- Add `language_model` field to robot data structures for LLM connector overrides.
- Update `AgentCaller` to utilize the robot's language model and include logging capabilities for agent calls.
- Refactor task execution to log task outputs and inputs, improving observability during execution.
- Modify tests to accommodate changes in the runner initialization and ensure proper logging functionality.
- Implement V2 execution model in the standard executor, simplifying task execution to a single call without validation loops.
- Introduce support for resuming suspended executions, allowing for human input during task processing.
- Enhance event handling by pushing task completion and failure events to the event bus for better tracking and integration.
- Update tests to reflect changes in execution flow and ensure robust handling of task statuses and results.
- Updated MCP task executor ID format to use "mcp_server.mcp_tool" for better clarity and consistency.
- Added required MCP-specific fields (`mcp_server` and `mcp_tool`) to the Task struct and validation logic.
- Enhanced documentation in DESIGN.md and TECHNICAL.md to reflect changes in MCP task structure and requirements.
- Improved error handling in ExecuteMCPTask to ensure proper validation of MCP task fields before execution.
- Introduced a new `Description` field in the `Task` struct for a human-readable task description, improving UI clarity.
- Updated the `ParseTask` function to save the description from input data and convert it to a message if no explicit messages are provided.
- Enhanced the `Executor` to update UI fields with localized messages during task execution phases, ensuring better user feedback.
- Implemented a new method in the `ExecutionStore` to persist task status updates, allowing real-time UI updates.
- Added unit tests to validate the new task description handling and UI updates during execution phases.
- Added `Name` and `CurrentTaskName` fields to the `Execution` struct for improved UI display during execution phases.
- Implemented localization support for UI messages, allowing dynamic updates based on the execution context and user locale.
- Updated the executor to manage these fields at various phases, ensuring accurate representation of execution status.
- Enhanced OpenAPI documentation to reflect the new fields and their usage in execution responses.
- Added unit tests to validate the functionality of UI fields and localization handling.
- Marked P1 Goals and P2 Tasks as completed in TODO.md, reflecting the successful implementation of goal generation and task planning functionalities.
- Updated the input formatter to include delivery target details in the goal output, ensuring tasks are designed for appropriate delivery methods.
- Enhanced the RunTasks method to validate goals and parse tasks from agent responses, including comprehensive error handling and task validation.
- Added unit tests for new task parsing and validation features, ensuring robust coverage of task generation and execution scenarios.
- Revised documentation to clarify the integration of validation rules and expected outputs in task management.
- Introduced multiple executor modes (Standard, DryRun, Sandbox) to accommodate various use cases, enhancing flexibility in execution strategies.
- Updated DESIGN.md to reflect the new executor modes and their respective use cases, including detailed descriptions and configuration examples.
- Revised TECHNICAL.md to outline the new executor package structure, emphasizing the modular design for future enhancements.
- Enhanced the TODO.md to track the progress of executor mode implementations and related tasks.
- Removed outdated executor stub files and tests, streamlining the codebase for improved maintainability.
- Updated integration tests to utilize the new DryRun executor, ensuring comprehensive coverage of execution scenarios without real agent calls.
