feat: scaffold watch-screen AI pipeline (mock-runnable skeleton)

Modular async pipeline: FrameSource->Vision->context and STT/text->Brain->TTS.
All stages are Protocols; mock backends run end-to-end with no deps/keys.
Real backends included: mss screen capture, Claude vision+brain (guarded imports).

wsai/state.py

@@ -0,0 +1,34 @@
+"""Shared, thread/async-safe screen context.
+
+The perception loop keeps writing the latest ScreenObservation here; the
+conversation loop reads it when the user says something. We only keep the most
+recent observation plus a short ring buffer of recent ones so the Brain can
+notice "the screen changed" without us re-sending every frame.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from collections import deque
+
+from .interfaces import ScreenObservation
+
+
+class SharedScreenContext:
+    def __init__(self, history: int = 8) -> None:
+        self._latest: ScreenObservation | None = None
+        self._recent: deque[ScreenObservation] = deque(maxlen=history)
+        self._lock = asyncio.Lock()
+
+    async def update(self, obs: ScreenObservation) -> None:
+        async with self._lock:
+            self._latest = obs
+            self._recent.append(obs)
+
+    async def latest(self) -> ScreenObservation | None:
+        async with self._lock:
+            return self._latest
+
+    async def recent(self) -> list[ScreenObservation]:
+        async with self._lock:
+            return list(self._recent)