V1.2.0 — Adaptive investment control

V1.2.0 adds adaptive investment control to the performance decision engine introduced in V1.1. The Controller now decides whether the next stage is worth running from measured headroom, evidence quality, expected cost, scope, risk, and user authorization instead of treating the time ceiling as a target.

Highlights:

• Adds run-level grants for execution time, modification scope, risk, and the furthest permitted validation stage.
• Freezes one ChangeSet and advances it through static review, correctness, short paired timing, targeted profiling when needed, and formal workload validation.
• Preserves completed stages and candidates across interruption; authorization pauses keep the working state, while rejection or explicit abandonment restores the original implementation.
• Prevents failed or low-value candidates from starting unnecessary expensive stages.
• Keeps search and external AI review advisory and bound to locally verifiable evidence.
• Reworks the Chinese README as the primary user guide and clarifies test workload and correctness-check requirements in both languages.

Validation:

• 1,299 automated tests: 1,289 passed and 10 physical-GPU opt-in tests were skipped in the CPU/static suite.
• Python 3.10 and Python 3.12 CI passed for the released source.
• Installable-skill tests, staged-installation smoke, source compilation, and self_check passed.
• Physical GPU coverage and known profiler-permission limits remain documented in docs/validation.md.

Upgrade note:

• Unfinished runs created before the V1.2 run-grant protocol are not migrated automatically. Start a new V1.2 run for controlled execution.

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V1.2.0 在 V1.1 性能决策引擎的基础上加入自适应投入控制。Controller 会根据可优化空间、证据质量、后续成本、修改范围、风险和用户授权，判断下一阶段是否值得执行，不再把时间上限当成需要用完的预算。

主要变化：

• 以运行级授权统一约束执行时间、修改范围、风险和最远验证阶段。
• 每次冻结一个 ChangeSet，依次完成静态检查、正确性校验、短版成对测试、必要的定向 profile 和正式 workload 验证。
• 中断后保留已完成阶段和候选现场；授权不足时暂停，候选被否决或明确放弃后恢复原实现。
• 前一阶段失败或预期收益不足时，不再启动后续昂贵验证。
• 外部搜索和第三方 AI 只提供方向挑战，最终结论仍由本地正确性与性能证据决定。
• 以中文 README 作为主要使用文档，并统一说明测试 workload 和正确性校验要求。

验证情况：

• 自动化测试共 1,299 项，其中 1,289 项通过，10 项物理 GPU 可选测试在 CPU/static 测试中跳过。
• Python 3.10 和 Python 3.12 的 GitHub CI 均通过。
• 安装包测试、临时安装验证、源码编译检查和 self_check 均通过。
• 物理 GPU 覆盖范围和 profiler 权限限制记录在 docs/validation.md。

升级说明：

• V1.2 之前尚未结束的运行不会自动迁移到新的运行级授权协议，受控执行请新建 V1.2 任务。