diff --git a/docs/plans/2026-07-19-scanner-engine-fuzzy-diff.md b/docs/plans/2026-07-19-scanner-engine-fuzzy-diff.md
index bf822ee..30cd290 100644
--- a/docs/plans/2026-07-19-scanner-engine-fuzzy-diff.md
+++ b/docs/plans/2026-07-19-scanner-engine-fuzzy-diff.md
@@ -62,9 +62,9 @@
 - [x] run tests — must pass before task 3
 
 ### Task 3: Implement similarity scoring in `internal/scanner`
-- [ ] create `internal/scanner/scanner.go` with `Similarity(a, b string) float64` using `normalize.NormalizeString` + `fuzzy.Ratio` (normalized to 0.0–1.0); define `IsMatch(a, b string, threshold float64) bool`
-- [ ] write tests `internal/scanner/scanner_test.go` (table-driven): exact match → 1.0, `(Remastered)` / year variants still match above 0.85, clearly different titles → below threshold, empty-string handling
-- [ ] run tests — must pass before task 4
+- [x] create `internal/scanner/scanner.go` with `Similarity(a, b string) float64` using `normalize.NormalizeString` + `fuzzy.LevenshteinDistance` (normalized to 0.0–1.0); define `IsMatch(a, b string, threshold float64) bool`
+- [x] write tests `internal/scanner/scanner_test.go` (table-driven): exact match → 1.0, `(Remastered)` / year variants still match above 0.85, clearly different titles → below threshold, empty-string handling
+- [x] run tests — must pass before task 4
 
 ### Task 4: Implement the diff engine (missing-release detection)
 - [ ] add `type MissingRelease struct { RGID, ArtistID, Title, Type, ReleaseDate string }` in `internal/scanner`
@@ -99,7 +99,7 @@
   - `bracketRe` = `\[[^\]]*\]` , `parenRe` = `\([^)]*\)`, `yearRe` = `\b(1[0-9]{3}|2[0-9]{3})\b`, `spaceRe` = `\s+`.
   - `NormalizeString`: lowercase → strip brackets/parens → strip years → replace `-`/`_` with space → keep `[a-z0-9 ]` → collapse spaces → trim.
   - `NormalizeArtistName`: `NormalizeString` then strip leading `the `/`a `/`an ` tokens.
-- **Similarity**: `fuzzy.Ratio(normalize(a), normalize(b))` returns an int 0–100; `Similarity` returns `float64(ratio)/100.0`. `IsMatch` returns `Similarity(a,b,threshold) >= threshold`.
+- **Similarity**: `fuzzy.LevenshteinDistance(normalize(a), normalize(b))` returns an int edit distance; `Similarity` returns `1.0 - float64(dist)/float64(maxLen)` (clamped to [0.0, 1.0]). Empty/whitespace-only inputs normalize to empty and score 0.0 (no false match). `IsMatch` returns `Similarity(a,b) >= threshold`. Note: `fuzzy.Ratio` does not exist in `lithammer/fuzzysearch` v1.1.8 — `LevenshteinDistance` is used instead (contrary to earlier plan assumption).
 - **Diff algorithm**: per external release (filtered by `!IsIgnored`), compare normalized title against each local album of the same `ArtistID`; missing if no `IsMatch` at `threshold`.
 - **Config contract**: `threshold` passed from `config.Scanner.FuzzyThreshold` (default 0.85). Decide: if caller passes `0`, use default — implement explicitly and document.
 - **No new DB tables** in this plan (compute-only per user decision).
diff --git a/internal/scanner/scanner.go b/internal/scanner/scanner.go
new file mode 100644
index 0000000..a1e12e2
--- /dev/null
+++ b/internal/scanner/scanner.go
@@ -0,0 +1,56 @@
+// Package scanner implements the core fuzzy-diff engine of NaviWatcher.
+//
+// It compares a user's local albums (from Navidrome) against an artist's
+// external discography (from MusicBrainz) and reports the releases that are
+// present externally but have no sufficiently similar local album.
+package scanner
+
+import (
+	"github.com/lithammer/fuzzysearch/fuzzy"
+	"naviwatcher/internal/normalize"
+)
+
+// Similarity returns a normalized similarity score in the range [0.0, 1.0]
+// between two strings. The strings are normalized first (lowercased,
+// bracketed/parenthesized content and years stripped, special characters
+// removed), then compared with a Levenshtein-distance-based ratio.
+//
+// A score of 1.0 means the normalized strings are identical; 0.0 means they
+// share nothing. Empty strings (after normalization) always score 0.0.
+func Similarity(a, b string) float64 {
+	na := normalize.NormalizeString(a)
+	nb := normalize.NormalizeString(b)
+
+	// Two empty inputs are not considered a match.
+	if na == "" && nb == "" {
+		return 0.0
+	}
+	// One empty, one non-empty: no similarity.
+	if na == "" || nb == "" {
+		return 0.0
+	}
+
+	dist := fuzzy.LevenshteinDistance(na, nb)
+	maxLen := len(na)
+	if len(nb) > maxLen {
+		maxLen = len(nb)
+	}
+
+	// Guard against maxLen == 0 (already handled above, but kept for safety).
+	if maxLen == 0 {
+		return 0.0
+	}
+
+	// 1.0 - normalized distance → higher is more similar.
+	score := 1.0 - float64(dist)/float64(maxLen)
+	if score < 0.0 {
+		return 0.0
+	}
+	return score
+}
+
+// IsMatch reports whether a and b are similar enough to be considered the
+// same release, given the provided threshold in [0.0, 1.0].
+func IsMatch(a, b string, threshold float64) bool {
+	return Similarity(a, b) >= threshold
+}
diff --git a/internal/scanner/scanner_test.go b/internal/scanner/scanner_test.go
new file mode 100644
index 0000000..3b7bf0b
--- /dev/null
+++ b/internal/scanner/scanner_test.go
@@ -0,0 +1,131 @@
+package scanner
+
+import "testing"
+
+func TestSimilarity(t *testing.T) {
+	tests := []struct {
+		name     string
+		a        string
+		b        string
+		want     float64
+		epsilon  float64
+	}{
+		{
+			name:    "exact match scores 1.0",
+			a:       "The Wall",
+			b:       "The Wall",
+			want:    1.0,
+			epsilon: 1e-9,
+		},
+		{
+			name:    "case-insensitive exact match scores 1.0",
+			a:       "The Wall",
+			b:       "the wall",
+			want:    1.0,
+			epsilon: 1e-9,
+		},
+		{
+			name:    "remastered variant stays above threshold",
+			a:       "The Wall",
+			b:       "The Wall (Remastered)",
+			want:    1.0, // parenthesized content is stripped during normalization
+			epsilon: 1e-9,
+		},
+		{
+			name: "year-suffixed variant stays above threshold",
+			a:    "Abbey Road",
+			b:    "Abbey Road (2019 Remix)",
+			// After normalization both collapse to "abbey road" → identical.
+			want:    1.0,
+			epsilon: 1e-9,
+		},
+		{
+			name:    "clearly different titles score below 0.85",
+			a:       "The Wall",
+			b:       "Completely Different Album",
+			want:    0.0,
+			epsilon: 1e-9,
+		},
+		{
+			name:    "substring-ish title scores moderately",
+			a:       "Dark Side of the Moon",
+			b:       "Dark Side of the Moon Part II",
+			want:    0.0, // non-empty; value asserted only as below threshold
+			epsilon: 1e-9,
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			got := Similarity(tt.a, tt.b)
+			switch {
+			case tt.name == "clearly different titles score below 0.85" ||
+				tt.name == "substring-ish title scores moderately":
+				if got >= 0.85 {
+					t.Errorf("Similarity(%q, %q) = %v, want < 0.85", tt.a, tt.b, got)
+				}
+			default:
+				if diff := got - tt.want; diff > tt.epsilon || diff < -tt.epsilon {
+					t.Errorf("Similarity(%q, %q) = %v, want %v (+/- %v)", tt.a, tt.b, got, tt.want, tt.epsilon)
+				}
+			}
+		})
+	}
+}
+
+func TestSimilarity_EmptyStrings(t *testing.T) {
+	// Both empty → no match (0.0).
+	if got := Similarity("", ""); got != 0.0 {
+		t.Errorf("Similarity(%q, %q) = %v, want 0.0", "", "", got)
+	}
+	// One empty, one non-empty → no similarity.
+	if got := Similarity("The Wall", ""); got != 0.0 {
+		t.Errorf("Similarity(%q, %q) = %v, want 0.0", "The Wall", "", got)
+	}
+	if got := Similarity("", "The Wall"); got != 0.0 {
+		t.Errorf("Similarity(%q, %q) = %v, want 0.0", "", "The Wall", got)
+	}
+	// Whitespace-only inputs normalize to empty → no match.
+	if got := Similarity("   ", "The Wall"); got != 0.0 {
+		t.Errorf("Similarity(%q, %q) = %v, want 0.0", "   ", "The Wall", got)
+	}
+}
+
+func TestIsMatch(t *testing.T) {
+	const threshold = 0.85
+
+	tests := []struct {
+		name     string
+		a        string
+		b        string
+		expected bool
+	}{
+		{name: "exact match is a match", a: "The Wall", b: "The Wall", expected: true},
+		{name: "remastered variant is a match", a: "The Wall", b: "The Wall (Remastered)", expected: true},
+		{name: "year variant is a match", a: "Abbey Road", b: "Abbey Road (2019)", expected: true},
+		{name: "clearly different is not a match", a: "The Wall", b: "Random Noise", expected: false},
+		{name: "empty vs non-empty is not a match", a: "", b: "The Wall", expected: false},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			if got := IsMatch(tt.a, tt.b, threshold); got != tt.expected {
+				t.Errorf("IsMatch(%q, %q, %v) = %v, want %v", tt.a, tt.b, threshold, got, tt.expected)
+			}
+		})
+	}
+}
+
+func TestIsMatch_ThresholdBoundary(t *testing.T) {
+	// A moderately different title should be a match at a low threshold but
+	// not at a high one, confirming the boundary is inclusive (>=).
+	a, b := "The Wall", "The Wall Live"
+	low := IsMatch(a, b, 0.5)
+	high := IsMatch(a, b, 0.99)
+	if !low {
+		t.Errorf("IsMatch(%q, %q, 0.5) = false, want true", a, b)
+	}
+	if high {
+		t.Errorf("IsMatch(%q, %q, 0.99) = true, want false", a, b)
+	}
+}