fixed typo in filename

Author: HeidiSteen

articles/search/.openpublishing.redirection.search.json

@@ -11,7 +11,7 @@
             "redirect_document_id": true
         },
                 {
-            "source_path_from_root": "/articles/search/tutorial-skillset-md",
+            "source_path_from_root": "/articles/search/tutorial-skillset.md",
             "redirect_url": "/azure/search/tutorial-skillset.md",
             "redirect_document_id": true
         },

articles/search/chat-completion-skill-example-usage.md

@@ -117,7 +117,7 @@ This section supplements the [skill reference](cognitive-search-defining-skillse
 Once the basic framework of your skillset is created and Azure AI services is configured, you can focus on each individual image skill, defining inputs and source context, and mapping outputs to fields in either an index or knowledge store.
 
 > [!NOTE]
-> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset-md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
+> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset.md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
 
 ### Example inputs for image processing
 

articles/search/cognitive-search-concept-image-scenarios.md

@@ -166,7 +166,7 @@ This section supplements the [skill reference](cognitive-search-predefined-skill
 Once the basic framework of your skillset is created and Azure AI services is configured, you can focus on each individual image skill, defining inputs and source context, and mapping outputs to fields in either an index or knowledge store.
 
 > [!NOTE]
-> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset-md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
+> For an example skillset that combines image processing with downstream natural language processing, see [REST Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset.md). It shows how to feed skill imaging output into entity recognition and key phrase extraction.
 
 ### Inputs for image processing
 

articles/search/cognitive-search-concept-intro.md

@@ -135,7 +135,7 @@ To repeat any of the above steps, [reset the indexer](search-howto-reindex.md) b
 ## Next steps
 
 + [Quickstart: Create a skillset for AI enrichment](search-get-started-skillset.md)
-+ [Tutorial: Learn about the AI enrichment REST APIs](tutorial-skillset-md)
++ [Tutorial: Learn about the AI enrichment REST APIs](tutorial-skillset.md)
 + [Skillset concepts](cognitive-search-working-with-skillsets.md)
 + [Knowledge store concepts](knowledge-store-concept-intro.md)
 + [Create a skillset](cognitive-search-defining-skillset.md)

articles/search/cognitive-search-concept-troubleshooting.md

@@ -71,7 +71,7 @@ For [parallel indexing](search-howto-large-index.md), distribute your data into
 ## See also
 
 + [Quickstart: Create an AI enrichment pipeline in the Azure portal](search-get-started-skillset.md)
-+ [Tutorial: Learn AI enrichment REST APIs](tutorial-skillset-md)
++ [Tutorial: Learn AI enrichment REST APIs](tutorial-skillset.md)
 + [How to configure blob indexers](search-howto-indexing-azure-blob-storage.md)
 + [How to define a skillset](cognitive-search-defining-skillset.md)
 + [How to map enriched fields to an index](cognitive-search-output-field-mapping.md)

articles/search/cognitive-search-predefined-skills.md

@@ -81,4 +81,4 @@ For guidance on creating a custom skill, see [Define a custom interface](cogniti
 
 + [How to define a skillset](cognitive-search-defining-skillset.md)
 + [Custom Skills interface definition](cognitive-search-custom-skill-interface.md)
-+ [Tutorial: Enriched indexing with AI](tutorial-skillset-md)
++ [Tutorial: Enriched indexing with AI](tutorial-skillset.md)

articles/search/samples-rest.md

@@ -30,7 +30,7 @@ Code samples from the Azure AI Search team demonstrate features and workflows. M
 | [quickstart](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart) | Source code for the REST portion of [Quickstart: Full-text search](search-get-started-text.md). This sample covers the basic workflow for creating, loading, and querying a search index using sample data. |
 | [quickstart-vectors](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-vectors) | Source code for [Quickstart: Vector search using REST APIs](search-get-started-vector.md). This sample covers the basic workflow for indexing and querying vector data. |
 | [quickstart-agentic-retrieval](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-agentic-retrieval) | Source code for the REST portion of [Quickstart: Run agentic retrieval in Azure AI Search](search-get-started-agentic-retrieval.md). This sample shows you how to create a knowledge agent in Azure AI Search to integrate LLM reasoning into query planning. |
-| [skillset-tutorial](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skillset-tutorial) | Source code for [Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset-md). This sample shows you how to create a skillset that iterates over Azure blobs to extract information and infer structure.|
+| [skillset-tutorial](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skillset-tutorial) | Source code for [Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset.md). This sample shows you how to create a skillset that iterates over Azure blobs to extract information and infer structure.|
 | [skill examples](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skill-examples) | Skillset examples in indexer pipelines that include indexes and indexers so that you can follow field mappings, output field mappings, and source paths. |
 | [debug-sessions](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Debug-sessions) | Source code for [Tutorial: Diagnose, repair, and commit changes to your skillset](cognitive-search-tutorial-debug-sessions.md). This sample shows you how to use a skillset debug session in the Azure portal. REST is used to create the objects used during debug.|
 | [custom-analyzers](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/custom-analyzers) | Source code for [Tutorial: Create a custom analyzer for phone numbers](tutorial-create-custom-analyzer.md). This sample explains how to use analyzers to preserve patterns and special characters in searchable content.|

articles/search/search-get-started-skillset.md

@@ -195,4 +195,4 @@ If you used a free service, remember that you're limited to three indexes, index
 You can create skillsets using the Azure portal, .NET SDK, or REST API. To further your knowledge, try the REST API by using a REST client and more sample data:
 
 > [!div class="nextstepaction"]
-> [Tutorial: Use skillsets to generate searchable content in Azure AI Search](tutorial-skillset-md)
+> [Tutorial: Use skillsets to generate searchable content in Azure AI Search](tutorial-skillset.md)

articles/search/search-howto-incremental-index.md

@@ -174,7 +174,7 @@ To verify whether the cache is operational, modify a skillset and run the indexe
 
 Skillsets that include image analysis and Optical Character Recognition (OCR) of scanned documents make good test cases. If you modify a downstream text skill or any skill that isn't image-related, the indexer can retrieve all of the previously processed image and OCR content from cache, updating and processing only the text-related changes indicated by your edits.  You can expect to see fewer documents in the indexer execution document count, shorter execution times, and fewer charges on your bill. 
 
-The [file set](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/ai-enrichment-mixed-media) used in [cog-search-demo tutorials](tutorial-skillset-md) is a useful test case because it contains 14 files of various formats JPG, PNG, HTML, DOCX, PPTX, and other types. Change `en` to `es` or another language in the text translation skill for proof-of-concept testing of incremental enrichment.
+The [file set](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/ai-enrichment-mixed-media) used in [cog-search-demo tutorials](tutorial-skillset.md) is a useful test case because it contains 14 files of various formats JPG, PNG, HTML, DOCX, PPTX, and other types. Change `en` to `es` or another language in the text translation skill for proof-of-concept testing of incremental enrichment.
 
 ## Common errors
 
@@ -191,4 +191,4 @@ Incremental enrichment is applicable on indexers that contain skillsets, providi
 + [Incremental enrichment (lifecycle and management)](cognitive-search-incremental-indexing-conceptual.md)
 + [Skillset concepts and composition](cognitive-search-working-with-skillsets.md)
 + [Create a skillset](cognitive-search-defining-skillset.md)
-+ [Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset-md)
++ [Tutorial: Use REST and AI to generate searchable content from Azure blobs](tutorial-skillset.md)

articles/search/search-howto-reindex.md

@@ -327,7 +327,7 @@ Deleting a document doesn't immediately free up space in the index. Every few mi
 
 1. Check the values of the document key field: `search=*&$select=HotelId`. A simple string is straightforward, but if the index uses a base-64 encoded field, or if search documents were generated from a `parsingMode` setting, you might be working with values that you aren't familiar with.
 
-1. [Look up the document](/rest/api/searchservice/documents/get) to verify the value of the document ID and to review its content before deleting it. Specify the key or document ID in the request. The following examples illustrate a simple string for the [Hotels sample index](search-get-started-portal.md) and a base-64 encoded string for the metadata_storage_path key of the [cog-search-demo index](tutorial-skillset-md).
+1. [Look up the document](/rest/api/searchservice/documents/get) to verify the value of the document ID and to review its content before deleting it. Specify the key or document ID in the request. The following examples illustrate a simple string for the [Hotels sample index](search-get-started-portal.md) and a base-64 encoded string for the metadata_storage_path key of the [cog-search-demo index](tutorial-skillset.md).
 
     ```http
     GET https://[service name].search.windows.net/indexes/hotel-sample-index/docs/1111?api-version=2024-07-01