From 588808e98285ca4e6d6988ec014f1196f95ab252 Mon Sep 17 00:00:00 2001
From: Khelan Modi <khelanmodi@users.noreply.github.com>
Date: Tue, 26 May 2026 14:31:12 -0700
Subject: [PATCH] Fix cosmosSearch vector field name: query -> vector

The cosmosSearch operator in Azure DocumentDB's $search aggregation
stage takes the query embedding under the ector field, not query.
The previous examples would fail at runtime (or silently return wrong
results depending on server version), and the agent surfaces these
files verbatim when generating vector-search code.

Fixes three occurrences:
- skills/vector-search/vector-knn-query.md (both the incorrect and
  correct examples)
- skills/full-text-search/fts-hybrid-search.md (vector arm of the
  hybrid example)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---
 skills/full-text-search/fts-hybrid-search.md | 2 +-
 skills/vector-search/vector-knn-query.md     | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/skills/full-text-search/fts-hybrid-search.md b/skills/full-text-search/fts-hybrid-search.md
index bcad938..8d215a6 100644
--- a/skills/full-text-search/fts-hybrid-search.md
+++ b/skills/full-text-search/fts-hybrid-search.md
@@ -68,7 +68,7 @@ const kwHits = await db.products.aggregate([
 // Vector arm
 const qv = await embed(userQuery);
 const vecHits = await db.products.aggregate([
-  { $search: { cosmosSearch: { path: "embedding", query: qv, k: 50 } } },
+  { $search: { cosmosSearch: { path: "embedding", vector: qv, k: 50 } } },
   { $project: { _id: 1, vec: { $meta: "searchScore" } } }
 ]).toArray();
 
diff --git a/skills/vector-search/vector-knn-query.md b/skills/vector-search/vector-knn-query.md
index a5b2d1e..a7171fa 100644
--- a/skills/vector-search/vector-knn-query.md
+++ b/skills/vector-search/vector-knn-query.md
@@ -20,7 +20,7 @@ Or post-filtering that drops 90% of your top-k before the user sees anything:
 
 ```javascript
 db.products.aggregate([
-  { $search: { cosmosSearch: { path: "embedding", query: qv, k: 10 } } },
+  { $search: { cosmosSearch: { path: "embedding", vector: qv, k: 10 } } },
   { $match: { inStock: true, price: { $lte: 100 } } } // may leave 1-2 results
 ]);
 ```
@@ -37,7 +37,7 @@ const hits = await db.products.aggregate([
     $search: {
       cosmosSearch: {
         path: "embedding",
-        query: queryVector,
+        vector: queryVector,
         k: 10,
         lSearch: 100, // higher than k, boosts recall
         filter: {