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── 99185 repos indexed ── | filtered by tag: #decision-making
alchaincyf/munger-skill ★ 372 97 DATA_RESEARCH

This repository is a knowledge package designed to create an AI agent skill that embodies Charlie Munger's thinking framework. It doesn't contain executable code but rather curates and structures Munger's mental models, decision heuristics, and communication style into a usable format for AI agent runtimes. The core output is the SKILL.md file, which provides detailed instructions for how an AI agent should adopt Munger's perspective when responding to user queries, including role-playing rules, a response workflow requiring research before answering, and specific guidelines for expressing Munger's characteristic communication style. The repository represents a sophisticated approach to expertise capture and encoding for AI systems. It synthesizes information from over 50 sources including Berkshire Hathaway shareholder meetings, USC/Harvard speeches, interview records, and external criticisms to distill Munger's approach into five core mental models, eight decision heuristics, and a detailed expression DNA. The references/ directory contains the source research materials, demonstrating transparency about the knowledge foundation. Examples/show how the skill works in practice through sample conversations about investment decisions, team management, and content creation. While primarily a knowledge resource, the structure of the SKILL.md file itself offers potential reusability as a template for creating similar 'thinking style' skills for other experts or domains. The systematic approach to encoding expertise through role-playing protocols, mental model collections, decision frameworks, and communication guidelines represents a pattern that could be adapted with domain-specific content substitution for other AI agent skills.

RATING: 8.8/10 REPRO: 6.0/10 MAINT: active DRIFT: low
▸ 1 reusable components found
jmejia8/Metaheuristics.jl ★ 303 29 APPLICATION

Metaheuristics.jl is a Julia library for global optimization implementing various metaheuristic algorithms for single-objective, multi-objective, and combinatorial optimization problems. The library provides a modular architecture with clear separation between core functionality (state management, problem definitions), algorithm implementations (organized by optimization type), operators (selection, crossover, mutation), test problems, performance indicators, and decision-making methods. The primary workflow involves defining an objective function and search space, selecting/configuring an algorithm, and calling the optimize() function to find optimal solutions. The library depends on standard Julia packages and specialized libraries for distance calculations, distributions, and multi-criteria decision-making.

RATING: 8.6/10 MAINT: active DRIFT: low
▸ 2 reusable components found
kuchin/awesome-cto ★ 35458 2197 APPLICATION

This repository is a curated resource list (Awesome List) for Chief Technology Officers and VP R&D professionals. It contains no executable code, API endpoints, or data pipelines. The repository consists of a single README.md file with structured links to external resources organized by topic (hiring, architecture, startups, etc.), a LICENSE file (CC0), and a Jekyll theme configuration. The value proposition is entirely in the curation effort and organization of external resources, not in software craftsmanship. This is a documentation/resource aggregation project designed to be deployed as a static GitHub Pages site using Jekyll. The high star count (35K+) reflects community value in the curated content, not technical complexity.

RATING: 7.0/10 MAINT: maintained DRIFT: low
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