- Added a guideline to delete unused files, classes, or functions to prevent dead code accumulation in `coderule.mdc`.
- Introduced a critical thinking guideline in `meta-rule.mdc` to encourage careful evaluation of user inputs and task specifications.
These updates aim to improve code quality and maintainability by promoting the removal of obsolete code and fostering critical assessment of instructions.
- Delete src/augmentation.py (dead code with broken processed_dir refs after AZ-168)
- Remove dead Augmentator import from manual_run.py
- Move all 5 refactoring tasks from todo/ to done/
- Update autopilot state: Step 7 Refactor complete, advance to Step 8 New Task
- Strengthen tracker.mdc: NEVER use ADO MCP
Made-with: Cursor
- Added a guideline to place all source code under the `src/` directory in `coderule.mdc`.
- Removed the outdated guideline regarding the `src/` layout in `python.mdc` to streamline project structure.
These updates improve project organization and maintainability by clarifying the structure for source code and project files.
- Modified `.gitignore` to include test fixture data while excluding test results.
- Updated `config.yaml` to change the model from 'yolo11m.yaml' to 'yolo26m.pt'.
- Enhanced `.cursor/rules/coderule.mdc` with additional guidelines for test environment consistency and infrastructure handling.
- Revised autopilot state management in `_docs/_autopilot_state.md` to reflect current progress and tasks.
- Removed outdated augmentation tests and adjusted dataset formation tests to align with the new structure.
These changes streamline the configuration and testing processes, ensuring better organization and clarity in the project.
- Rewrite autopilot flow resolution to 4 deterministic rules based on source code + docs + state file presence
- Replace all hard-coded Jira references with tracker-agnostic terminology across 30+ files
- Move project-management.mdc to _project.md (project-specific, not portable with .cursor)
- Rename FINAL_implementation_report.md to context-dependent names (implementation_report_tests/features/refactor)
- Remove "acknowledged tech debt" option from test-run — failing tests must be fixed or removed
- Add debug/error recovery protocol to protocols.md
- Align directory paths: metrics -> 06_metrics/, add 05_security/, reviews/, 02_task_plans/ to README
- Add missing skills (test-spec, test-run, new-task, ui-design) to README
- Use language-appropriate comment syntax for Arrange/Act/Assert in coderule + testing rules
- Copy updated coderule.mdc to parent suite/.cursor/rules/
- Raise max task complexity from 5 to 8 points in decompose
- Skip test-spec Phase 4 (script generation) during planning context
- Document per-batch vs post-implement test run as intentional
- Add skill-internal state cross-check rule to state.md
- Changed the directory structure for task specifications to include a dedicated `todo/` folder within `_docs/02_tasks/` for tasks ready for implementation.
- Updated references in various skills and documentation to reflect the new task lifecycle, including changes in the `implementer` and `decompose` skills.
- Enhanced the README and flow documentation to clarify the new task organization and its implications for the implementation process.
These updates improve task management clarity and streamline the implementation workflow.
- Modified `.gitignore` to reflect the new path for test results.
- Updated `docker-compose.test.yml` to mount the correct test results directory.
- Adjusted `Dockerfile.test` to set the `PYTHONPATH` and ensure test results are saved in the updated location.
- Added `boto3` and `netron` to `requirements-test.txt` to support new functionalities.
- Updated `pytest.ini` to include the new `pythonpath` for test discovery.
These changes streamline the testing process and ensure compatibility with the updated directory structure.
- Introduced `ApiClient` for handling API interactions, including file uploads and downloads.
- Implemented `CDNManager` for managing CDN operations with AWS S3.
- Added `Augmentator` class for image augmentation, including bounding box corrections and transformations.
- Created utility functions for annotation conversion and dataset visualization.
- Established a new rules file for sound notifications during human input requests.
These additions enhance the system's capabilities for data handling and user interaction, laying the groundwork for future features.
Simplify autopilot state file to minimal current-step pointer; add execution safety rule to cursor-meta; remove Completed Steps/Key Decisions/Retry Log/Blockers from state template and all references.
- Replaced module-level path variables in constants.py with a structured Pydantic Config class.
- Updated all relevant modules (train.py, augmentation.py, exports.py, dataset-visualiser.py, manual_run.py) to access paths through the new config structure.
- Fixed bugs related to image processing and model saving.
- Enhanced test infrastructure to accommodate the new configuration approach.
This refactor improves code maintainability and clarity by centralizing configuration management.
Oleksandr Bezdieniezhnykh