# Lens Protocol The OpenRank APIs for Profile scoring aim to surface individual profile scores and highlight socially acceptable attestations within the Lens ecosystem, while the content recommendation system focuses on surfacing new and engaging posts through ranking and classification. Additionally, our platform provides personalization algorithms that suggest profiles and posts relevant to each individual's social network and interests, enhancing the overall user experience within the Lens ecosystem. Our APIs for profile scores and personalized recommendations help builders in the Lens ecosystem deliver highly relevant and engaging social experiences by giving them access to a readily-available recommendation service and allowing them to focus on building amazing user experiences. Developers: * Get started with [**demos and tutorials**](https://docs.karma3labs.com/lens-protocol/getting-started-demos) * We published the [**documentation**](https://docs.karma3labs.com/lens-protocol/ranking-strategies-on-lens) describing pre-configured reputation scoring strategies * Developers can tryout the API via [**OpenAPI**](https://openapi.lens.k3l.io/) using the 4 initial [**scoring strategies**](https://docs.karma3labs.com/lens-protocol/ranking-strategies-on-lens) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.openrank.com/integrations/lens-protocol.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.