investorskills

Investor Skills

Investor Skills are portable judgment systems for AI finance agents.

Run these investor skills inside Questflow, the AI Finance Agent for financial markets.

Investor Skill Template · Investment Schema · Reading List · Podcast List · YouTube List · Templates · Examples · Contributing

Investor Skills is an open-source library that turns durable investing judgment into portable, structured formats. It collects how great investors think, filter opportunities, size risk, and act under uncertainty — then structures those patterns so humans can study them and AI finance agents can apply them.

It is also a public template layer for Questflow-style AI Finance Agents: top investor judgment becomes skills that can explain, monitor, size, invalidate, and execute within explicit risk rules.

Built For Questflow, Portable Everywhere

Investor Skills are plain-text skill packages. You can use them in Claude Code, Codex, Cursor, OpenCode, or any other agent harness that can read SKILL.md instructions.

They are tailored for Questflow's financial harness: models, skills, plugins, and execution accounts working together across market data, portfolio context, broker/exchange/wallet permissions, and fund workflows.

Open-source skills

This repo is the free public layer:

• portable investor judgment systems
• templates and schemas
• reading list, podcast list, and YouTube list as reference material for each skill

Use a skill first, then use readings/podcasts/videos as source material to understand, stress-test, and enrich that skill.

Questflow exclusive skills

Questflow also includes exclusive closed-source skills not published here.

Those exclusive skills are distilled from top traders by labeling judgment across real trades: what they watched, why they entered, how they sized, what would invalidate the thesis, and how they reviewed the outcome. They are available to paid members inside Questflow.

The free open-source skills here should already feel excellent for study, research, and agent workflows. Questflow exclusives go further for execution-grade, trade-labeled judgment.

Run these skills in Questflow

Investor Skill Packages

An Investor Skill is one agent skill package. It can embed or reference a structured investment judgment system.

skills/livermore/
├── SKILL.md    # when to use, inputs, process, output, guardrails
└── invest.md   # optional investment system schema: signals, filters, sizing, risk

For simple skills, put the investment system directly inside SKILL.md. For larger or reusable models, keep it as invest.md and reference it from the skill frontmatter.

SKILL.md — The Agent Entry Point

SKILL.md is the public interface of an investor skill. It tells the agent when to use the model, what inputs are required, how to apply the process, what to avoid, and how to format the answer.

---
name: buffett
description: Use when evaluating a business through Buffett-style ownership, moat, owner earnings, and margin-of-safety judgment.
invest: ./invest.md
---

Use templates/skill.template.md to create new packaged skills.

Investment Schema — The Judgment System

The investment schema is the structured judgment system inside an investor skill. It defines the investor's worldview, universe, market regime, signals, filters, sizing, risk, monitoring, and playbooks.

docs/spec.md documents the optional standalone INVEST.md format for teams that want to store the investment system as a separate file. Conceptually, INVEST.md is not a separate product from skills; it is the investment schema used inside investor skills.

An INVEST.md file combines:

• YAML tokens (machine-readable): signals, filters, sizing rules, risk parameters, key metrics
• Markdown prose (human-readable): philosophy, analysis process, execution rules, behavioral guardrails

---
version: alpha
name: Buffett/Munger Value Investing
slug: buffett-munger-value
style: value+quality
timeHorizon: 5-10 years
decisionCadence: quarterly
assetClasses:
  - public equities
universe:
  marketCap: large-cap
  liquidity: high
marketRegime:
  preferred: any
  posture: patient
signals:
  fundamental:
    roic:
      weight: high
      frequency: annual
      direction: higher-is-better
      threshold: "> 15%"
filters:
  durableMoat: required
  consistentFCF: required
sizing:
  maxPosition: 25%
  maxPortfolio: 15
risk:
  marginOfSafety: 30%
  stopLoss: none
---

See the full specification and example.

Templates — Copyable Starting Points

Use these when adding a new investor model:

Template	Purpose
templates/skill.template.md	Defines the investor skill package: triggers, inputs, process, output format, guardrails, and Questflow use
templates/invest.template.md	Optional schema file for larger models: worldview, universe, market regime, signals, filters, sizing, risk, monitoring, playbooks, and sources

The optimized template adds fields that matter for real investor agents: assetClasses, universe, marketRegime, decisionCadence, signal frequency, and sources.

Repo Structure

investorskills/
├── docs/
│   ├── spec.md              # Optional investment schema specification
│   ├── reading-list.md      # Primary sources and classic essays by skill
│   ├── podcast-list.md      # Recommended podcasts with Spotify/Apple links
│   └── youtube-list.md      # Recommended YouTube talks and channels by skill
├── examples/
│   └── buffett.invest.md    # Standalone investment-system example
├── templates/
│   ├── skill.template.md    # Copyable investor skill package template
│   └── invest.template.md   # Optional investment schema template
├── skills/
│   └── <skill-name>/        # Agent skill package
│       ├── SKILL.md
│       └── invest.md        # Optional, referenced by SKILL.md
├── assets/
│   └── social-poster.png
├── README.md
└── LICENSE

Quick Start

Use an investor skill

Copy a skill package into your agent's skills directory. The SKILL.md file is the entry point; any linked invest.md file is supporting schema.

Use readings, podcasts, and videos as skill references

1. Load a skill package.
2. Open the skill's own Reading List / Podcasts / YouTube section.
3. Or use the shared indexes:
   • docs/reading-list.md
   • docs/podcast-list.md
   • docs/youtube-list.md
4. Attach 1-3 sources as reference material and ask the agent to apply the skill process, not just summarize the source.

Create a new investor skill

mkdir -p skills/livermore
cp templates/skill.template.md skills/livermore/SKILL.md
cp templates/invest.template.md skills/livermore/invest.md

Then replace the placeholders with the investor's actual judgment system: triggers, universe, regime, signals, filters, sizing, risk, monitoring, playbooks, and sources.

Install as a skill

Install all packaged skills or a single skill:

# Install all skills
npx skills add https://github.com/xuboyuebobb/investorskills

# Install a single skill
npx skills add https://github.com/xuboyuebobb/investorskills --skill "livermore"

Use standalone

Copy any SKILL.md into ChatGPT, Codex, Cursor, Claude, or another agent conversation. If the skill references invest.md, include that file too.

Investment Schema Examples

File	Investor	Style	Description
buffett.invest.md	Buffett, Munger, Graham	value+quality	Long-term ownership of durable businesses bought below intrinsic value

Available Skills

Skill	Investor	Model
livermore	Jesse Livermore	Trend following, breakout confirmation, pyramiding, and strict loss cutting
oneil-canslim	William O'Neil	Earnings acceleration, relative strength, institutional demand, and clean base breakouts
buffett	Warren Buffett	Durable business ownership, owner earnings, moat, management quality, and margin of safety
munger	Charlie Munger	Mental models, inversion, incentives, quality filters, and concentrated decisions
marks-cycles	Howard Marks	Second-level thinking, credit cycles, risk premiums, and defensive/aggressive posture
soros-reflexivity	George Soros	Reflexivity, macro dislocations, feedback loops, and asymmetric risk windows
druckenmiller	Stanley Druckenmiller	Top-down macro, liquidity regimes, concentrated risk-taking, and quick loss cutting
darvas-box	Nicolas Darvas	New-high momentum, box breakouts, volume confirmation, and mechanical stops
ansem-crypto	Ansem	Crypto portfolio structure, L1/app-token theses, attention, narratives, comparative valuation, TA+FA, and retail-flow reflexivity
serenity	Serenity / @aleabitoreddit	AI and semiconductor supply-chain chokepoints, upstream bottleneck mapping, institutional rotation, and dilution-aware thesis validation
minervini-vcp	Mark Minervini	VCP pattern, stage-2 trend, volatility contraction, tightness, pivot breakout, and fast loss cutting
burry-asymmetric-contrarian	Michael Burry	Primary-source contrarian longs/shorts, complex mispricing, asymmetric payoff, and catalyst/carry risk
simons-quant	Jim Simons / Renaissance	Quant signal research, many weak edges, statistical validation, execution cost, and signal decay
lynch-growth	Peter Lynch	Understandable growth stocks, company classification, PEG discipline, balance sheet, and story monitoring
klarman-deep-value	Seth Klarman	Deep value, distressed assets, forced sellers, illiquidity discounts, and downside protection
greenblatt-special-situations	Joel Greenblatt	Spinoffs, restructurings, merger securities, forced selling, and quality-value special situations
tepper-distressed-macro	David Tepper	Distressed macro, bank/credit stress, capital structure, policy backstops, and recovery asymmetry
ptj-macro-trend	Paul Tudor Jones	Macro trend, turning points, technical confirmation, liquidity, and strict drawdown control
seykota-systematic-trend	Ed Seykota	Systematic trend following, mechanical rules, volatility sizing, whipsaw tolerance, and discipline
turtle-trading	Richard Dennis / Turtles	Donchian breakouts, ATR/N-unit sizing, pyramiding, stops, and portfolio heat control
icahn-activist	Carl Icahn	Activist investing, governance pressure, capital allocation fixes, asset sales, and control catalysts
li-lu-value	Li Lu	Circle of competence, deep research, downside protection, global quality value, and concentrated ownership
nick-sleep-scale-economies	Nick Sleep / Qais Zakaria	Scale economies shared, customer-value flywheels, owner culture, low turnover, and long-duration compounding
dalio-principles-allweather	Ray Dalio	Economic machine, debt cycles, risk parity, diversification, and all-weather portfolio construction
gundlach-bonds	Jeffrey Gundlach	Duration, yield curve, credit spreads, fixed-income relative value, and rates regime judgment
ackman-concentrated-activism	Bill Ackman	Concentrated multiyear equity theses, activism catalysts, business quality, and public thesis path
einhorn-forensic-short	David Einhorn	Forensic accounting shorts, governance failures, capital-allocation critique, and evidence-based long/short
coleman-tiger-growth	Chase Coleman / Tiger Global	Scalable growth platforms, unit economics, network effects, growth duration, and concentrated tech growth
cathie-wood-innovation	Cathie Wood	Disruptive innovation, S-curve adoption, technology convergence, and long-duration thematic growth
graham-net-net	Benjamin Graham	Net-current-asset value, statistical deep value, margin of safety, and balance-sheet-first bargains
schloss-cigar-butt	Walter Schloss	Cigar-butt value, cheap balance sheets, diversified bargains, and low-turnover deep value
templeton-max-pessimism	John Templeton	Global contrarian value, maximum pessimism buying, crisis recovery, and cross-border opportunity search
hohn-concentrated-quality	Chris Hohn / TCI	Concentrated quality compounders, pricing power, high ROIC, engagement, and long-duration ownership
watsa-insurance-float	Prem Watsa / Fairfax	Insurance float, contrarian value allocation, special situations, and downside-focused capital compounding
muddy-waters-forensic	Muddy Waters / Carson Block	Forensic shorts, channel checks, related-party webs, cash verification, and evidence-based short reports
hindenburg-investigation	Hindenburg Research	Investigative short reports, promoter networks, disclosure gaps, and catalyst-driven evidence chains
spruce-point-accounting-short	Spruce Point Capital	Accounting-quality shorts, cash conversion, aggressive non-GAAP, acquisition accounting, and governance red flags
sequoia-founder-market	Sequoia Capital	Founder quality, market selection, product-market fit, distribution, and long-duration company building
a16z-techno-optimist	Andreessen Horowitz	Technology adoption, market creation, platform power, AI/software/crypto theses, and techno-optimist venture bets
usv-network-effects	Union Square Ventures	Network effects, marketplace defensibility, protocols/platforms, openness, and scalable network businesses
founders-fund-contrarian	Founders Fund	Contrarian venture, hard tech, non-consensus secrets, bold product ambition, and monopoly-seeking company design
yc-early-pmf	Y Combinator	Early PMF, talk to users, simple growth, default alive, and anti-premature-scaling startup judgment
arthur-hayes-liquidity	Arthur Hayes	Dollar liquidity, crypto risk appetite, funding/leverage cycles, and macro-driven crypto positioning
hsaka-crypto-ta	Hsaka	Crypto market structure, trend, invalidation, leverage discipline, and narrative-aware technical timing
cryptocred-structure	CryptoCred	Crypto levels, structure, confluence, predefined risk, and educational chart planning
willy-woo-onchain	Willy Woo	On-chain holder behavior, realized value, supply dynamics, and BTC/crypto cycle diagnosis
cobie-cycle-filter	Cobie	Crypto cycle psychology, narrative traps, leverage humility, and anti-stupid decision filtering
paradigm-crypto-research	Paradigm	Protocol research, mechanism design, incentives/MEV/L2, and research-driven crypto investing
multicoin-thesis-vc	Multicoin Capital	Thesis-driven crypto VC, high-performance chains, token value capture, and sector concentration
a16z-crypto	a16z crypto	Web3 adoption, crypto infrastructure vs apps, open networks, and long-duration ecosystem investing
delphi-thematic-crypto	Delphi Digital	Crypto thematic research, sector maps, tokenomics, narrative timing, and research-driven allocation
placeholder-token-networks	Placeholder	Open network investing, token frameworks, network participation, and long-duration crypto network ownership
grayscale-crypto-sectors	Grayscale Research	Crypto Sectors taxonomy, FTSE/Grayscale index eligibility, fee/usage fundamentals, sector-share valuation, ETP/trust wrappers, and the Zcash privacy-as-money case
duanyongping-benfen-value	段永平 / Duan Yongping	Benfen value, good business at right price, long hold, circle of competence, owner mindset
fengliu-reverse-weakhand	冯柳 / Feng Liu	Weak-hand reverse investing, asymmetric risk/reward, consensus divergence, probability-based sizing
qiuguolu-value-quality	邱国鹭 / Qiu Guolu	Value-quality, industry leaders, circle of competence, simple clear thesis
dengxiaofeng-cycle-industry	邓晓峰 / Deng Xiaofeng	Cycle-aware industry investing, supply-demand dynamics, buying leaders at cycle bottoms
danbin-longterm-compounder	但斌 / Dan Bin	Long-term compounders, holding great companies through volatility, time as edge
libei-macro-hedge	李蓓 / Li Bei	Macro hedge, regime identification, conviction-based sizing, drawdown control
tangnengtong-shortterm-ta	唐能通 / Tang Nengtong	A-share short-term TA, volume-price relationships, MA systems, breakout signals
chenhao-limit-up	陈浩 / Chen Hao	A-share limit-up sentiment, market emotion cycles, board strength, aggressive momentum
zhanglei-longterm-research-value	张磊 / Zhang Lei (Hillhouse)	Long-term research-driven value, deep diligence, great companies, active value-add
shihanbing-macro-interest-analysis	时寒冰 / Shi Hanbing	Macro interest analysis, incentive-based policy prediction, trend following from利益博弈

Contributing

Adding an investor skill

1. Create skills/<skill-name>/SKILL.md
2. Use templates/skill.template.md
3. Embed the investment judgment system in SKILL.md, or add skills/<skill-name>/invest.md for larger models
4. Define when to use, inputs, process, output format, and guardrails
5. Add an entry to the Available Skills table above

Adding a standalone investment schema example

1. Create <name>.invest.md in examples/
2. Follow the investment schema specification
3. Include YAML frontmatter with tokens and markdown body with rationale
4. Add an entry to the Investment Schema Examples table above

Planned models

• lynch.invest.md — Peter Lynch: invest in what you know, PEG ratio, stock categories
• dalio.invest.md — Ray Dalio: all-weather, risk parity, macro regime identification
• simons.invest.md — Jim Simons: quantitative, statistical arbitrage, signal processing
• greenblatt.invest.md — Joel Greenblatt: magic formula, special situations, spinoffs
• templeton.invest.md — John Templeton: contrarian, global, maximum pessimism

Why

Most investing content is passive: books, interviews, letters, podcasts, clips, and commentary.

The useful part is operational:

• What does this investor notice before others?
• What questions do they ask every time?
• What data do they trust?
• What do they ignore?
• What makes them act?
• What would their agent scan for every day?

Investor Skills extracts those decision patterns into software-shaped instructions.

License

MIT