> ## Documentation Index
> Fetch the complete documentation index at: https://docs.uselayers.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Test content search with the API

> Run content search requests against your blog articles, knowledge base, and pages, then use response scores to understand result ordering.

## Prerequisites

* Your content index must include the blog articles, knowledge base pages, or Shopify pages you want to search.
* You need API access for the store you want to test.
* You should know which content types you want to search, such as articles, pages, or both.

## What you can test

* Search your blog articles and Shopify pages using natural-language queries.
* Compare result titles, summaries, and scores for representative customer questions.
* Override ranking weights per request when you need to test a different balance of semantic relevance and freshness.
* Use the response metadata to confirm whether the API is returning the expected content type.

## Run a content search

1. Open the [Content Search API reference](/api-reference/search-content).
2. Use a real search query, such as "how to clean leather boots".
3. Review the returned content results and their ranking scores.
4. Repeat the request with a few high-value queries from your store's search analytics.

Content search results may include blog articles and Shopify pages, depending on the request parameters and what your store has indexed.

## Tune ranking weights

Content search supports per-request ranking weight overrides through the API. Use them when you want to test how much semantic relevance and freshness should influence result order.

For example, increase freshness when recent educational content should rank higher. Increase semantic relevance when evergreen content should win because it answers the query more directly.

## Tips

* If results feel too focused on older evergreen content, increase the freshness weight in the API request.
* If recent but less relevant content ranks too high, increase the semantic weight in the API request.
* Use the `content_type` filter in the API to restrict results to only articles or only pages when needed.
* Test weight changes on representative queries before applying them to live content search.

## See also

* [Content search API](/api-reference/search-content) - API reference for executing content searches
* [Ranking relevancy](/platform/ranking-relevancy) - How ranking models work for product search
* [Lab Insights](/help/lab/insights) - Trends, anomalies, and opportunities Layers detected in product search