SuperAPI AI Directory

buffett-skills - Open-source Claude Code Skill collection, reproducing Buffett's decision-making

Author: AI小集 · Original source: AI工具集

What is buffett-skills

buffett-skills is an open-source Claude Code Skill collection built on Buffett's complete investment framework. buffett-skills distills 49 core concepts from the corpus of Buffett's shareholder letters into 8 reference files. Through progressive loading and three execution paths (quick screening, in-depth analysis, and topic-based Q&A), it enables AI to analyze any company using Buffett's decision-making process, outputting a structured report containing 10 fixed sections including moat, management, valuation, and margin of safety.

buffett-skills

Main features of buffett-skills

  • Automatic investment analysis triggering: Automatically activates when users analyze stocks, read financial reports, discuss buy or sell decisions, or evaluate moats, invoking the complete investment framework without explicitly mentioning "Buffett."
  • Progressive reference file loading: Uses a design of a SKILL.md main file paired with 8 topic-specific reference files, loading content such as moat, management, financial, or industry manuals only as needed, effectively controlling context costs.
  • Intelligent routing across three execution paths: The quick screening path uses an 8-question checklist to determine within 2 minutes whether a company is worth researching; the in-depth analysis path reads the moat, management, financial, and valuation files in sequence to complete a full assessment; the topic-based Q&A path directly locates a single concept file to answer precisely.
  • Moat scanning and trend assessment: Identifies five types of moats—cost advantage, switching costs, network effects, intangible assets, and scale efficiency—and determines whether they are widening or narrowing.
  • Three-dimensional management evaluation: Evaluates management quality and integrity across three dimensions—degree of promise fulfillment, capital allocation history, and alignment with shareholder interests—with a one-vote veto applied to dishonest management.
  • Core financial metric analysis: Focuses on Buffett-style financial metrics such as owner earnings, ROIC/ROE, and cash conversion rate, distinguishing accounting profit from real cash flow.
  • Valuation and margin of safety calculation: Uses three valuation methods to output the intrinsic value range, margin of safety percentage, and suggested entry price under optimistic, base, and pessimistic scenarios.
  • Mandatory structured output: Each in-depth analysis must output 10 fixed sections: conclusion, circle of competence, key assumptions, business quality, financial snapshot, valuation, sell criteria, major risks, monitoring indicators, and overall judgment.
  • Industry-specific manual support: Includes differentiated analysis manuals for industries such as insurance, banking, consumer, media, energy, railroads, and technology, invoking the corresponding evaluation logic for different industries.
  • Sell discipline check: For hold or sell decisions, mandatorily verifies against the four sell criteria one by one, ensuring that exit decisions also follow a systematic process.

How to use buffett-skills

  • Environment preparation: Ensure Claude Code is installed locally and that there is a project directory for storing the skill.
  • Download the project: Run git clone https://github.com/agi-now/buffett-skills /tmp/buffett-skills to clone the repository to a local temporary directory.
  • Deploy the Skill: Run cp -r /tmp/buffett-skills/skills/buffett your-project/.claude/skills/buffett, copying the buffett folder to the target project's .claude/skills/ path.
  • Verify the directory: Confirm that the directory structure strictly matches your-project/.claude/skills/buffett/SKILL.md and 8 reference files; Claude Code will automatically discover the skill under that path.
  • Getting started: Enter any company name, stock ticker, or investment analysis question in the Claude Code conversation, and the skill will be triggered automatically.
  • Select analysis mode: The system will automatically route to one of three paths based on the type of question: quick screening (2-minute 8-question checklist), in-depth analysis (complete 10-chapter report), or topical Q&A (precise answer to a single concept).

Key information and usage requirements for buffett-skills

  • Project nature: Open-source Claude Code Skill, not a standalone application
  • Reference sources: 49 concept pages from Buffett's shareholder letters and public writings from 1965 to the present
  • Installation requirements: Claude Code must already be installed, and the skill placement path must strictly conform to .claude/skills/<name>/SKILL.md
  • Trigger method: Automatic recognition; automatically activated when analyzing keywords such as stocks, financial reports, buy/sell decisions, moats, and management, without explicitly mentioning "Buffett"
  • Output format: Strict 10-chapter structured template (conclusion, circle of competence, key assumptions, business quality, financial snapshot, valuation, sell criteria, main risks, monitoring indicators, comprehensive judgment)
  • Performance cost: In-depth analysis consumes on average about 30,829 additional tokens and 59.2 seconds, with tool calls increasing from 2 to more than 11

Core advantages of buffett-skills

  • Process rather than conclusion: It does not provide follow-the-crowd advice on "what Buffett buys"; it reproduces his decision-making process so users understand why to buy or not buy.
  • Disciplined output: It mandates complete output of 10 chapters to avoid analysis omissions; when the business model is highly uncertain, it clearly gives the disciplined conclusion "cannot judge, observe, do not act."
  • Engineering-oriented design: Progressive loading solves the long-context cost problem, and three paths match different analysis depth requirements.
  • Significant measured results: In three test cases—Apple stock analysis, banking framework, and Moutai hold/sell—the pass rate with the Skill reached 100% (15/15), versus only 66.7% (10/15) without the Skill, an improvement of 33%.

Comparison of buffett-skills with similar competitors

Dimension buffett-skills buffett-oracle-analyzer ai-sub-invest (ConsensusAI)
Core positioning Reproduction of Buffett's decision-making process Buffett philosophy + modern multidimensional analysis framework Multi-master consensus investment decision system
Analytical perspective Single depth (pure Buffett framework) Single depth (Buffett as the main focus, integrating technical analysis) Multiple breadth (aggregation of 21 analyst roles)
Data dependency None, purely framework- and corpus-driven Requires real-time financial/market/conference call data Requires financial data API key and Python environment
Valuation methods Three classic valuation methods + margin of safety 8 models (DCF/PEG/DDM/NAV/sum-of-the-parts, etc.) Varies by analyst role
Technical analysis None Yes (candlestick charts/moving averages/RSI/MACD/chip analysis) Yes (supported by independent technical skill)
Output format 10-chapter fixed structured template Buffett scorecard + target price + position sizing recommendation JSON signal aggregation + consensus rating
Installation method Copy the folder to .claude/skills Copy the folder to .claude/skills Requires uv sync Install dependencies and configure API
Best scenarios Learn Buffett's thought process and discipline Generate institutional-grade in-depth individual stock research reports Cross-validate from multiple perspectives to find consensus signals

Application scenarios of buffett-skills

  • In-depth individual stock analysis: Enter a company name and complete the full-process evaluation from moat to valuation according to the Buffett framework.
  • Rapid financial report reading: When reading annual reports or shareholder letters, quickly extract key financial indicators and management signals.
  • Buy/sell decision assistance: Conduct hold/sell checks on held stocks, verifying them one by one against the four sell criteria.
  • Industry thematic research: Call industry manuals such as insurance, banking, consumer, media, energy, railways, and technology for vertical analysis.
  • Value investing learning: Through the thematic Q&A mode, ask the AI about core concepts such as circle of competence, Mr. Market, intrinsic value, and margin of safety.