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/20260320100100 上下文腐烂与全新窗口隔离.md

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+---
+created: "2026-03-20 10:01"
+type: zettel
+tags: [claude-code, context-window, ai-quality, gsd]
+source: "https://github.com/gsd-build/get-shit-done"
+---
+
+# 上下文腐烂与全新窗口隔离
+
+AI 编码 Agent 的输出质量随上下文填充率非线性下降:
+
+- 0-30%: 峰值质量
+- 50%+: 开始赶工
+- 70%+: 幻觉风险显著增加
+
+GSD 的解决方案是**激进隔离**: 每个任务执行器获得全新的 200K token 上下文窗口，编排器保持在 30-40% 使用率。这与 ECC 的"策略性压缩"（在逻辑节点手动 `/compact`）形成对比。
+
+两种方法的权衡:
+- **全新窗口**: 质量最佳，但 token 成本高（每个 Agent 独立 API 调用）
+- **策略性压缩**: 成本低，但依赖人类判断何时压缩，且压缩可能丢失关键上下文
+
+理想方案可能是两者结合: 对复杂多阶段项目用 GSD 的窗口隔离，对日常编码用 ECC 的策略压缩。
+
+---
+
+## Related
+
+- [[GSD 方法论与最佳实践]]
+- [[MCP数量与上下文窗口的反比关系]]