docs+skills: add main UI/UX visual-truth PRD and skill links

.agents/skills/rlm-mem/brain/scripts/test_layered_retrieval.py

@@ -0,0 +1,95 @@
+"""
+Tests for layered memory retrieval with source attribution.
+
+Run: python -m unittest brain.scripts.test_layered_retrieval -v
+"""
+
+import tempfile
+import unittest
+from pathlib import Path
+
+from brain.scripts.layered_memory_store import LayeredMemoryStore
+from brain.scripts.memory_policy import MemoryPolicy
+
+
+class TestLayeredRetrieval(unittest.TestCase):
+    def test_retrieve_all_returns_records_with_attribution(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            project_root = Path(tmpdir)
+            # Configure policy to read from multiple layers
+            policy = MemoryPolicy(
+                project_root=project_root,
+                read_layers=["project_agent", "project_global"],
+                write_layers=["project_agent", "project_global"],
+            )
+            store = LayeredMemoryStore(policy=policy, agent_id="agent-1")
+
+            # Write to project_global
+            store.append_entry(
+                layer="project_global",
+                record={
+                    "id": "global-1",
+                    "created_at": "2026-02-11T00:00:00Z",
+                    "scope": "project_global",
+                    "entry_type": "fact",
+                    "content": "Global Fact",
+                    "project_id": "rlm-mem",
+                },
+            )
+
+            # Write to project_agent
+            store.append_entry(
+                layer="project_agent",
+                record={
+                    "id": "agent-1",
+                    "created_at": "2026-02-11T00:00:01Z",
+                    "scope": "project_agent",
+                    "agent_id": "agent-1",
+                    "entry_type": "note",
+                    "content": "Agent Note",
+                    "project_id": "rlm-mem",
+                },
+            )
+
+            all_records = store.get_all_records()
+
+            # Precedence should be project_agent then project_global
+            self.assertEqual(len(all_records), 2)
+            
+            # First record should be from project_agent
+            self.assertEqual(all_records[0]["id"], "agent-1")
+            self.assertEqual(all_records[0]["source_layer"], "project_agent")
+            self.assertIn("agents", all_records[0]["source_path"])
+            self.assertIn("agent-1", all_records[0]["source_path"])
+
+            # Second record should be from project_global
+            self.assertEqual(all_records[1]["id"], "global-1")
+            self.assertEqual(all_records[1]["source_layer"], "project_global")
+            self.assertIn("global", all_records[1]["source_path"])
+
+    def test_retrieval_respects_policy_layer_order(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            project_root = Path(tmpdir)
+            # Reverse order for testing
+            policy = MemoryPolicy(
+                project_root=project_root,
+                read_layers=["project_global", "project_agent"],
+                write_layers=["project_agent", "project_global"],
+            )
+            store = LayeredMemoryStore(policy=policy, agent_id="agent-1")
+
+            store.append_entry(layer="project_global", record={
+                "id": "g1", "created_at": "2026-02-11T00:00:00Z", "scope": "project_global",
+                "entry_type": "fact", "content": "G", "project_id": "rlm-mem"
+            })
+            store.append_entry(layer="project_agent", record={
+                "id": "a1", "created_at": "2026-02-11T00:00:00Z", "scope": "project_agent",
+                "agent_id": "agent-1", "entry_type": "fact", "content": "A", "project_id": "rlm-mem"
+            })
+
+            all_records = store.get_all_records()
+            self.assertEqual(all_records[0]["id"], "g1")
+            self.assertEqual(all_records[1]["id"], "a1")
+
+if __name__ == "__main__":
+    unittest.main(verbosity=2)