run prettier

docs/guides/entity-level-caching.md

@@ -7,9 +7,9 @@ Entity-level caching is a crucial technique in optimizing application performanc
 
 ## Understanding Entity-Level Caching:
 
-Entity-level caching involves storing individual data entities in memory to reduce the need for repeated data retrieval. This optimization technique is particularly useful for frequently accessed data that doesn't change frequently. By caching entities, we can improve application response times and reduce the load on backend services.
+Entity-level caching involves storing individual data entities in memory to reduce the need for repeated data retrieval. This optimization technique is frequently useful for frequently accessed data that doesn't change frequently. By caching entities, we can improve application response times and reduce the load on backend services.
 
-## Using Tailcall for Entity-Level Caching 
+## Using Tailcall for Entity-Level Caching
 
 Tailcall simplifies entity-level caching within GraphQL schemas through its @cache directive, offering an efficient way to optimize performance by minimizing redundant data fetching. Here's how you can leverage Tailcall's `@cache` directive to implement caching and an example to illustrate its usage:
 
@@ -52,7 +52,8 @@ This example demonstrates how Tailcall's @cache operator can be used to efficien
 
 - **Over-caching:** Avoid caching unnecessary or transient data to prevent excessive memory usage.
 - **Cache Invalidation:** Implement robust cache invalidation strategies to ensure data consistency and prevent stale data.
-- **Performance Monitoring:** Regularly monitor cache performance and usage to identify bottlenecks and optimize caching strategies.
+- **Performance Monitoring:** Monitor cache performance and usage to identify bottlenecks and optimize caching strategies.
 
 ## Conclusion:
-Entity-level caching using Tailcall in GraphQL schemas offers a powerful means of optimizing API performance by minimizing redundant data fetching. By leveraging Tailcall's `@cache` operator and following best practices, developers can efficiently cache individual data entities, improve response times, and enhance overall system scalability and reliability.
+
+Entity-level caching using Tailcall in GraphQL schemas offers a powerful means of optimizing API performance by minimizing redundant data fetching. By leveraging Tailcall's `@cache` operator and following best practices, developers can efficiently cache individual data entities, improve response times, and enhance overall system scalability and reliability.