thiagomvas/FFlow

AI Summary: Create a new NuGet package, `FFlow.Steps.FileIO`, for the FFlow workflow automation library. This package should contain reusable workflow steps for common file I/O operations (create directory, read file, write file, copy file) using the existing fluent API style. The steps should handle errors consistently and be easily testable.

AI Summary: Implement a new FFlow package, `FFlow.Steps.Script`, containing steps to execute PowerShell and Bash scripts. This involves creating a generic interface for script execution, implementing specific steps for each scripting language, handling output capture (stdout, stderr), error management, timeouts, cancellation, security considerations, and writing comprehensive tests. Documentation of usage and language-specific options is also required.

AI Summary: Implement undo/compensation logic in the FFlow workflow library. This involves creating an interface or method for steps to define compensation actions, configuring compensation in the workflow builder, extending the runtime to execute compensation on failures, ensuring correct compensation order, and adding comprehensive unit tests and documentation.

AI Summary: Enhance the FFlow workflow library to support attaching metadata (name, description, tags) to workflow steps and workflows. This involves extending the `FlowStep` class or using attributes, modifying the builder API to allow metadata setting, ensuring metadata accessibility during runtime and by event listeners, updating documentation, and writing comprehensive tests.

AI Summary: Develop a secure credential management package for the FFlow workflow automation library. This involves creating an abstraction for storing and retrieving credentials (API keys, tokens, passwords), supporting scoped credentials, credential rotation, and providing secure usage guidelines. The package should integrate seamlessly with FFlow's workflow execution and leverage existing dependency injection.

AI Summary: Implement reusable workflow steps for HTTP operations (GET, POST, PUT, DELETE) within the FFlow .NET workflow automation library. These steps should support headers, query parameters, request body serialization (JSON, XML), response parsing, and integration with the existing WorkflowContext. Thorough unit and integration tests, along with usage documentation and examples, are also required.

AI Summary: Implement workflow persistence for the FFlow library, allowing long-running workflows to be paused and resumed. This involves creating interfaces for serialization/deserialization, implementing in-memory persistence, supporting pluggable providers (e.g., file system, database), extending the workflow runtime to save state, enabling workflow resumption, providing example implementations, writing integration tests, and documenting the feature.

AI Summary: Implement a console event logger for the FFlow workflow automation library. This involves creating a class that implements the IFlowEventListener interface and logs workflow and step events (start, completion, failure) to the console, including timestamps. Example usage should be added to the documentation.