diff --git a/.prettierignore b/.prettierignore
index f08ea3e5e7..aefbc2e0b0 100644
--- a/.prettierignore
+++ b/.prettierignore
@@ -13,10 +13,6 @@ public/demo-documents/
 scratch/
 .claude/worktrees/
 .impeccable/
-# tests/worker-visual-capture.test.ts asserts on the exact source text of this
-# file (line-level guards on redaction/normalization order); prettier's
-# line-wrapping would break those assertions, so it owns its own layout.
-worker/main.ts
 # Generated by `supabase gen types`; keep the generator's formatting so
 # regeneration stays churn-free.
 src/lib/supabase/database.types.ts
diff --git a/tests/worker-visual-capture.test.ts b/tests/worker-visual-capture.test.ts
index 1e61e0f100..5b90343d6e 100644
--- a/tests/worker-visual-capture.test.ts
+++ b/tests/worker-visual-capture.test.ts
@@ -74,9 +74,8 @@ describe("worker visual capture hardening", () => {
     expect(workerSource).toContain("const classification = redactImageClassification(args.classification);");
     expect(workerSource).toContain("let classification = redactImageClassification(resolved.classification);");
     expect(workerSource).toContain("caption: classification.caption");
-    expect(workerSource).toContain(
-      "const structuredProfile = normalizeStructuredVisualProfile(redactCaptionMetadataValue(metadata.structured_visual_profile), {",
-    );
+    expect(workerSource).toContain("const structuredProfile = normalizeStructuredVisualProfile(");
+    expect(workerSource).toContain("redactCaptionMetadataValue(metadata.structured_visual_profile)");
   });
 
   it("computes perceptual duplicate groups before caption budget selection", () => {
diff --git a/worker/main.ts b/worker/main.ts
index 922dfc62eb..29cd7d21d3 100644
--- a/worker/main.ts
+++ b/worker/main.ts
@@ -752,7 +752,9 @@ async function getCachedImageClassification(ownerId: string | null, imageHash: s
     : "unclear";
   const score = Number(metadata.clinical_relevance_score);
   const labels = cachedImageLabels(metadata.labels);
-  const cachedCaption = redactCaptionIdentifiers(cleanString(String(data.caption || "").trim() || "Extracted source image."));
+  const cachedCaption = redactCaptionIdentifiers(
+    cleanString(String(data.caption || "").trim() || "Extracted source image."),
+  );
   const assessment = assessClinicalImageUse({
     imageType,
     searchable: Boolean(metadata.searchable),
@@ -761,10 +763,13 @@ async function getCachedImageClassification(ownerId: string | null, imageHash: s
     labels,
     skipReason: typeof metadata.skip_reason === "string" ? metadata.skip_reason : null,
   });
-  const structuredProfile = normalizeStructuredVisualProfile(redactCaptionMetadataValue(metadata.structured_visual_profile), {
-    fallbackText: cachedCaption,
-    fallbackConfidence: score,
-  });
+  const structuredProfile = normalizeStructuredVisualProfile(
+    redactCaptionMetadataValue(metadata.structured_visual_profile),
+    {
+      fallbackText: cachedCaption,
+      fallbackConfidence: score,
+    },
+  );
 
   return {
     image_type: imageType,
@@ -813,8 +818,8 @@ async function setCachedImageClassification(args: {
         clinical_signal_score: classification.clinical_signal_score,
         admin_signal_score: classification.admin_signal_score,
         structured_visual_profile: (classification as ImageClassificationWithVisualProfile).structured_visual_profile,
-        structured_extraction_confidence:
-          (classification as ImageClassificationWithVisualProfile).structured_extraction_confidence,
+        structured_extraction_confidence: (classification as ImageClassificationWithVisualProfile)
+          .structured_extraction_confidence,
         image_policy_version: clinicalImagePolicyVersion,
         visual_intelligence_version: visualIntelligenceVersion,
         image_caption_cache_version: imageCaptionCacheVersion,