diff --git a/.github/workflows/branch.yaml b/.github/workflows/branch.yaml
index 84d3b48dc..418dee41d 100644
--- a/.github/workflows/branch.yaml
+++ b/.github/workflows/branch.yaml
@@ -10,7 +10,7 @@ jobs:
     name: Build and Deploy
     runs-on: ubuntu-latest
     env:
-      GH_API_TOKEN: ${{ secrets.GH_API_TOKEN }}
+      GH_API_TOKEN: ${{ secrets.GITHUB_TOKEN }}
       SLACK_BOT: ${{ secrets.SLACK_BOT }}
       NETLIFY_AUTH_TOKEN: ${{ secrets.NETLIFY_AUTH_TOKEN }}
       GOOGLE_CONTAINER_ID: ${{ secrets.GOOGLE_CONTAINER_ID }}
@@ -26,7 +26,7 @@ jobs:
           yarn install
       - name: Update versions from GitHub
         env:
-          GH_API_TOKEN: ${{ secrets.GH_API_TOKEN }}
+          GH_API_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
           node _build_scripts/update-config-versions.js
       - name: Build Docusarus project
diff --git a/.github/workflows/pull_requests.yaml b/.github/workflows/pull_requests.yaml
index ae19053c6..7548a6c50 100644
--- a/.github/workflows/pull_requests.yaml
+++ b/.github/workflows/pull_requests.yaml
@@ -21,7 +21,7 @@ jobs:
           yarn install
       - name: Update versions from GitHub
         env:
-          GH_API_TOKEN: ${{ secrets.GH_API_TOKEN }}
+          GH_API_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
           node _build_scripts/update-config-versions.js
       - name: Build a dev version
diff --git a/_build_scripts/link-validator.js b/_build_scripts/link-validator.js
index eed9c5162..2b3c8715b 100644
--- a/_build_scripts/link-validator.js
+++ b/_build_scripts/link-validator.js
@@ -51,6 +51,7 @@ const domainsToIgnore = [
     'https://static.scarf.sh',
     'https://www.snowflake.com',
     'https://stackoverflow.com/',
+    'https://www.tim-kleyersburg.de/', // 403s automated requests (site loads fine in a browser); community PHP client author link
     'https://towardsdatascience.com/',
     'https://voyageai.com/',
     'https://weaviateagents.featurebase.app',
diff --git a/_includes/code/llms-txt/python/query_agent.py b/_includes/code/llms-txt/python/query_agent.py
index 7b2c34121..77a26afb1 100644
--- a/_includes/code/llms-txt/python/query_agent.py
+++ b/_includes/code/llms-txt/python/query_agent.py
@@ -28,7 +28,7 @@
 print(response.final_answer)
 
 # Retrieval only (no generation)
-search_response = qa.search("sci-fi movies", limit=5)
+search_response = qa.search("sci-fi movies", filtering="recall", limit=5)
 # END llms_query_agent
 
 assert response.final_answer
diff --git a/_includes/code/python/quickstart.short.query_agent.py b/_includes/code/python/quickstart.short.query_agent.py
index 07cafb325..05663434e 100644
--- a/_includes/code/python/quickstart.short.query_agent.py
+++ b/_includes/code/python/quickstart.short.query_agent.py
@@ -18,7 +18,7 @@
     qa = QueryAgent(client=client, collections=["Movie"])
 
     # Step 2.3: Perform a query using Search Mode
-    response = qa.search("Find a cool sci-fi movie.", limit=1)
+    response = qa.search("Find a cool sci-fi movie.", filtering="recall", limit=1)
     # highlight-end
 
     # Print the response
diff --git a/docs/query-agent/_includes/code/query_agent.mts b/docs/query-agent/_includes/code/query_agent.mts
index 61cd68907..f5a042d56 100644
--- a/docs/query-agent/_includes/code/query_agent.mts
+++ b/docs/query-agent/_includes/code/query_agent.mts
@@ -141,6 +141,7 @@ clothingResponse.display();
 // START BasicSearchQuery
 // Perform a search using Search Mode (retrieval only, no answer generation)
 const basicSearchResponse = await qa.search("Find me some vintage shoes under $70", {
+    filtering: "recall",
     limit: 10
 })
 
@@ -154,6 +155,7 @@ for (const obj of basicSearchResponse.searchResults.objects) {
 // Diversity ranking needs a vectorizer it can resolve. Scope the call to a
 // single collection with a target vector so the agent knows what to use.
 const diversitySearchResponse = await qa.search("summer shoes", {
+    filtering: "recall",
     limit: 10,
     diversityWeight: 0.5,
     collections: [{
@@ -179,6 +181,7 @@ basicResponse.display();
 // START SearchModeResponseStructure
 // SearchModeResponse structure for TypeScript
 const searchResponse = await qa.search("winter boots for under $100", {
+    filtering: "recall",
     limit: 5
 })
 
@@ -206,6 +209,7 @@ for (const obj of searchResponse.searchResults.objects) {
 // Search with pagination
 const responsePage1 = await qa.search(
     "Find summer shoes and accessories between $50 and $100 that have the tag 'sale'", {
+    filtering: "recall",
     limit: 3,
 })
 
diff --git a/docs/query-agent/_includes/code/query_agent.py b/docs/query-agent/_includes/code/query_agent.py
index e8df3d9c7..bd58dac5d 100644
--- a/docs/query-agent/_includes/code/query_agent.py
+++ b/docs/query-agent/_includes/code/query_agent.py
@@ -211,7 +211,7 @@
 
 # START BasicSearchQuery
 # Perform a search using Search Mode (retrieval only, no answer generation)
-search_response = qa.search("Find me some vintage shoes under $70", limit=10)
+search_response = qa.search("Find me some vintage shoes under $70", filtering="recall", limit=10)
 
 # Access the search results
 for obj in search_response.search_results.objects:
@@ -220,7 +220,7 @@
 
 # START SearchModeResponseStructure
 # SearchModeResponse structure for Python
-search_response = qa.search("winter boots for under $100", limit=5)
+search_response = qa.search("winter boots for under $100", filtering="recall", limit=5)
 
 # Access different parts of the response
 print(f"Original query: {search_response.searches[0].query}")
@@ -244,6 +244,7 @@
 # Search with pagination
 response_page_1 = qa.search(
     "Find summer shoes and accessories between $50 and $100 that have the tag 'sale'",
+    filtering="recall",
     limit=3,
 )
 
@@ -269,6 +270,7 @@
 # START DiversityRanking
 search_response = qa.search(
     "summer shoes",
+    filtering="recall",
     limit=10,
     diversity_weight=0.5,
     collections=[
diff --git a/docs/query-agent/_includes/code/query_agent_get_started.py b/docs/query-agent/_includes/code/query_agent_get_started.py
index 2cf55a8dd..9abaea4be 100644
--- a/docs/query-agent/_includes/code/query_agent_get_started.py
+++ b/docs/query-agent/_includes/code/query_agent_get_started.py
@@ -135,6 +135,7 @@
 # START SearchMode
 search_response = agent.search(
     "Find me some vintage shoes under $70",
+    filtering="recall",
     limit=10,
 )
 
diff --git a/docs/query-agent/_includes/code/quickstart.mts b/docs/query-agent/_includes/code/quickstart.mts
index 727b5c932..0693851c5 100644
--- a/docs/query-agent/_includes/code/quickstart.mts
+++ b/docs/query-agent/_includes/code/quickstart.mts
@@ -51,6 +51,7 @@ qa = new QueryAgent(client, {
 // START BasicSearchQuery
 const searchResponse = await qa.search(
     "Find me some vintage shoes under $70", {
+    filtering: "recall",
     limit: 10,
 });
 // END BasicSearchQuery
diff --git a/docs/query-agent/_includes/code/quickstart.py b/docs/query-agent/_includes/code/quickstart.py
index 73af640cb..013cc3ce6 100644
--- a/docs/query-agent/_includes/code/quickstart.py
+++ b/docs/query-agent/_includes/code/quickstart.py
@@ -53,7 +53,8 @@
 
 # START BasicSearchQuery
 search_response = qa.search(
-    "Find me some vintage shoes under $70", 
+    "Find me some vintage shoes under $70",
+    filtering="recall",
     limit=10
 )
 # END BasicSearchQuery
diff --git a/docs/query-agent/_includes/code/search_mode.mts b/docs/query-agent/_includes/code/search_mode.mts
index fc9f355b8..e07231ec5 100644
--- a/docs/query-agent/_includes/code/search_mode.mts
+++ b/docs/query-agent/_includes/code/search_mode.mts
@@ -39,6 +39,7 @@ await populateWeaviate(client);
 
 // START BasicSearchMode
 const searchResponse = await qa.search("Find me some vintage shoes under $70", {
+    filtering: "recall",
     limit: 10,
 });
 
@@ -50,6 +51,7 @@ for (const obj of searchResponse.searchResults.objects) {
 
 // START DiversityRanking
 const diversitySearchResponse = await qa.search("summer shoes", {
+    filtering: "recall",
     limit: 10,
     diversityWeight: 0.5,
     collections: [{
@@ -67,6 +69,7 @@ for (const obj of diversitySearchResponse.searchResults.objects) {
 // Search with pagination
 const responsePage1 = await qa.search(
     "Find summer shoes and accessories between $50 and $100 that have the tag 'sale'", {
+    filtering: "recall",
     limit: 3,
 });
 
diff --git a/docs/query-agent/_includes/code/search_mode.py b/docs/query-agent/_includes/code/search_mode.py
index d1bab68d4..281fdb037 100644
--- a/docs/query-agent/_includes/code/search_mode.py
+++ b/docs/query-agent/_includes/code/search_mode.py
@@ -41,6 +41,7 @@
 # START BasicSearchMode
 search_response = qa.search(
     query="Find me some vintage shoes under $70",
+    filtering="recall",
     limit=10,
 )
 
@@ -62,6 +63,7 @@
 
 search_response = qa.search(
     "summer shoes",
+    filtering="recall",
     limit=10,
     diversity_weight=0.5,
 )
@@ -74,6 +76,7 @@
 # Search with pagination
 response_page_1 = qa.search(
     "Find summer shoes and accessories between $50 and $100 that have the tag 'sale'",
+    filtering="recall",
     limit=3,
 )
 
@@ -135,6 +138,7 @@
 # START AsyncSearch
 await async_qa.search(
     query="Find me some vintage shoes under $70",
+    filtering="recall",
     limit=10,
 )
 # END AsyncSearch
@@ -161,6 +165,7 @@ async def _async_run_for_testing():
 
     await async_qa.search(
         query="Find me some vintage shoes under $70",
+        filtering="recall",
         limit=10,
     )
     await async_client.close()
diff --git a/docs/query-agent/guides/search_mode.md b/docs/query-agent/guides/search_mode.md
index ff4d6a24c..d2e87a6b8 100644
--- a/docs/query-agent/guides/search_mode.md
+++ b/docs/query-agent/guides/search_mode.md
@@ -67,7 +67,7 @@ The `.search()` method accepts several arguments:
 | `query` | `str \| list[ChatMessage]` | The user query you want the agent to search with. This can be a simple string (`"Find me some vintage shoes under $70"`) or a list of chat messages (for conversational context). [See the page on multi-turn conversations for more detail](../reference/multi_turn_conversations.md). |
 | `collections` | `list[str \| QueryAgentCollectionConfig] \| None` | The name(s) of the collections to search. You can pass one or many collection names as a list of strings (e.g., `["ECommerce", "BookSales"]`), or provide collection configuration objects for more control. If specified in the `ask` method, it will overwrite those defined in the instantiation of `QueryAgent`. [See the page on collection configuration for more detail](../reference/advanced_collections.md). |
 | `limit` | `int` | The maximum number of results returned in this page of results. Defaults to `20`. Use [`.next()`](#pagination) to fetch additional pages. |
-| `filtering` | `Literal["recall", "precision"]` | Either `"recall"` or `"precision"` to control filter generation. `"recall"` favors more results across filter interpretations; `"precision"` favors strict intent match. See [Customized filtering](#customized-filtering) below. |
+| `filtering` | `Literal["recall", "precision"]` | **Required.** Either `"recall"` or `"precision"` to control filter generation. `"recall"` favors more results across filter interpretations; `"precision"` favors strict intent match. Pass `"recall"` for most cases. See [Customized filtering](#customized-filtering) below. |
 | `diversity_weight` | `float \| None` | A value between `0.0` and `1.0` that biases the result ranking towards diversity using Maximal Marginal Relevance (MMR). See [Diversity ranking](#diversity-ranking) below. |
 
 </TabItem>
@@ -77,7 +77,7 @@ The `.search()` method accepts several arguments:
 | `query` | `string \| ChatMessage[]` | The user query you want the agent to search with. This can be a simple string (`"Find me some vintage shoes under $70"`) or a list of chat messages (for conversational context). [See the page on multi-turn conversations for more detail](../reference/multi_turn_conversations.md). |
 | `collections` | `(string \| QueryAgentCollectionConfig)[]` | The name(s) of the collections to search. You can pass one or many collection names as a list of strings (e.g., `["ECommerce", "BookSales"]`), or provide collection configuration objects for more control. If specified in the `ask` method, it will overwrite those defined in the instantiation of `QueryAgent`. [See the page on collection configuration for more detail](../reference/advanced_collections.md). |
 | `limit` | `number` | The maximum number of results returned in this page of results. Defaults to `20`. Use [`.next()`](#pagination) to fetch additional pages. |
-| `filtering` | `"recall" \| "precision"` | Either `"recall"` or `"precision"` to control filter generation. `"recall"` favors more results across filter interpretations; `"precision"` favors strict intent match. See [Customized filtering](#customized-filtering) below. |
+| `filtering` | `"recall" \| "precision"` | **Required.** Either `"recall"` or `"precision"` to control filter generation. `"recall"` favors more results across filter interpretations; `"precision"` favors strict intent match. Pass `"recall"` for most cases. See [Customized filtering](#customized-filtering) below. |
 | `diversityWeight` | `number` | A value between `0.0` and `1.0` that biases the result ranking towards diversity using Maximal Marginal Relevance (MMR). See [Diversity ranking](#diversity-ranking) below. |
 
 </TabItem>
@@ -89,7 +89,9 @@ For more advanced searches, you can also specify _additional filters_ within the
 
 Search Mode uses query rewriting to transform your original query into one or multiple Weaviate queries, each with either a search query, metadata filters, or both. The `filtering` parameter controls how many Weaviate queries are generated.
 
-- **`"recall"`** (default): Generates multiple Weaviate queries spanning different filters and interpretations of the user query. You should use these when you prefer to get results, even if they don't match every criteria in your query.
+`filtering` is a required argument; pass either `"recall"` or `"precision"`. `"recall"` is recommended when you want more results.
+
+- **`"recall"`** (recommended): Generates multiple Weaviate queries spanning different filters and interpretations of the user query. You should use these when you prefer to get results, even if they don't match every criteria in your query.
 
 - **`"precision"`**: Generates a single Weaviate query targeting the most likely interpretation of the user query. You should use this when you want the results to follow your query intent closely, even if that means potentially receiving no results.