使用方法
- 复制安装命令，在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物，并对照来源检查输出。
npx skills add https://github.com/heyimcarlos/agent-skills --skill principle-foundational-thinking开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。
按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。
Foundational Thinking
Structural decisions protect option value. Code-level decisions protect simplicity. Over-engineering is often a premature decision that closes doors. The right foundational data structure keeps doors open.
Data structures first. Get the data shape right before writing logic. The right shape makes downstream code obvious. Define core types early, trace every access pattern, and choose structures that match the dominant paths. A data-structure change late is a rewrite. Early, it is often a one-line diff.
At code level, DRY the structure, not every line. Types and data models should converge. Three similar statements still beat a premature abstraction. Prefer explicit over clever. Test behavior and edge cases, not line counts.
Concurrency corollary. Before sharing state between actors, ask "what happens if another actor modifies this concurrently?" If not "nothing", isolate.
Scaffold first. If something helps every later phase, do it first. Ask "does every subsequent phase benefit from this existing?" CI, linting, test infrastructure, and shared types are scaffold. Sequence for option value: setup before features, tests before fixes. Keep commits small and single-purpose.
Each increment should land a coherent abstraction or deepen one that exists. Do not spread a new capability across callers as special-case coordination.
Subtraction comes before scaffolding: remove dead weight first, then lay foundations.
