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).

tests/test_pipeline.py

@@ -0,0 +1,48 @@
+"""Smoke test: the mock pipeline must run end-to-end and route screen context
+into the brain's replies."""
+
+import asyncio
+
+from wsai.backends.mock import (
+    MockBrain,
+    MockFrameSource,
+    MockSTT,
+    MockTTS,
+    MockVision,
+)
+from wsai.pipeline import Pipeline
+
+
+def test_mock_pipeline_runs_and_replies(capsys):
+    replies: list[str] = []
+
+    class CapturingTTS(MockTTS):
+        async def speak(self, reply):
+            replies.append(reply.text)
+
+    pipe = Pipeline(
+        source=MockFrameSource(interval=0.05, limit=3),
+        vision=MockVision(),
+        brain=MockBrain(),
+        stt=MockSTT(script=["화면에 뭐 보여?"], interval=0.1),
+        tts=CapturingTTS(),
+    )
+
+    asyncio.run(asyncio.wait_for(pipe.run(), timeout=5))
+
+    assert replies, "brain produced no reply"
+    # The reply must embed the screen observation → context reached the brain.
+    assert "화면:" in replies[0]
+
+
+def test_history_is_bounded():
+    pipe = Pipeline(
+        source=MockFrameSource(limit=0),
+        vision=MockVision(),
+        brain=MockBrain(),
+        history_turns=3,
+    )
+    for i in range(10):
+        pipe._remember(f"u{i}", f"a{i}")
+    assert len(pipe._history) == 3
+    assert pipe._history[-1] == ("u9", "a9")