The integration of intelligent test scripting in API testing tools enables the rapid development of test cases by learning from past test executions. This approach enhances test case creation efficiency and adaptability.

In a lightweight mobile application, where efficiency and simplicity are crucial, RESTful APIs are well-suited. They offer a stateless communication model, enabling lightweight data exchange with minimal overhead. Other options like GraphQL, SOAP API, and WebSockets might introduce unnecessary complexity for such scenarios.

GraphQL's single endpoint approach can increase the attack surface in security testing. While it simplifies testing, it also introduces the risk of more concentrated attacks on a single endpoint, requiring thorough vulnerability assessments to ensure robust security measures.

API testing tools in Agile environments should facilitate easy script maintenance. This ensures that the tests can be quickly adapted to accommodate frequent changes in requirements, a key characteristic of Agile development. Easy maintenance contributes to the flexibility and responsiveness required in Agile workflows.

In GraphQL, the 'Schema' plays a critical role in API design by defining the data structure, types, and relationships within the API. It acts as a contract between the client and server, specifying what data can be queried and how it relates. The schema ensures consistency and clarity in communication between the client and server, making it a fundamental aspect of GraphQL API design.

Latency Testing would be the primary focus to identify delays in response times. It helps pinpoint specific performance issues related to delays in data processing or communication. Baseline Testing establishes a performance baseline for comparison, Regression Testing ensures new changes don't adversely affect performance, and Soak Testing assesses system stability over an extended period but may not be as effective in identifying latency issues.

API testing in Agile thrives on collaboration with development teams. This close collaboration ensures that the API functionality aligns with user stories and meets the expectations of the development and testing teams. Effective communication and collaboration are essential components of successful Agile API testing.

Performance testing is crucial in Continuous Deployment (CD) pipelines, ensuring that the API can handle the expected load and maintain optimal performance. It helps identify and address scalability issues before deploying changes to production.

In the event of a failed API test, it is crucial to check the test logs to identify any errors or issues. Investigating the root cause helps in understanding and resolving the problem, ensuring that the CI pipeline stays reliable. Retrying the failed test without understanding the cause might lead to false positives or missed issues. Skipping the test may result in undetected bugs, and rolling back to the last stable version is a conservative approach to maintain stability.

Equivalence Partitioning is a testing technique where input data is divided into groups to ensure that each group is processed in a similar way. When dealing with invalid input data, raising an exception is a common approach to handle unexpected scenarios and ensure robustness in the API. This helps identify potential issues in how the API handles incorrect or unexpected data.