diff --git a/tests/unit/test_embeddings.py b/tests/unit/test_embeddings.py
deleted file mode 100644
index f73d1faf..00000000
--- a/tests/unit/test_embeddings.py
+++ /dev/null
@@ -1,153 +0,0 @@
-"""Unit tests for timmy.memory.embeddings — embedding, similarity, and overlap."""
-
-import math
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-import timmy.memory.embeddings as emb
-from timmy.memory.embeddings import (
-    _keyword_overlap,
-    _simple_hash_embedding,
-    cosine_similarity,
-    embed_text,
-)
-
-# ── _simple_hash_embedding ──────────────────────────────────────────────────
-
-
-class TestSimpleHashEmbedding:
-    def test_returns_list_of_floats(self):
-        vec = _simple_hash_embedding("hello world")
-        assert isinstance(vec, list)
-        assert all(isinstance(v, float) for v in vec)
-
-    def test_dimension_is_128(self):
-        vec = _simple_hash_embedding("test sentence")
-        assert len(vec) == 128
-
-    def test_normalized_unit_vector(self):
-        vec = _simple_hash_embedding("some text here")
-        mag = math.sqrt(sum(x * x for x in vec))
-        assert mag == pytest.approx(1.0, abs=1e-6)
-
-    def test_deterministic(self):
-        a = _simple_hash_embedding("deterministic check")
-        b = _simple_hash_embedding("deterministic check")
-        assert a == b
-
-    def test_different_texts_differ(self):
-        a = _simple_hash_embedding("alpha")
-        b = _simple_hash_embedding("beta")
-        assert a != b
-
-    def test_empty_string(self):
-        vec = _simple_hash_embedding("")
-        assert len(vec) == 128
-        # All zeros normalized → magnitude 0 guarded by `or 1.0`
-        assert all(v == 0.0 for v in vec)
-
-
-# ── cosine_similarity ────────────────────────────────────────────────────────
-
-
-class TestCosineSimilarity:
-    def test_identical_vectors(self):
-        v = [1.0, 2.0, 3.0]
-        assert cosine_similarity(v, v) == pytest.approx(1.0)
-
-    def test_orthogonal_vectors(self):
-        a = [1.0, 0.0]
-        b = [0.0, 1.0]
-        assert cosine_similarity(a, b) == pytest.approx(0.0)
-
-    def test_opposite_vectors(self):
-        a = [1.0, 0.0]
-        b = [-1.0, 0.0]
-        assert cosine_similarity(a, b) == pytest.approx(-1.0)
-
-    def test_zero_vector_returns_zero(self):
-        assert cosine_similarity([0.0, 0.0], [1.0, 2.0]) == 0.0
-        assert cosine_similarity([1.0, 2.0], [0.0, 0.0]) == 0.0
-
-    def test_both_zero_returns_zero(self):
-        assert cosine_similarity([0.0], [0.0]) == 0.0
-
-
-# ── _keyword_overlap ─────────────────────────────────────────────────────────
-
-
-class TestKeywordOverlap:
-    def test_full_overlap(self):
-        assert _keyword_overlap("hello world", "hello world") == pytest.approx(1.0)
-
-    def test_partial_overlap(self):
-        assert _keyword_overlap("hello world", "hello there") == pytest.approx(0.5)
-
-    def test_no_overlap(self):
-        assert _keyword_overlap("foo bar", "baz qux") == pytest.approx(0.0)
-
-    def test_empty_query_returns_zero(self):
-        assert _keyword_overlap("", "some content") == 0.0
-
-    def test_case_insensitive(self):
-        assert _keyword_overlap("Hello WORLD", "hello world") == pytest.approx(1.0)
-
-
-# ── _get_embedding_model ─────────────────────────────────────────────────────
-
-
-class TestGetEmbeddingModel:
-    def setup_method(self):
-        # Reset global state before each test
-        emb.EMBEDDING_MODEL = None
-
-    def teardown_method(self):
-        emb.EMBEDDING_MODEL = None
-
-    def test_skip_embeddings_setting(self):
-        mock_settings = MagicMock()
-        mock_settings.timmy_skip_embeddings = True
-        with patch.dict("sys.modules", {"config": MagicMock(settings=mock_settings)}):
-            emb.EMBEDDING_MODEL = None
-            result = emb._get_embedding_model()
-        assert result is False
-
-    def test_fallback_when_sentence_transformers_missing(self):
-        mock_settings = MagicMock()
-        mock_settings.timmy_skip_embeddings = False
-        with patch.dict("sys.modules", {"config": MagicMock(settings=mock_settings)}):
-            with patch.dict("sys.modules", {"sentence_transformers": None}):
-                emb.EMBEDDING_MODEL = None
-                result = emb._get_embedding_model()
-        assert result is False
-
-    def test_caches_model(self):
-        sentinel = MagicMock()
-        emb.EMBEDDING_MODEL = sentinel
-        assert emb._get_embedding_model() is sentinel
-
-
-# ── embed_text ───────────────────────────────────────────────────────────────
-
-
-class TestEmbedText:
-    def test_uses_fallback_when_model_false(self):
-        with patch.object(emb, "_get_embedding_model", return_value=False):
-            vec = embed_text("test")
-        assert len(vec) == 128
-
-    def test_uses_model_when_available(self):
-        import numpy as np
-
-        mock_model = MagicMock()
-        mock_model.encode.return_value = np.array([0.1, 0.2, 0.3])
-        with patch.object(emb, "_get_embedding_model", return_value=mock_model):
-            vec = embed_text("test")
-        assert vec == [0.1, 0.2, 0.3]
-        mock_model.encode.assert_called_once_with("test")
-
-    def test_uses_fallback_when_model_none(self):
-        with patch.object(emb, "_get_embedding_model", return_value=None):
-            vec = embed_text("test")
-        assert len(vec) == 128