diff --git a/internal/config/config.go b/internal/config/config.go
index 059aa0a8..03a34856 100644
--- a/internal/config/config.go
+++ b/internal/config/config.go
@@ -73,6 +73,7 @@ type RecommendationConfig struct {
 	SkipPenalty         float64 `yaml:"skip_penalty"`
 	JitterMagnitude     float64 `yaml:"jitter_magnitude"`
 	ContextWeight       float64 `yaml:"context_weight"`
+	SimilarityWeight    float64 `yaml:"similarity_weight"`
 	RecentlyPlayedHours int     `yaml:"recently_played_hours"`
 	RadioSize           int     `yaml:"radio_size"`
 	RadioSizeMax        int     `yaml:"radio_size_max"`
@@ -95,6 +96,7 @@ func Default() Config {
 			SkipPenalty:         1.0,
 			JitterMagnitude:     0.1,
 			ContextWeight:       2.0,
+			SimilarityWeight:    2.0,
 			RecentlyPlayedHours: 1,
 			RadioSize:           50,
 			RadioSizeMax:        200,
diff --git a/internal/recommendation/score.go b/internal/recommendation/score.go
index 82f4e940..3c6f061e 100644
--- a/internal/recommendation/score.go
+++ b/internal/recommendation/score.go
@@ -11,23 +11,26 @@ import (
 // ContextualMatchScore is in [0, 1] — max similarity between the user's
 // current session vector and any non-seed contextual_like row for this
 // track. Set by LoadCandidates after a bulk fetch.
+// SimilarityScore is in [0, 1]; 0 when no signal (random fill).
 type ScoringInputs struct {
 	IsGeneralLiked       bool
 	LastPlayedAt         *time.Time // nil = never played
 	PlayCount            int        // total play_events
 	SkipCount            int        // play_events with was_skipped=true
 	ContextualMatchScore float64    // [0, 1]; 0 when no signal
+	SimilarityScore      float64    // [0, 1]; 0 when no signal (random fill)
 }
 
 // ScoringWeights are the operator-tunable knobs. Defaults live in
 // config.RecommendationConfig and are propagated here per request.
 type ScoringWeights struct {
-	BaseWeight      float64
-	LikeBoost       float64
-	RecencyWeight   float64
-	SkipPenalty     float64
-	JitterMagnitude float64
-	ContextWeight   float64
+	BaseWeight       float64
+	LikeBoost        float64
+	RecencyWeight    float64
+	SkipPenalty      float64
+	JitterMagnitude  float64
+	ContextWeight    float64
+	SimilarityWeight float64
 }
 
 // Score computes the weighted-shuffle score per spec §6:
@@ -37,6 +40,7 @@ type ScoringWeights struct {
 //	      + recency_decay * RecencyWeight
 //	      - skip_ratio * SkipPenalty
 //	      + contextual_match_score * ContextWeight
+//	      + similarity_score * SimilarityWeight
 //	      + small_random_jitter
 //
 // Higher score = more likely to surface. rng is a function returning a
@@ -50,6 +54,7 @@ func Score(in ScoringInputs, w ScoringWeights, now time.Time, rng func() float64
 	s += recencyDecay(in.LastPlayedAt, now) * w.RecencyWeight
 	s -= skipRatio(in.PlayCount, in.SkipCount) * w.SkipPenalty
 	s += in.ContextualMatchScore * w.ContextWeight
+	s += in.SimilarityScore * w.SimilarityWeight
 	s += (rng()*2 - 1) * w.JitterMagnitude
 	return s
 }
diff --git a/internal/recommendation/score_test.go b/internal/recommendation/score_test.go
index f4521910..908ab3e5 100644
--- a/internal/recommendation/score_test.go
+++ b/internal/recommendation/score_test.go
@@ -182,3 +182,37 @@ func TestScore_ContextualMatch_ZeroNoEffect(t *testing.T) {
 		t.Errorf("score-with-zero-ctx = %v, score-without = %v; should be equal", withCtx, withoutCtx)
 	}
 }
+
+func TestScore_SimilarityScore_PerfectMatchAtWeight2(t *testing.T) {
+	w := defaultWeights()
+	w.SimilarityWeight = 2.0
+	in := ScoringInputs{SimilarityScore: 1.0}
+	got := Score(in, w, time.Now(), fixedRNG(0.5))
+	// base 1.0 + recency 1.0 (never played) + similarity 2.0 = 4.0
+	want := 4.0
+	if math.Abs(got-want) > 1e-9 {
+		t.Errorf("score = %v, want %v", got, want)
+	}
+}
+
+func TestScore_SimilarityScore_HalfMatchAtWeight2(t *testing.T) {
+	w := defaultWeights()
+	w.SimilarityWeight = 2.0
+	in := ScoringInputs{SimilarityScore: 0.5}
+	got := Score(in, w, time.Now(), fixedRNG(0.5))
+	// base 1.0 + recency 1.0 + similarity 1.0 = 3.0
+	want := 3.0
+	if math.Abs(got-want) > 1e-9 {
+		t.Errorf("score = %v, want %v", got, want)
+	}
+}
+
+func TestScore_SimilarityScore_ZeroNoEffect(t *testing.T) {
+	wWithSim := defaultWeights()
+	wWithSim.SimilarityWeight = 2.0
+	withSim := Score(ScoringInputs{SimilarityScore: 0}, wWithSim, time.Now(), fixedRNG(0.5))
+	withoutSim := Score(ScoringInputs{}, defaultWeights(), time.Now(), fixedRNG(0.5))
+	if math.Abs(withSim-withoutSim) > 1e-9 {
+		t.Errorf("score-with-zero-sim = %v, score-without = %v; should be equal", withSim, withoutSim)
+	}
+}