We've added 10 custom agents from AgentWarehouse into .github/agents/ to help with tasks ranging from architecture design and quantitative research to documentation and data visualization. These profiles provide structured implementation, auditing, and analysis support directly in our repository. This addition should significantly speed up our development and quality assurance workflows!

We have integrated a suite of 10 specialized agents into the .github/agents/ directory, imported directly from the AgentWarehouse repository. This update introduces distinct roles ranging from BUILDER and DOCUMENTER to OPTIMIZER and VALIDATOR, each with clear philosophies and operational guidelines to streamline the development workflow and improve output consistency. By delegating tasks to these tailored personas, we aim to enhance both the quality and predictability of our automated tasks.

Updated the visualization output module to provide cleaner, more professional figures for the Linear A statistics report. Specifically, I removed overhead text labels from the site map and streamlined the histogram subtitle for readability.

Updated the project's data figures and report statistics to reflect the latest state of the corpus. This ensures that all visualizations and embedded documentation accurately represent current data trends.

Updated the project README to better reflect the current state of the database, clarifying methodology and the provenance of the encoded artefacts. This change ensures better transparency regarding data coverage, quality confidence metrics, and source attribution for users of the Linear A research tool.

This release wraps up several visual and structural cleanup tasks, including removing redundant chart subtitles, surfacing additional corpus statistics in tables, and improving the document narrative flow. Visuals in builder_lina_stats.py were polished for clarity, and total number formatting was updated to be more readable. These changes ensure the documentation and reporting remain professional as the project matures.

This update delivers a comprehensive cleanup of the project documentation and statistical reporting tools. We have refined the README's structure for clarity—specifically regarding methodology, limitations, and assumptions—and updated the codebase to improve the visual consistency and accuracy of generated corpus statistics and charts.

Updated the documentation in README.md to better represent the database corpus coverage by adding a site coverage figure and cleaning up outdated table references. This improves the readability and accuracy of the project overview for anyone exploring the Linear A database metrics.