Tag: GitHub stars

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GitHub stars: what they measure (and what they do not)

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Ranking repos by stars favors visibility over fit. That can be a fair first filter—stars are cheap and usually mean someone noticed the project—but treating the count as proof of quality, maintenance, or production readiness is the common mistake. What follows is what stars actually measure, where they mislead, and what to check on the […]

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Evaluating AI Skills: A Practitioner’s Guide

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The ecosystem of “AI skills” — modular instruction packs that extend an LLM with task-specific know-how, whether they’re called Skills, plugins, agents, MCP servers, system-prompt templates, or tool bundles — has exploded fast enough that “which one should I use?” has become the dominant question. The answer is rarely obvious from a README, and almost […]

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