投资确定性

    • Separate data confidence from investment certainty.
  11. 数据来源与审计记录

    • List key sources and concise audit results. Keep command lines out of the report unless explicitly requested.

Quality Bar

A strong memo should answer these questions without forcing the reader to infer:

  • What exactly does this company sell, to whom, and why does money repeat?
  • What are the 2-3 variables that actually move profit?
  • Why might smart people refuse to buy?
  • What is already priced in?
  • What return is plausible under bull/base/bear cases, including dividends if relevant?
  • What should an empty-handed investor do?
  • What should a holder do?
  • What evidence would make the thesis wrong?

Pairing With Other Skills

When the task requires fresh company research, first use the relevant data/research skill and its validation requirements. Then use this skill to rewrite or structure the output as a memo.

For AI Berkshire work, pair especially with:

  • financial-data for source hierarchy and cross-source validation.
  • investment-research for the Buffett/Munger/Duan/Li Lu framework.
  • management-deep-dive when management quality is the core uncertainty.
  • report_audit.py before treating a report as publishable.

© xbtlin, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in codex-skills/investment-memo-craft of xbtlin/ai-berkshire.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit a221a20

Compare with similar skills

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Longbridgehelsome/folio2711 repos~1.9kAutomated safety check: PassNone

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Questions about Investment Research Report Writing Overlay

What does Investment Research Report Writing Overlay do?

Codex-only writing overlay that reshapes value-investing research into a decision-ready report: operating mechanics first, a falsifiable moat score, and the recommendation near the end. This skill is a writing and judgment layer for AI Berkshire research reports, used after the underlying research skill has already gathered the financial data, primary sources and valuation. It opens a report with the research date, price, market cap and a short thesis, but holds the detailed buy, hold or sell recommendation and specific price bands until after business quality, risk and valuation have been argued, keeping good business and good investment at this price as separate questions.

When should I use Investment Research Report Writing Overlay?

Investment Research Report Writing Overlay fits situations like: turning raw investment research into a decision-ready long-form report; writing a falsifiable moat analysis for a company; structuring a report so the recommendation comes after the evidence, not before; doing inverse thinking on an investment thesis with scored failure paths.

How do I install Investment Research Report Writing Overlay in Claude Code?

Run `npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a claude-code`. Or copy the skill folder (codex-skills/investment-memo-craft in xbtlin/ai-berkshire) into .claude/skills/investment-memo-craft in your project. Claude Code loads it when a task matches its description.

How do I install Investment Research Report Writing Overlay in Codex?

Run `npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a codex`. Or copy the skill folder (codex-skills/investment-memo-craft in xbtlin/ai-berkshire) into .agents/skills/investment-memo-craft in your project. Codex loads it when a task matches its description.

Can I use Investment Research Report Writing Overlay in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/investment-memo-craft, .gemini/skills/investment-memo-craft, .github/skills/investment-memo-craft and .opencode/skills/investment-memo-craft in your project.

What does Investment Research Report Writing Overlay need to run?

SKILL.md names no scripts, command-line tools or credentials: Investment Research Report Writing Overlay is instructions for the agent only. Our summary lists: Codex (this skill is Codex-only); An underlying investment research skill that supplies the financial data.

Does Investment Research Report Writing Overlay access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Investment Research Report Writing Overlay safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Investment Research Report Writing Overlay use?

Investment Research Report Writing Overlay is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Investment Research Report Writing Overlay use?

About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Investment Research Report Writing Overlay?

Skills that share tags, products or a category with Investment Research Report Writing Overlay: A-Share Daily Review (qusong0627/QuantMind, 1.7k stars), Longbridge Earnings (helsome/folio, 271 stars), Earnings Analysis (Wind-Alice/AliceMarket, 134 stars) and Buy Side Equity Research Memo (haskaomni/serenity-skill, 633 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Investment Research Report Writing Overlay?

xbtlin (a GitHub user) maintains it in xbtlin/ai-berkshire, which has 16,676 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 8, 2026.

Source: xbtlin/ai-berkshire on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.