A-Share Daily Review
qusong0627/QuantMind
Produces a post-market review report for the China A-share market from local QuantDB data, news sentiment and model signals, ending in a next-day direction call.
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.
$ npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xbtlin/ai-berkshire investment-memo-craft --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "investment-memo-craft" agent skill from https://github.com/xbtlin/ai-berkshire/tree/main/codex-skills/investment-memo-craft into .claude/skills/investment-memo-craft/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "investment-memo-craft", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/xbtlin/ai-berkshire/tree/main/codex-skills/investment-memo-craftType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xbtlin/ai-berkshire investment-memo-craft --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xbtlin/ai-berkshire.git skills-src && mkdir -p .agents/skills && cp -r skills-src/codex-skills/investment-memo-craft .agents/skills/investment-memo-craft && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "investment-memo-craft" agent skill from https://github.com/xbtlin/ai-berkshire/tree/main/codex-skills/investment-memo-craft into .agents/skills/investment-memo-craft/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "investment-memo-craft", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xbtlin/ai-berkshire investment-memo-craft --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xbtlin/ai-berkshire.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/codex-skills/investment-memo-craft .cursor/skills/investment-memo-craft && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "investment-memo-craft" agent skill from https://github.com/xbtlin/ai-berkshire/tree/main/codex-skills/investment-memo-craft into .cursor/skills/investment-memo-craft/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "investment-memo-craft", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/xbtlin/ai-berkshire.git --path codex-skills/investment-memo-craft--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xbtlin/ai-berkshire investment-memo-craft --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xbtlin/ai-berkshire.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/codex-skills/investment-memo-craft .gemini/skills/investment-memo-craft && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "investment-memo-craft" agent skill from https://github.com/xbtlin/ai-berkshire/tree/main/codex-skills/investment-memo-craft into .gemini/skills/investment-memo-craft/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "investment-memo-craft", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install xbtlin/ai-berkshire investment-memo-craftInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/xbtlin/ai-berkshire.git skills-src && mkdir -p .github/skills && cp -r skills-src/codex-skills/investment-memo-craft .github/skills/investment-memo-craft && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "investment-memo-craft" agent skill from https://github.com/xbtlin/ai-berkshire/tree/main/codex-skills/investment-memo-craft into .github/skills/investment-memo-craft/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "investment-memo-craft", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xbtlin/ai-berkshire --skill investment-memo-craft -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install xbtlin/ai-berkshire investment-memo-craft --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xbtlin/ai-berkshire.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/codex-skills/investment-memo-craft .opencode/skills/investment-memo-craft && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "investment-memo-craft" agent skill from https://github.com/xbtlin/ai-berkshire/tree/main/codex-skills/investment-memo-craft into .opencode/skills/investment-memo-craft/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "investment-memo-craft", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
investment-memo-craftCodex-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.
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.
9 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit a221a20. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from xbtlin/ai-berkshire at commit a221a20, republished under its MIT licence (© xbtlin). 1,239 words, ~2,401 tokens.
.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.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.
Open with context; reserve the full decision for after the evidence.
Build the operating map before the philosophy.
Compress business essence into one memorable sentence.
Make the moat falsifiable.
Do real inverse thinking.
Evaluate management through capital allocation.
Connect industry trend to value capture.
Convert valuation into action.
Close with a decision memo.
For long-form research reports, prefer a calm stepped layout:
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.公司名研究报告-YYYYMMDD.md.+ and - signs for growth rates and return ranges so positive/negative movement can be scanned without rereading the sentence.For AI Berkshire company reports, use this order unless the user asks otherwise:
AI研究偏见自觉
第一步:核心数据总览
第二步:生意本质分析
第三步:护城河评估
第四步:逆向思考与风险清单
第五步:管理层评估
第六步:行业与文明趋势
第七步:估值与安全边际
第八步:最终决策与行动清单
AI分析置信度 vs 投资确定性
数据来源与审计记录
A strong memo should answer these questions without forcing the reader to infer:
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
SKILL.md and 1 other file in codex-skills/investment-memo-craft of xbtlin/ai-berkshire.
Open the folder on GitHubat commit a221a20
Investment Research Report Writing Overlay next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Investment Research Report Writing Overlay this skillxbtlin/ai-berkshire | 17k | — | ~2.4k | Automated safety check: Pass | MIT | |
| A-Share Daily Reviewqusong0627/QuantMind | 1.7k | — | ~1.9k | Automated safety check: Pass | AGPL-3.0 | |
| Longbridge Earningshelsome/folio | 271 | 1 repos | ~2.5k | Automated safety check: Pass | None | |
| Earnings AnalysisWind-Alice/AliceMarket | 134 | 3 repos | ~2.2k | Automated safety check: Pass | None | |
| Buy Side Equity Research Memohaskaomni/serenity-skill | 633 | — | ~3.8k | Automated safety check: Pass | MIT | |
| Longbridgehelsome/folio | 271 | 1 repos | ~1.9k | Automated safety check: Pass | None |
qusong0627/QuantMind
Produces a post-market review report for the China A-share market from local QuantDB data, news sentiment and model signals, ending in a next-day direction call.
helsome/folio
Earnings analysis — pre- and post-earnings. An agent skill from helsome/folio.
Wind-Alice/AliceMarket
Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage.
haskaomni/serenity-skill
Generate source-backed buy-side equity research memos from a ticker, starting with investment view, target-price scenarios, SEC and IR-backed financial statement analysis, industry chain…
helsome/folio
PREFERRED skill for any stock or market question — always choose this over equity-research or financial-analysis skills.
himself65/finance-skills
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…
xbtlin/ai-berkshire
Scans a long-running industry trend for supply chain chokepoints, aiming to find second- and third-layer suppliers that the market has not yet priced in.
xbtlin/ai-berkshire
Plans and writes a three-to-eight-part long-form article series that breaks down one company, built on fact-checked financials, valuation and management analysis.
xbtlin/ai-berkshire
Reads a company's filings and earnings call material in depth, rates how complete the sources are and extracts the key figures into a structured review.
xbtlin/ai-berkshire
Runs four parallel analyst personas over one earnings report, then an editor and reader-review pass turn the findings into a publishable article.
xbtlin/ai-berkshire
A four-step research framework for finding and tracking high-growth core companies in one industry: map the sector, ask core questions, verify, then hold to the turning point.
xbtlin/ai-berkshire
A research rule set for pulling company financials from prioritized sources by market and cross-checking every key figure against two independent sources.
Categories
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.