Finance & Investment Banking value-investingequity-researchstock-analysisvaluationbuffettfinancial-analysisdecision-framework

Buffett Investment Thinking System

A Claude Code skill that turns 70 years of Warren Buffett's investing wisdom into structured buy/hold/sell analysis, from an 8-question quick screen to deep-dive company evaluations.

FollowSkills review · FSRS-2.0
Use with care
53/ 100 5-point scale 2.7 / 5
1 2 3 4 5 6
1Trust17 / 25 · 3.4/5

Pure prompt-based knowledge skill: no permissions requested, no scripts executed, no external side effects or data exfiltration; data flow is transparent and least-privilege holds. Deducted for: Buffett quotes and figures (e.g., 1965–2022 returns) carry no verifiable sources, so attribution is incomplete.

2Reliability9 / 20 · 2.3/5

Instructions are self-consistent; task-type-to-reading-path mapping is clear; on-demand reading reduces context-overload risk; explicit stop-and-explain requirement outside circle of competence. Deducted for: static review cannot execute/validate, no tests or failure-feedback design for abnormal input, and the read-references protocol depends on model compliance.

3Adaptability9 / 15 · 3.0/5

Scenarios (stock analysis, report interpretation, valuation, sell decisions) are concrete; fixed output format includes explicit circle-of-competence boundaries. Deducted for: aggressive trigger description ('proactively trigger even if Buffett is not mentioned') creating false-trigger risk; no evidence of Chinese-language fit; non-fit boundaries (short-term trading, derivatives pricing) undeclared.

4Convention8 / 15 · 2.7/5

Good layered architecture (SKILL.md main flow plus 8 topically organized reference files) with an index table and reading protocol. Deducted for: unknown license metadata, no versioning or changelog, no disclosed maintainer/update path, publisher unverified.

5Effectiveness6 / 15 · 2.0/5

Structured framework with fixed output template offers clear marginal value over generic chat (8-question filter, owner-earnings formula, four sell criteria are directly usable). Deducted for: static review cannot verify actual output quality; valuation numbers (multiple ranges, discount tiers) are rule-of-thumb values requiring user verification.

6Verifiability4 / 10 · 2.0/5

Key claims cite Buffett shareholder-letter years (1983, 1991, 1993, etc.), giving some traceable form. Deducted for: self-references within files only, no third-party corroboration, no tests or independent reproduction material, and quote accuracy cannot be verified in a static read; fact/inference boundaries partly rest on the author's curation.

Evidence confidence:Low Reviewed Sep 10, 2026 Reviewed revision aeeae92c22c4
Before you use it
  • Trigger scope is overly broad: any investment-related topic forcibly activates the skill, which may misfit non-value-investing queries (short-term trading, options pricing).
  • Concrete figures (valuation multiples, margin-of-safety discounts) are rule-of-thumb values without cited sources and should not be used directly as investment bases.
  • Buffett quotes and performance figures are not independently verified; paraphrasing distortion is possible.
  • License and version metadata are missing; confirm compliance and update responsibility before enterprise adoption.
  • Output is an analytical framework, not investment advice; financial data must be supplied and verified by the user.
Review evidence [1][2][3][4][5][6][7]
See the full review method →

What does this skill do, and when should you use it?

This is a Claude Code skill that packages Warren Buffett's investing framework — margin of safety, moats, circle of competence, Mr. Market, capital allocation — into a reusable analysis system. It consists of one SKILL.md plus eight on-demand reference files covering thinking frameworks, investment philosophy, business moats, management assessment, financial metrics, valuation and capital allocation, risk behavior, and industry playbooks. It offers three dispatch paths: a 2-minute 8-question quick screen, a full company deep analysis, and direct lookup for specific questions. All output follows a mandatory template including conclusion, circle-of-competence verdict, key assumptions, valuation range, and item-by-item checks of four sell criteria. According to the repo's own eval, it lifts pass rate from 66.7% to 100% across three test cases, at a clear token and time cost.

Once installed, the skill auto-triggers on stock analysis, financial report interpretation, moat assessment, buy/hold/sell decisions, or value-investing concepts. Path A runs an 8-question filter (circle of competence, durability, moat, pricing power, earnings quality, debt safety, management integrity, price); two "No" answers need strong justification, four mean pass. Path B reads references/03-business-moat.md, 04-management-governance.md, 05-financial-metrics.md, and 06-valuation-capital.md in order, adding 07-risk-behavior.md and the relevant 08-industry-playbooks.md chapter as needed. Analysis requires computing owner earnings (net income + D&A − maintenance capex − working capital increase), checking 10-year average ROIC (target >15%) and cash conversion (target >90%), and assigning margin-of-safety discounts of 20–50% by certainty tier. Management integrity is an automatic veto. Output is a fixed structured template ending with a verdict delivered in Buffett's voice.

  1. A retail investor wondering whether a stock deserves deeper research uses the 8-question screen to filter out weak candidates fast
  2. A shareholder deciding whether to sell checks the four sell criteria (severe overvaluation / moat destruction / management integrity / better opportunity) one by one
  3. After reading an annual report or shareholder letter, an analyst assesses management integrity, capital allocation record, and institutional imperative
  4. An analyst doing Buffett-style work in a specific sector — insurance, banking, consumer, media, energy, railroads, tech — jumps straight to the relevant industry playbook
  5. A value-investing learner applies concepts like intrinsic value, compounding, and concentration to real cases
  6. Anyone discussing buybacks, dividends, or capital allocation who wants the analysis framed in Buffett's terms

What are this skill's strengths and limitations?

Pros
  • Methodology is explicit and traceable: the 8-question screen, five moat types, owner-earnings formula, margin-of-safety tiers, and four sell criteria are all concretely defined, not vague prompting
  • Sensible progressive disclosure: SKILL.md always loads, eight reference files load on demand by task type, controlling context spend
  • Mandatory output template forces sections that models tend to skip, like circle-of-competence verdict and key assumptions for later verification
  • Has quantitative eval: three benchmark cases show pass rate rising from 66.7% to 100%, attributed mainly to systematic reference-file reading
  • Management integrity is an automatic veto, reflecting an actual Buffett decision rule
Limitations
  • No license information; commercial-use compliance is unclear
  • The eval covers only three self-reported test cases — a tiny sample with no third-party validation
  • Material cost: roughly 30,000 extra tokens and 59 extra seconds per analysis on average; overkill for lightweight questions
  • No live market or financial-data integration; the user must supply all valuation inputs
  • The Buffett-voice verdict is stylized interpretation and should not be treated as real investment advice
  • Only verified in Claude Code; other Agent Skills clients are untested

How do you install this skill?

Clone the repo and copy the skill folder into your project's .claude/skills/ directory:

git clone https://github.com/agi-now/buffett-skills /tmp/buffett-skills
cp -r /tmp/buffett-skills/skills/buffett your-project/.claude/skills/buffett

The final layout must be .claude/skills/buffett/SKILL.md plus a references/ directory containing the eight reference files (01–08). Claude Code auto-discovers skills at that path; no registration needed. The repo documents no other installation method.

How do you use this skill?

Just ask in Claude Code — you don't need to say "Buffett"; any investment-analysis or business-quality question triggers the skill per its description. "Analyze Apple — is it a buy at current prices?" invokes the deep-analysis path; "Should I sell this position?" forces a read of 07-risk-behavior.md and an item-by-item check of the four sell criteria. For quick filtering, ask for the 8-question checklist. Note the skill insists on actually reading reference files rather than relying on the model's built-in knowledge, so expect noticeably higher token usage and latency than a plain chat.

How does this skill compare with similar options?

Versus simply asking Claude to "analyze this stock like Buffett," the skill's difference is enforced structured reference reading (11+ tool calls vs 2 in the eval) and a strict output template, reducing improvised answers from built-in knowledge. The repo names no competing skills or products.

FAQ

How much does each analysis cost in tokens and time?
Per the repo's own numbers, using the skill averages about 43,353 tokens and 154 seconds, versus roughly 12,524 tokens and 95 seconds without it. Path A (quick screen) reads no reference files and is much cheaper.
Does it fetch live prices or financial data?
No. Neither SKILL.md nor the references show any network calls, market APIs, or data sources; numbers like ROIC, cash conversion, and valuation inputs must be supplied by the user in conversation.
Is triggering automatic? Do I have to say "Buffett"?
The description states the skill should proactively trigger whenever the topic involves investment analysis, business quality, or investment decisions, even without mentioning Buffett. Actual triggering depends on your client's matching against the description.
Is this suitable as a basis for real investment decisions?
It is an analysis framework, not investment advice. Output is structured reasoning with explicit key assumptions for you to verify, but the repo makes no advisory claims; responsibility for decisions stays with the user.

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