feat: integrate Perfetto SQL stdlib modules (P0+P1)

.gitignore

@@ -33,3 +33,4 @@ reports/
 platform/android/.gradle/
 platform/android/build/
 platform/android/.idea/
+perfetto-build/

ARCHITECTURE.md

@@ -83,7 +83,20 @@ smartinspector/
 │   │   └── deterministic.py     #   Deterministic pre-computation (reduces LLM tokens)
 │   │
 │   ├── collector/               # Data collection & processing
-│   │   └── perfetto.py          #   PerfettoCollector: adb collect → SQL query → JSON (CPU调用链, 系统级CPU, WS+SQL合并, context manager)
+│   │   ├── perfetto.py          #   PerfettoCollector: adb collect → SQL query → JSON (CPU调用链, 系统级CPU, WS+SQL合并, context manager)
+│   │   ├── frame.py             #   FrameMixin: per-frame metrics (overrun, cpu_time, ui_time, vsync_delay, jank)
+│   │   ├── startup.py           #   StartupMixin: TTID/TTFD startup metrics + bottleneck breakdown
+│   │   ├── memory.py            #   MemoryMixin: heap graph stats, class aggregation, dominator tree
+│   │   ├── lock.py              #   LockMixin: Java monitor lock contention analysis
+│   │   ├── binder.py            #   BinderMixin: binder transactions + latency breakdown
+│   │   ├── gc.py                #   GcMixin: garbage collection event analysis
+│   │   ├── anr.py               #   AnrMixin: ANR detection + main-thread slice analysis
+│   │   ├── slice_enhanced.py    #   SliceEnhancedMixin: SI$ slice CPU time + thread state distribution
+│   │   ├── input.py             #   InputMixin: input event latency breakdown (dispatch/handling/ACK)
+│   │   ├── sched_latency.py     #   SchedLatencyMixin: scheduling latency per thread
+│   │   ├── oom.py               #   OomMixin: OOM score transitions + RSS/Swap + LMK events
+│   │   ├── cpu_utilization.py   #   CpuUtilizationMixin: frequency-weighted CPU utilization (process/thread)
+│   │   └── surfaceflinger.py    #   SurfaceFlingerMixin: App-SF frame timeline matching
 │   │
 │   ├── commands/                # Slash command implementations
 │   │   ├── __init__.py          #   Command registry (SLASH_COMMANDS dict + handle_slash_command)
@@ -431,6 +444,39 @@ PerfSummary
 | `collect_threads()` | `thread` | Thread listing |
 | `collect_sys_stats()` | `sys_stats` | System-level CPU metrics |
 
+### Stdlib Analysis Modules (Mixin 模式)
+
+所有模块以 Mixin 形式挂载到 `PerfettoCollector`，通过 `INCLUDE PERFETTO MODULE` 引入 Perfetto 标准库。每个 Mixin 依赖宿主提供 `self._open()` (返回 TraceProcessor) 和 `self._target_package`。
+
+#### P0 — 核心模块
+
+| Mixin | 方法 | Perfetto Stdlib (`INCLUDE`) | 采集数据 | 解决的性能问题 |
+|-------|------|---------------------------|---------|---------------|
+| `FrameMixin` | `collect_frame_metrics()` | `android.frames.per_frame_metrics`<br>`android.frames.timeline` | 每帧行为指标：overrun、cpu_time、ui_time、vsync_delay、jank 分类 (was_jank/was_slow_frame/was_big_jank/was_huge_jank)，Top 30 最差帧 | 定位 UI 卡顿根因：区分 CPU 耗时过高、UI 线程慢、VSYNC 延迟等不同类型的帧超时 |
+| `StartupMixin` | `collect_startup_metrics()` | `android.startup.startups`<br>`android.startup.time_to_display` | 应用启动事件：TTID (Time To Initial Display)、TTFD (Time To Full Display)、启动类型 (cold/warm/hot) | 量化启动性能：精确定位每次冷启动/暖启动的首次绘制时间和全屏展示时间 |
+| `StartupMixin` | `collect_startup_breakdown()` | `android.startup.startups`<br>`android.startup.startup_breakdowns` | 启动瓶颈分解：每段耗时的 reason (binder/io/cpu/lock 等)，Top 50 最长段 | 分解启动耗时归因：识别启动期间是 binder 调用、磁盘 IO、CPU 计算还是锁竞争占用了时间 |
+| `MemoryMixin` | `collect_heap_graph_stats()` | `android.memory.heap_graph.heap_graph_stats` | 堆图摘要：总/可达对象数量、堆大小、Native 分配、OOM score、RSS/Swap、dmabuf | 内存用量概览：评估应用整体内存健康度，OOM 风险判断 |
+| `MemoryMixin` | `collect_heap_class_aggregation()` | `android.memory.heap_graph.heap_graph_class_aggregation` | 按类聚合堆内存 Top 20：对象数量、self size、reachable size、dominated size、native size | 定位内存大户：找出哪些类占用了最多堆空间，区分可达 vs 不可达对象 |
+| `MemoryMixin` | `collect_heap_dominator_tree()` | `android.memory.heap_graph.dominator_tree` | 堆支配树 Top 50：对象 ID、immediate dominator、dominated set 大小、retained size、深度 | 追踪内存泄漏：通过支配树找到 retain 最多内存的对象链路，定位泄漏根节点 |
+
+#### P1 — 增强模块
+
+| Mixin | 方法 | Perfetto Stdlib (`INCLUDE`) | 采集数据 | 解决的性能问题 |
+|-------|------|---------------------------|---------|---------------|
+| `LockMixin` | `collect_lock_contention()` | `android.monitor_contention` | Java 锁竞争事件 Top 20：blocked/blocking 方法、线程名、是否主线程、等待者数量 + 阻塞线程状态分解 | 定位主线程阻塞：识别导致主线程等待的锁竞争，区分 IO 等待 vs CPU 等待 |
+| `BinderMixin` | `collect_binder_txns()` | `android.binder` | 同步 Binder 事务 Top 30：client/server 进程线程、AIDL 方法名、是否主线程、client/server 耗时 | 定位跨进程调用瓶颈：找出最耗时的 IPC 调用，识别主线程上的同步 binder 等待 |
+| `BinderMixin` | `collect_binder_breakdown()` | `android.binder`<br>`android.binder_breakdown` | Binder 延迟分解 Top 50：client/server 侧的 reason (flush/sched/wait 等)、reason_type | 深入分析 Binder 延迟：区分 binder 调用中的调度延迟、flush 等待、事务执行等各阶段耗时 |
+| `GcMixin` | `collect_garbage_collection()` | `android.garbage_collection` | GC 事件 Top 20：wall duration、CPU 时间分解 (running/runnable/io_wait/non_io_wait)、GC 类型、reclaimed 大小、heap 范围 | 评估 GC 影响：识别 GC Stop-The-World 对主线程的实际影响，区分 concurrent vs stop-the-world GC |
+| `AnrMixin` | `collect_anrs()` | `android.anrs` | ANR 事件：进程/组件、ANR 类型、subject、timer_delay + ANR 窗口内主线程 Top 10 切片 | ANR 根因分析：识别 ANR 发生时主线程正在执行的耗时操作 |
+| `SliceEnhancedMixin` | `collect_slice_cpu_time()` | `slices.cpu_time` | SI$ 切片真实 CPU 时间 Top 20：cpu_time、total_dur、cpu_ratio、线程名 | 区分真实计算 vs 等待：切片耗时长不代表 CPU 慢，cpu_ratio 低说明瓶颈在 IO/锁/调度而非计算 |
+| `SliceEnhancedMixin` | `collect_slice_time_in_state()` | `slices.time_in_state`<br>`sched.states` | SI$ 切片线程状态分布 Top 10：Running/Sleeping/Runnable/IO Wait 等状态占比、blocked_function | 诊断切片耗时根因：识别切片时间花在了 CPU 运行、IO 等待、调度等待还是休眠上 |
+| `InputMixin` | `collect_input_latency()` | `android.input` | 输入事件延迟 Top 20：dispatch/handling/ACK 三阶段耗时、end-to-end 延迟、事件类型 | 追踪触控响应延迟：区分输入事件在 dispatch、处理、ACK 哪个阶段耗时最长 |
+| `SchedLatencyMixin` | `collect_sched_latency()` | `sched.latency` | 线程调度延迟 Top 20：per-thread 的 runnable→running 等待次数、总/平均/最大等待时间 | 识别调度瓶颈：线程 ready 后多久才被 CPU 执行，高调度延迟意味着 CPU 资源竞争激烈 |
+| `OomMixin` | `collect_oom_rss_swap()` | `android.memory.process`<br>`android.memory.lmk` | OOM score 变迁 + 内存快照 (anon_rss/file_rss/shmem_rss/swap) + LMK kill 事件 | 内存压力分析：追踪进程 OOM score 变化与内存占用的关系，识别被 LMK 杀死的进程 |
+| `CpuUtilizationMixin` | `collect_process_cpu_utilization()` | `linux.cpu.utilization.process` | 进程级 CPU 利用率：频率加权 millicycles/megacycles、runtime、min/max/avg freq、per-second utilization | 精确 CPU 利用率：传统 CPU 使用率不含频率信息，频率加权利用率更准确反映真实 CPU 消耗 |
+| `CpuUtilizationMixin` | `collect_thread_cpu_utilization()` | `linux.cpu.utilization.thread` | 线程级 CPU 利用率 Top 15：per-thread 的 millicycles/megacycles、频率信息、per-second utilization | 定位 CPU 热线程：找出哪些线程消耗了最多 CPU 周期，结合频率信息判断是否因低频运行导致性能差 |
+| `SurfaceFlingerMixin` | `collect_surfaceflinger_timeline()` | `android.surfaceflinger` | App-SF 帧时间线匹配 Top 200：app/SF 帧时间戳、耗时、期望 deadline、匹配类型 (on_time/late) | 端到端帧延迟分析：从 App 渲染到 SurfaceFlinger 合成的完整链路，识别帧是在 App 端还是 SF 端延迟 |
+
 **Perfetto config**:
 - Default categories: sched, freq, idle, power, memreclaim, gfx, view, input, dalvik, am, wm
 - `atrace_apps: "*"` — captures app-level atrace markers
@@ -685,7 +731,27 @@ User: "全面分析列表滑动性能"
   │   ├─ collect_frame_timeline()
   │   ├─ collect_memory()
   │   ├─ collect_view_slices()  ← SI$ prefix filtering, rv_instances grouping
-  │   └─ collect_block_events()  ← WS 结构化 JSON + SQL atrace 合并（非覆盖）
+  │   ├─ collect_block_events()  ← WS 结构化 JSON + SQL atrace 合并（非覆盖）
+  │   └─ Stdlib Mixin modules (via INCLUDE PERFETTO MODULE):
+  │       ├─ collect_frame_metrics()        ← android.frames.*
+  │       ├─ collect_startup_metrics()      ← android.startup.*
+  │       ├─ collect_startup_breakdown()    ← android.startup.startup_breakdowns
+  │       ├─ collect_heap_graph_stats()     ← android.memory.heap_graph.heap_graph_stats
+  │       ├─ collect_heap_class_aggregation() ← android.memory.heap_graph.heap_graph_class_aggregation
+  │       ├─ collect_heap_dominator_tree()  ← android.memory.heap_graph.dominator_tree
+  │       ├─ collect_lock_contention()      ← android.monitor_contention
+  │       ├─ collect_binder_txns()          ← android.binder
+  │       ├─ collect_binder_breakdown()     ← android.binder + android.binder_breakdown
+  │       ├─ collect_garbage_collection()   ← android.garbage_collection
+  │       ├─ collect_anrs()                 ← android.anrs
+  │       ├─ collect_slice_cpu_time()       ← slices.cpu_time
+  │       ├─ collect_slice_time_in_state()  ← slices.time_in_state + sched.states
+  │       ├─ collect_input_latency()        ← android.input
+  │       ├─ collect_sched_latency()        ← sched.latency
+  │       ├─ collect_oom_rss_swap()         ← android.memory.process + android.memory.lmk
+  │       ├─ collect_process_cpu_utilization() ← linux.cpu.utilization.process
+  │       ├─ collect_thread_cpu_utilization()  ← linux.cpu.utilization.thread
+  │       └─ collect_surfaceflinger_timeline() ← android.surfaceflinger
   └─ State: perf_summary = "{...json...}", _trace_path = "/tmp/xxx.pb"
   │
   ▼

CLAUDE.md

@@ -1 +1,49 @@
+# SmartInspector - Project Instructions
 
+## Collector 模块 (Perfetto SQL Stdlib 集成)
+
+采集层位于 `src/smartinspector/collector/`，所有模块以 Mixin 形式挂载到 `PerfettoCollector`。每个 Mixin 依赖宿主提供 `self._open()` (返回 TraceProcessor) 和 `self._target_package`。
+
+### 基础模块
+
+| 文件 | 类 | 说明 |
+|------|-----|------|
+| `perfetto.py` | `PerfettoCollector` | 核心采集器 (adb → SQL → JSON)，提供 `_open()` / `_target_package`，所有 Mixin 的宿主 |
+
+### Stdlib 分析模块 (P0 — 核心)
+
+| 文件 | Mixin | 方法 | Perfetto Stdlib |
+|------|-------|------|-----------------|
+| `frame.py` | `FrameMixin` | `collect_frame_metrics()` — 帧指标 (overrun, cpu_time, ui_time, vsync_delay, jank) | `android.frames.per_frame_metrics`, `android.frames.timeline` |
+| `startup.py` | `StartupMixin` | `collect_startup_metrics()` — TTID/TTFD 启动耗时 | `android.startup.startups`, `android.startup.time_to_display` |
+| `startup.py` | `StartupMixin` | `collect_startup_breakdown()` — 启动瓶颈分解 | `android.startup.startup_breakdowns` |
+| `memory.py` | `MemoryMixin` | `collect_heap_graph_stats()` — 堆图摘要统计 | `android.memory.heap_graph.heap_graph_stats` |
+| `memory.py` | `MemoryMixin` | `collect_heap_class_aggregation()` — 按类聚合堆内存 (Top 20) | `android.memory.heap_graph.heap_graph_class_aggregation` |
+| `memory.py` | `MemoryMixin` | `collect_heap_dominator_tree()` — 堆支配树 (最大 retained size) | `android.memory.heap_graph.dominator_tree` |
+
+### Stdlib 分析模块 (P1 — 增强)
+
+| 文件 | Mixin | 方法 | Perfetto Stdlib |
+|------|-------|------|-----------------|
+| `lock.py` | `LockMixin` | `collect_lock_contention()` — Java 锁竞争分析 | `android.monitor_contention` |
+| `binder.py` | `BinderMixin` | `collect_binder_txns()` — Binder 事务 Top 30 | `android.binder` |
+| `binder.py` | `BinderMixin` | `collect_binder_breakdown()` — Binder 延迟分解 | `android.binder`, `android.binder_breakdown` |
+| `gc.py` | `GcMixin` | `collect_garbage_collection()` — GC 事件分析 | `android.garbage_collection` |
+| `anr.py` | `AnrMixin` | `collect_anrs()` — ANR 检测与分析 | `android.anrs` |
+| `slice_enhanced.py` | `SliceEnhancedMixin` | `collect_slice_cpu_time()` — SI$ slice 真实 CPU 耗时 | `slices.cpu_time` |
+| `slice_enhanced.py` | `SliceEnhancedMixin` | `collect_slice_time_in_state()` — SI$ slice 线程状态分布 | `slices.time_in_state`, `sched.states` |
+| `input.py` | `InputMixin` | `collect_input_latency()` — 输入事件延迟分解 | `android.input` |
+| `sched_latency.py` | `SchedLatencyMixin` | `collect_sched_latency()` — 调度延迟分析 | `sched.latency` |
+| `oom.py` | `OomMixin` | `collect_oom_rss_swap()` — OOM score 转换 + RSS/Swap + LMK 事件 | `android.memory.process`, `android.memory.lmk` |
+| `cpu_utilization.py` | `CpuUtilizationMixin` | `collect_process_cpu_utilization()` — 进程级 CPU 利用率 | `linux.cpu.utilization.process` |
+| `cpu_utilization.py` | `CpuUtilizationMixin` | `collect_thread_cpu_utilization()` — 线程级 CPU 利用率 | `linux.cpu.utilization.thread` |
+| `surfaceflinger.py` | `SurfaceFlingerMixin` | `collect_surfaceflinger_timeline()` — App-SF 帧时间线匹配 | `android.surfaceflinger` |
+
+### 添加新 Stdlib 模块的约定
+
+1. 在 `src/smartinspector/collector/` 下创建新文件，以 Mixin 模式实现
+2. 类名遵循 `{Feature}Mixin` 命名
+3. 方法名遵循 `collect_{metric_name}()` 命名，返回 `list[dict]` 或 `dict`
+4. SQL 查询中使用 `INCLUDE PERFETTO MODULE {module_path};` 引入 stdlib
+5. 在 `PerfettoCollector` 中通过多重继承挂载 Mixin
+6. 查询结果按耗时/大小降序排列，使用 `LIMIT` 控制返回数量