📈
DataPython

Evolutionary Investing

by simbajigege

Evolutionary Investing is a Data skill for Claude Code, published by simbajigege in book2skills.

161 stars30 forkson simbajigege/book2skillsAdded 2026/09/08+4% in starsRepository updated 2026/08/26
agent-skillsagentskillsanthropicanthropic-claudebook2skillsgrowth-investinginvestinginvesting-skillsskillsstock-analysis
Install in seconds
Install Evolutionary Investing
Copy Evolutionary Investing into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/simbajigege/book2skills/tree/main/skills/investing-from-darwin ~/.claude/skills/investing-from-darwin

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/simbajigege/book2skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
skills/investing-from-darwin/SKILL.md in simbajigege/book2skills
Installs to
~/.claude/skills/investing-from-darwin
Collection
One of 25 skills cataloged from this repository
Category
Data812 skills

What Evolutionary Investing does

Evolutionary Investing applies Pulak Prasad’s Darwin-inspired rules to stock picks. Use it to screen for big-loss risks, test business resilience, and judge whether patience is better than trading.

Evolutionary Investing is cataloged under Data on DirSkills. Evolutionary Investing comes from a repository tagged agent-skills, agentskills, anthropic, anthropic-claude and book2skills.

Documentation

README

What I Learned About Investing from Darwin — Evolutionary Investing Skill

Knowledge source: What I Learned About Investing from Darwin by Pulak Prasad.

Overview

Use this skill to evaluate investments through evolutionary survival logic: avoid big risks, buy high-quality resilient businesses at fair prices, and stay very patient. It supports investors who want to avoid permanent capital loss, resist over-trading, and prefer robustness over fragile forecasting.

When to Use This Skill

Use this skill when the user asks:

  • "Is this business resilient enough to own?"
  • "What big risks could permanently hurt this investment?"
  • "Is this cheap stock a trap?"
  • "Should I rely on this DCF?"
  • "How patient should I be?"
  • "How would Darwin-inspired investing judge this company?"

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Evolutionary Investing

  • What else does simbajigege publish alongside Evolutionary Investing?

    Evolutionary Investing is one of 25 skills that DirSkills catalogs from simbajigege/book2skills, the repository it ships in. Its siblings there include Agent Memory Implementation, Agent Tool Builder and Business Adventures Analysis. Each one is a separate skill with its own page in this directory, installs the same way Evolutionary Investing does, and is maintained by simbajigege in that same repository. The rest of the collection is listed on the simbajigege/book2skills page.

  • How does Evolutionary Investing compare to other Data skills?

    Evolutionary Investing ranks #761 by stars among the 812 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Evolutionary Investing against them. Open each page to compare what they document and how they install.

More from simbajigege/book2skills

Evolutionary Investing is one of 25 skills cataloged on DirSkills from simbajigege/book2skills.

See all 25 skills
🧠
1h ago

Agent Memory Implementation

Agent Memory Implementation restructures a crowded MEMORY.md into a small pointer index plus on-demand topic files. Use it when MEMORY.md gets too long, mixes pointers with content, or needs stale memories corrected in place.
AI Engineering
16130
🛠️
1h ago

Agent Tool Builder

Agent Tool Builder helps define agent tools with a fail-closed pattern that keeps schema, security metadata, and execution together. Use it when creating a new tool or adding validation and permission checks to an existing one.
AI Engineering
16130
📘
1h ago

Business Adventures Analysis

Business Adventures Analysis uses John Brooks’s *Business Adventures* as a diagnostic lens for business failures, market panics, governance issues, and innovation questions. Use it to map a live situation to recurring patterns like hubris, incentive drift, and institutional fragility.
AI Engineering
16130
📈
1h ago

Common Sense Index Investing

Common Sense Index Investing applies Bogle's rules to fund selection, fees, asset allocation, and buy-and-hold discipline. Use it to compare index vs active funds, assess cost drag, and simplify a portfolio.
Data
16130
🧠
1h ago

Compact Memory Implementation

Compact Memory Implementation shows how to add memory compaction to an agent by triggering a forked compactor, generating a structured summary, and restoring it in later sessions. Use it when building context compression or persistence with Claude Agent SDK or the Anthropic API.
AI Engineering
16130
📣
1h ago

Contagious Viral Content Berger

Contagious Viral Content Berger applies Jonah Berger's STEPPS framework to diagnose why content spreads or stalls. Use it to engineer shareability with social currency, triggers, emotion, public visibility, practical value, and stories.
AI Engineering
16130