- Introduced README.md for the PyGhidra Crusader Toolkit, detailing setup and usage instructions.
- Added bootstrap_env.ps1 script to create and refresh the Python virtual environment with necessary packages.
- Implemented _tmp_patch_hidden_cheat_menu.py and _tmp_patch_hidden_cheat_menu_deferred.py scripts for patching specific memory addresses in Ghidra.
- Introduced a new command 'annotate-usecode' to import USECODE IR JSON annotation hints as Ghidra comments on compiled anchors.
- Added argument parsing for multiple IR JSON files, comment type selection, and a dry-run option.
- Implemented logic to read annotation records from the provided IR files and set comments on the corresponding addresses in Ghidra.
- Enhanced JSON schema to include response structure for the new command.
- Enhance `extract_eusecode_flx.py` to derive class event rows with additional metadata including derived body windows and repeated template statuses.
- Introduce `usecode_family_compare.py` for comparing event families, analyzing commonalities in event bodies, and generating reports on identical groups and differences.
- Implement new data structures for managing class event rows and family artifact specifications.
- Update output formats to include derived body information and repeated family regression checks.
- Ensure robust validation of repeated family expectations against actual extracted data.
- Introduced new file `vm_mask_ladder.tsv` containing detailed mappings for Crusader USECODE VM masks and their associated descriptors.
- Added comprehensive documentation in `scummvm-crusader-reference.md` outlining the structure, findings, and implications for reverse-engineering the Crusader engine within ScummVM.
- Created `usecode-roundtrip-ir.md` to document the plan for converting Crusader USECODE bytes into a human-readable format, detailing the container layout, event names, and intrinsic tables.
- Implemented a PowerShell script `temp_usecode_sample.ps1` for extracting and analyzing USECODE data from the Crusader FLX files, providing insights into class and event structures.
- Implemented a Python script to extract data from the EUSECODE.FLX file format.
- Defined data structures for candidate entries and extracted chunks using dataclasses.
- Added functions to read and parse the FLX table, extract candidate data, and generate human-readable output files.
- Included functionality for analyzing extracted data, including generating summaries, descriptors, and event family reports.
- Implemented utilities for calculating printable ratios, zero ratios, and identifying text-like data.
- Added support for writing various output formats, including JSON, TSV, and Markdown.
