vault: add GSD methodology deep-dive with examples and zettelkasten insights

Comprehensive GSD analysis: 15 sections covering core philosophy (fresh
context per agent), 5 methodologies (dream extraction, goal-backward
verification, nyquist validation, wave execution, checkpoints), full
command reference (37+), agent system (16 agents with model routing),
config system, git integration, state management, session continuity,
community best practices, pitfalls, framework comparison (GSD vs ECC vs
BMAD vs SpecKit), and 4 detailed practical examples (new project, brownfield,
debugging, quick tasks).

Three zettelkasten notes: context rot vs window isolation tradeoffs,
goal-backward vs forward verification, plans-as-prompts design pattern.

6 - Zettelkasten/20260320100300 Plans as Prompts设计模式.md

@@ -0,0 +1,27 @@
+---
+created: "2026-03-20 10:03"
+type: zettel
+tags: [prompt-engineering, ai-architecture, gsd]
+source: "https://github.com/gsd-build/get-shit-done"
+---
+
+# Plans as Prompts 设计模式
+
+GSD 中 PLAN.md 不是"被转化为 prompt 的文档"——它**就是** prompt。XML 结构（`<task>`, `<action>`, `<verify>`, `<done>`）直接指导执行器的行为。
+
+这个设计消除了"文档到 prompt 的翻译损失": 传统方式需要一个中间步骤把文档理解为指令，每次翻译都引入歧义。Plans as Prompts 让计划者直接写执行指令，跳过翻译。
+
+关键约束使这成为可能:
+- 每个计划 ≤ 50% 上下文预算（确保执行器有足够空间思考）
+- XML 结构强制精确性（不是自然语言的模糊描述）
+- `<verify>` 块要求每个任务都有可执行的验证命令
+- `<done>` 块定义明确的完成状态
+
+更广泛的启示: 当 AI Agent 是执行者时，规划文档应该以 Agent 的"母语"（结构化 prompt）书写，而非以人类的可读性为优先。
+
+---
+
+## Related
+
+- [[GSD 方法论与最佳实践]]
+- [[目标回溯验证vs正向任务检查]]